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137 results on '"Écophysiologie des Plantes sous Stress environnementaux (LEPSE)"'

1. Epigenetics for Plant Improvement: Current Knowledge and Modeling Avenues

Author

Nathalie Leblanc-Fournier, Denis Vile, Zhanwu Dai, Philippe Gallusci, Arnaud Gauffretau, Michel Génard, Céline Richard-Molard, Sophie Brunel-Muguet, Unité de recherche Plantes et Systèmes de Culture Horticoles (PSH), Institut National de la Recherche Agronomique (INRA), Laboratoire de Physique et Physiologie Intégratives de l'Arbre Fruitier et Forestier (PIAF), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Ecophysiologie Végétale, Agronomie et Nutritions (EVA), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Recherche Agronomique (INRA), Laboratoire de Physique et Physiologie Intégratives de l’Arbre en environnement Fluctuant (PIAF), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Unité de recherche Plantes et Systèmes de Culture Horticoles ( PSH ), Institut National de la Recherche Agronomique ( INRA ), Laboratoire de Physique et Physiologie Intégratives de l'Arbre Fruitier et Forestier ( PIAF ), Institut National de la Recherche Agronomique ( INRA ) -Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes ( ECOSYS ), Institut National de la Recherche Agronomique ( INRA ) -AgroParisTech, Écophysiologie des Plantes sous Stress environnementaux ( LEPSE ), Centre international d'études supérieures en sciences agronomiques ( Montpellier SupAgro ) -Institut National de la Recherche Agronomique ( INRA ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Ecophysiologie Végétale, Agronomie et Nutritions ( EVA ), Université de Caen Normandie ( UNICAEN ), Normandie Université ( NU ) -Normandie Université ( NU ) -Institut National de la Recherche Agronomique ( INRA ), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Institut National de la Recherche Agronomique (INRA)-Université de Caen Normandie (UNICAEN), and Normandie Université (NU)-Normandie Université (NU)

Subjects
0106 biological sciences, 0301 basic medicine, [ SDV.BV ] Life Sciences [q-bio]/Vegetal Biology, Process (engineering), plasticité phénotypique, régulateur du développement des plantes, intensive husbandry, adaptation, Plant Science, Breeding, Biology, phenotypic plasticity, 01 natural sciences, Epigenesis, Genetic, modelling, 03 medical and health sciences, épigénétique, adaptation au changement, plant breeding, variation epigénétique, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Epigenetics, development, modélisation, 2. Zero hunger, Genetic diversity, Phenotypic plasticity, Variation épigénétique, epigenetics, business.industry, fungi, food and beverages, modeling, Plants, 15. Life on land, Heritability, contrôle de processus, Adaptation, Physiological, Biotechnology, 030104 developmental biology, Evolutionary biology, Adaptation, changement environnemental, business, environment, élevage intensif, amélioration des plantes, 010606 plant biology & botany
Abstract

Epigenetic variations are involved in the control of plant developmental processes and participate in shaping phenotypic plasticity to the environment. Intense breeding has eroded genetic diversity, and epigenetic diversity now emerge as a new source of phenotypic variations to improve adaptation to changing environments and ensure the yield and quality of crops. Here, we review how the characterization of the stability and heritability of epigenetic variations is required to drive breeding strategies, which can be assisted by process-based models. We propose future directions to hasten the elucidation of complex epigenetic regulatory networks that should help crop modelers to take epigenetic modifications into account and assist breeding strategies for specific agronomical traits.

Published
2017

2. Global wellposedness for a class of reaction–advection–anisotropic-diffusion systems

Author

Guillaume Rolland, André Fischer, Dieter Bothe, Michel Pierre, Mathematical Modeling and Analysis, Darmstadt University of Technology [Darmstadt], École normale supérieure - Rennes (ENS Rennes), Institut de Recherche Mathématique de Rennes (IRMAR), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), École normale supérieure - Rennes ( ENS Rennes ), Institut de Recherche Mathématique de Rennes ( IRMAR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -AGROCAMPUS OUEST-École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National des Sciences Appliquées ( INSA ) -Université de Rennes 2 ( UR2 ), Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ), Écophysiologie des Plantes sous Stress environnementaux ( LEPSE ), Centre international d'études supérieures en sciences agronomiques ( Montpellier SupAgro ) -Institut National de la Recherche Agronomique ( INRA ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-INSTITUT AGRO Agrocampus Ouest

Subjects
Class (set theory), Anisotropic diffusion, Structure (category theory), Type (model theory), 01 natural sciences, Mathematics - Analysis of PDEs, [ MATH.MATH-AP ] Mathematics [math]/Analysis of PDEs [math.AP], Mathematics (miscellaneous), Reaction-diffusion-advection system, FOS: Mathematics, [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP], 35K57, 92E20, 35K51, 35K59, 92D25, Uniqueness, 0101 mathematics, global existence of weak solutions, Mathematics, 010102 general mathematics, Isotropy, Mathematical analysis, anisotropic diffusion, 010101 applied mathematics, Linear map, Nonlinear system, 35K57, 92E20, instantaneous reaction limit, control of mass, Analysis of PDEs (math.AP)
Abstract

International audience; We prove existence and uniqueness of global solutions for a class of reaction-advection-anisotropic-diffusion systems whose reaction terms have a "triangular structure". We thus extend previous results to the case of time-space dependent anisotropic diffusions and with time-space dependent advection terms. The corresponding models are in particular relevant for transport processes inside porous media and in situations in which additional migration occurs. The proofs are based on optimal $L^p$-maximal regularity results for the general time-dependent linear operator dual to the one involved in the considered systems. As an application, we prove global well-posedness for a prototypical class of chemically reacting systems with mass-action kinetics, involving networks of reactions of the type $C_1+\ldots+C_{P-1} \rightleftharpoons C_{P} $. Finally, we analyze how a classical a priori $L^2$-estimate of the solutions, which holds with this kind of nonlinear reactive terms, extends to our general anisotropic-advection framework. It does extend with the same assumptions for isotropic diffusions and is replaced by an $L^{(N+1)/N}$-estimate in the general situation.

Published
2016

3. Sucrose is an early modulator of the key hormonal mechanisms controlling bud outgrowth in Rosa hybrida

Author

Marion Lecerf, Thomas Péron, François Barbier, Stéphanie Boutet-Mercey, Jessica Bertheloot, Benoit Porcheron, Sylvie Citerne, Hanaé Roman, Soulaiman Sakr, Quentin Barrière, Jakub Rolčík, Rémi Lemoine, José Gentilhomme-Le Gourrierec, Nathalie Leduc, Maria-Dolores Perez-Garcia, Institut de Recherche en Horticulture et Semences (IRHS), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA)-Université d'Angers (UA), Laboratory of Growth Regulators, Palacky University and Institute of Experimental Botany ASCR, Institut Jean-Pierre Bourgin (IJPB), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Laboratoire de catalyse en chimie organique (LACCO), Centre National de la Recherche Scientifique (CNRS)-Université de Poitiers, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), SFR QUASAV 4207, Lab Biol & Pathol Vegetales, PRES Université Nantes Angers Le Mans (UNAM), Centre de Recherche des Cordeliers (CRC), Université Paris Diderot - Paris 7 (UPD7)-École pratique des hautes études (EPHE)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Universidad de Salamanca, Salamanca, Spain, Universidad de Salamanca, Ecologie et biologie des interactions (EBI), Université de Poitiers-Centre National de la Recherche Scientifique (CNRS), Université d'Angers (UA)-Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Laboratory of Growth Regulators [Univ Palacký] (LGR), Faculty of Science [Univ Palacký], Palacky University Olomouc-Palacky University Olomouc-Institute of Experimental Botany of the Czech Academy of Sciences (IEB / CAS), Czech Academy of Sciences [Prague] (CAS)-Czech Academy of Sciences [Prague] (CAS), Sucres & Echanges Végétaux-Environnement (SEVE), Université de Poitiers-Centre National de la Recherche Scientifique (CNRS)-Université de Poitiers-Centre National de la Recherche Scientifique (CNRS), Écophysiologie des Plantes sous Stress environnementaux ( LEPSE ), Centre international d'études supérieures en sciences agronomiques ( Montpellier SupAgro ) -Institut National de la Recherche Agronomique ( INRA ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Université Nantes Angers Le Mans, Centre de Recherche des Cordeliers ( CRC ), Université Paris Diderot - Paris 7 ( UPD7 ) -École pratique des hautes études ( EPHE ) -Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Institut de Recherche en Horticulture et Semences ( IRHS ), Université d'Angers ( UA ) -Institut National de la Recherche Agronomique ( INRA ) -AGROCAMPUS OUEST, Institut Jean-Pierre Bourgin ( IJPB ), Institut National de la Recherche Agronomique ( INRA ) -AgroParisTech, Ecologie et biologie des interactions ( EBI ), Université de Poitiers-Centre National de la Recherche Scientifique ( CNRS ), and Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)

Subjects
[ SDV.BV ] Life Sciences [q-bio]/Vegetal Biology, Sucrose, sugar signaling, Physiology, Mutant, Flowers, strigolactones, Plant Science, Biology, Rosa, Rosa sp, Bud burst, Pisum, chemistry.chemical_compound, Plant Growth Regulators, Gene Expression Regulation, Plant, Auxin, shoot branching, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Arabidopsis thaliana, Sugar, ComputingMilieux_MISCELLANEOUS, Plant Proteins, 2. Zero hunger, chemistry.chemical_classification, Indoleacetic Acids, fungi, food and beverages, Biological Transport, sugar signalling, biology.organism_classification, Hedgehog signaling pathway, cytokinins, chemistry, Biochemistry, sugar, Cytokinin, auxin, Research Paper, Signal Transduction
Abstract

Highlight Recent research shows that sugar availability triggers bud outgrowth. This paper further demonstrates that the effect of sucrose involves changes in the hormonal network related to bud outgrowth, and identifies potential hormones involved in sugar control., Sugar has only recently been identified as a key player in triggering bud outgrowth, while hormonal control of bud outgrowth is already well established. To get a better understanding of sugar control, the present study investigated how sugar availability modulates the hormonal network during bud outgrowth in Rosa hybrida. Other plant models, for which mutants are available, were used when necessary. Buds were grown in vitro to manipulate available sugars. The temporal patterns of the hormonal regulatory network were assessed in parallel with bud outgrowth dynamics. Sucrose determined bud entrance into sustained growth in a concentration-dependent manner. Sustained growth was accompanied by sustained auxin production in buds, and sustained auxin export in a DR5::GUS-expressing pea line. Several events occurred ahead of sucrose-stimulated bud outgrowth. Sucrose upregulated early auxin synthesis genes (RhTAR1, RhYUC1) and the auxin efflux carrier gene RhPIN1, and promoted PIN1 abundance at the plasma membrane in a pPIN1::PIN1-GFP-expressing tomato line. Sucrose downregulated both RwMAX2, involved in the strigolactone-transduction pathway, and RhBRC1, a repressor of branching, at an early stage. The presence of sucrose also increased stem cytokinin content, but sucrose-promoted bud outgrowth was not related to that pathway. In these processes, several non-metabolizable sucrose analogues induced sustained bud outgrowth in R. hybrida, Pisum sativum, and Arabidopsis thaliana, suggesting that sucrose was involved in a signalling pathway. In conclusion, we identified potential hormonal candidates for bud outgrowth control by sugar. They are central to future investigations aimed at disentangling the processes that underlie regulation of bud outgrowth by sugar.

Published
2015

4. Genetic variability and plasticity of plant allometry

Author

François Vasseur, Cyrille Violle, Brian J. Enquist, Denis Vile, Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), University of Arizona, Santa Fe Institute, Association Nationale de la Recherche et de la Technologie, Grant/Award Number: 0398/2009-09 42 008, H2020 European Research Council, Grant/Award Number: ERC-StG-2020-949843 PHENOVIGOUR, Région Occitanie Pyrénées-Méditerranée, Grant/Award Number: FEDER FSE IEJ 2014- 2020, ANR-17-CE02-0018,AraBreed,Exploration des réponses évolutives des plantes à des changements environnementaux à la lumière des théories écologiques : un test expérimental chez l'espèce modèle Arabidopsis thaliana(2017), and European Project: 639706,H2020,ERC-2014-STG,CONSTRAINTS(2015)

Subjects
high temperature, [SDV.GEN.GPL]Life Sciences [q-bio]/Genetics/Plants genetics, water stress, Arabidopsis thaliana, intraspecific trait variability, plasticity, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, growth rate, metabolic scaling theory, Ecology, Evolution, Behavior and Systematics
Abstract

International audience; The metabolic scaling theory (MST) predicts quasi-universal trait-size relationships in plants, characterised by a unique allometric exponent within and across large taxonomic scales. However, recent studies have identified variability in allometric relationships, without a clear understanding of the modulating role played by genetic variation and environment.Here, we investigated (1) the allometric relationships for two central traits of MST, namely total leaf area and plant growth rate, in the model species Arabidopsis thaliana, (2) the variability of plant allometries between genotypes and (3) the plastic responses of plant allometries under water deficit, high temperature and their interaction.Using a population of 120 genotypes, we found that intraspecific allometries adhered on average with MST predictions. However, a broad variability but a moderate plasticity in the allometric exponents was observed across genotypes and environments. Allometric exponents were impacted significantly, yet weakly, by water deficit, but not by high temperature. Moreover, genotypes that deviated from MST predictions exhibited more plasticity in trait-size relationships than genotypes that followed MST predictions.Our study suggests that plant allometry is genetically variable and might be related to different adaptive strategies to cope with stressing conditions. Thus, our results highlights the need of assessing trait-size relationships within species to understand the mechanisms of plant adaptation to contrasted environments.

Published
2023

5. A systemic approach to grapevine decline diagnosed using three key indicators: plant mortality, yield loss and vigour decrease

Author

Anne MEROT, Guillaume Coulouma, Nathalie Smits, Elsa Robelot, Christian Gary, Lucia Guerin-Dubrana, Jouanel Poulmach, Xavier Burgun, Anne Pellegrino, Marc Fermaud, Agrosystèmes Biodiversifiés (UMR ABSys), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH), Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Santé et agroécologie du vignoble (UMR SAVE), Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Chambre d'Agriculture de l'Hérault (CA 34), Institut Français de la Vigne et du Vin (IFV), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, and Plan National Dépérissement Viticole (PNDV) / France Agrimer

Subjects
vine mortality, diagnosis, dieback, [SDV]Life Sciences [q-bio], yield loss, vigour, Horticulture, decline, indicators, Food Science
Abstract

International audience; Grapevine decline, a major global viticulture issue, is defined as a multi-year decrease in vine productivity and/or increase in vine mortality. Although grapevine trunk diseases are one of the most studied causes, the decline is multifactorial and associated with more than 70 factors, including abiotic and biotic hazards. With so many factors to consider, the phenomenon is difficult to understand. Our study aims to make it easier to determine and assess grapevine decline by focusing on three key indicators: yield, mortality and vegetative vigour. We investigated the relationships between these indicators from both a temporal and spatial perspective to propose a set of diagnostic indicators. Thus, we conducted a winegrower survey, a historical analysis of grapevine decline and field measurements of the abovementioned indicators on plot networks in three major French winegrowing regions (see graphical abstract): Bordeaux, Cognac and Languedoc. We found that winegrowers' perceptions of decline were consistent with an objective characterisation based on field measurements of the indicators. Although vine mortality progressively spread over the years, neither the survey nor the historical analysis showed a direct link between decline and yield loss. Rather, large yearly fluctuations in yield, which did not systematically decrease over time, account for this finding. As a result, the mortality rate and the normalised difference vegetation index (NDVI) indicators were shown to be earlier indicators of grapevine decline than yield loss (addressed from the yield achievement ratio, YAR). We performed a multifactorial analysis of the overall data set from the three regions to deepen our understanding of the diversity of declining situations and the underlying environmental and management factors contributing to decline. Finally, two ground-based NDVI indicators and an image-analysis methodology using aerial photographs were proposed as easy-to-obtain indicators of grapevine decline. NDVI indicators were linearly correlated with both the YAR and mortality rate. This study provides a better understanding and promising tools for the early diagnosis of grapevine decline.

Published
2023

6. The uncertainty of crop yield projections is reduced by improved temperature response functions

Author

Alex C. Ruane, Peter J. Thorburn, Mikhail A. Semenov, Joost Wolf, Claudio O. Stöckle, Pramod K. Aggarwal, Gerard W. Wall, Margarita Garcia-Vila, Matthew P. Reynolds, Eckart Priesack, Jørgen E. Olesen, Enli Wang, Bruce A. Kimball, Jordi Doltra, Iurii Shcherbak, Ehsan Eyshi Rezaei, Jeffrey W. White, Leilei Liu, L. A. Hunt, Senthold Asseng, Frank Ewert, Yan Zhu, Fulu Tao, Christoph Müller, Daniel Wallach, Christian Biernath, Davide Cammarano, Mohamed Jabloun, Zhigan Zhao, Michael J. Ottman, Pierre Martre, Sebastian Gayler, Garry O'Leary, Zhimin Wang, Jakarat Anothai, Elias Fereres, Claas Nendel, Bruno Basso, Thilo Streck, Curtis D. Jones, Andrea Maiorano, Phillip D. Alderman, Andrew J. Challinor, Reimund P. Rötter, Taru Palosuo, Iwan Supit, Katharina Waha, Giacomo De Sanctis, Kurt Christian Kersebaum, Soora Naresh Kumar, Gerrit Hoogenboom, Dominique Ripoche, Pierre Stratonovitch, Ann-Kristin Koehler, Roberto C. Izaurralde, Commonwealth Scientific and Industrial Research Organisation (Australia), Chinese Academy of Sciences, China Scholarship Council, Ministry of Education of the People's Republic of China, Institut National de la Recherche Agronomique (France), European Commission, International Food Policy Research Institute (US), CGIAR (France), Department of Agriculture (US), Federal Ministry of Education and Research (Germany), Deutsche Gesellschaft für Internationale Zusammenarbeit, Danish Council for Strategic Research, Federal Ministry of Food and Agriculture (Germany), Finnish Ministry of Agriculture and Forestry, National Natural Science Foundation of China, Helmholtz Association, Grains Research and Development Corporation (Australia), Texas AgriLife Research, Texas A&M University, National Institute of Food and Agriculture (US), CSIRO, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), College of Agronomy and Biotechnology, Southwest University, Institute of Crop Science and Resource Conservation, Division of Plant Nutrition-University of Bonn, Institute of Landscape Systems Analysis, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Department of Crop Sciences, University of Goettingen, Centre of Biodiversity and Sustainable Land Use (CBL), United States Department of Agriculture - Agricultural Research Service, The School of Plant Sciences, University of Arizona, Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Washington State University (WSU), Department of Earth and Environmental Sciences and W.K. Kellogg Biological Station, Michigan State University [East Lansing], Michigan State University System-Michigan State University System, Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Agricultural and Biological Engineering Department, Purdue University [West Lafayette], Institute for Climate and Atmospheric Science [Leeds] (ICAS), School of Earth and Environment [Leeds] (SEE), University of Leeds-University of Leeds, GMO Unit, European Food Safety Authority = Autorité européenne de sécurité des aliments, Cantabrian Agricultural Research and Training Centre, Dep. Agronomia, University of Córdoba [Córdoba], Spanish National Research Council (CSIC), Institute of Soil Science and Land Evaluation, University of Hohenheim, Department of Plant Agriculture, University of Guelph, Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, Texas A&M AgriLife Research and Extension Center, Texas A&M University System, Department of Agroecology, Aarhus University [Aarhus], National Engineering and Technology Center for Information Agriculture, Nanjing Agricutural University, Potsdam Institute for Climate Impact Research (PIK), Centre for Environment Science and Climate Resilient Agriculture (CESCRA), Indian Agricultural Research Institute (IARI), Department of Economic Development, Department of Economic Development, Jobs, Transport and Resources (DEDJTR), Natural Resources Institute Finland, Institute of Crop Science and Resource Conservation (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, UE Agroclim (UE AGROCLIM), Institut National de la Recherche Agronomique (INRA), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Computational and Systems Biology Department, Rothamsted Research, Biological Systems Engineering, University of Wisconsin-Madison, PPS and WSG &CALM, Wageningen University and Research Center (WUR), Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences [Beijing] (CAS), Agriculture and Food, Universidad de La Rioja (UR), UMR : AGroécologie, Innovations, TeRritoires, Ecole Nationale Supérieure Agronomique de Toulouse, China Agricultural University, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), China Agricultural University (CAU), Institute of Crop Science and Resource Conservation [Bonn], Georg-August-University [Göttingen], Arid-Land Agricultural Research Center, Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Department of Agricultural and Biological Engineering [Gainesville] (UF|ABE), Institute of Food and Agricultural Sciences [Gainesville] (UF|IFAS), University of Florida [Gainesville] (UF)-University of Florida [Gainesville] (UF), University of Leeds, European Food Safety Authority (EFSA), Catabrian Agricultural Research and Training Center (CIFA), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), AgWeatherNet Program, Texas A and M AgriLife Research, Jiangsu Collaborative Innovation Center for Modern Crop Production, Landscape and Water Sciences, Natural Resources Institute Finland (LUKE), Agroclim (AGROCLIM), Wageningen University and Research [Wageningen] (WUR), Chinese Academy of Agricultural Sciences (CAAS), AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, European Project: 267196,EC:FP7:PEOPLE,FP7-PEOPLE-2010-COFUND,AGREENSKILLS(2012), Écophysiologie des Plantes sous Stress environnementaux ( LEPSE ), Institut National de la Recherche Agronomique ( INRA ) -Centre international d'études supérieures en sciences agronomiques ( Montpellier SupAgro ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Leibniz Centre for Agricultural Landscape Research, International Maize and Wheat Improvement Center ( CIMMYT ), CGIAR Research Program on Climate Change, Agriculture and Food Security ( CCAFS ), Washington State University ( WSU ), Michigan State University, Institute of Biochemical Plant Pathology ( BIOP ), Institute for Climate and Atmospheric Science, School of Earth and Environment, European Food Safety Authority, Spanish National Research Council ( CSIC ), Texas A and M University ( TAMU ), Potsdam Institute for Climate Impact Research ( PIK ), Centre for Environment Science and Climate Resilient Agriculture ( CESCRA ), Indian Agricultural Research Institute ( IARI ), Department of Economic Development, Jobs, Transport and Resources ( DEDJTR ), University of Bonn (Rheinische Friedrich-Wilhelms), UE Agroclim ( UE AGROCLIM ), Institut National de la Recherche Agronomique ( INRA ), NASA Goddard Institute for Space Studies ( GISS ), NASA Goddard Space Flight Center ( GSFC ), University of Wisconsin-Madison [Madison], Wageningen University and Research Center ( WUR ), Chinese Academy of Sciences [Beijing] ( CAS ), Universidad de La Rioja ( UR ), University of Bonn-Division of Plant Nutrition, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), USDA-ARS : Agricultural Research Service, Consultative Group on International Agricultural Research [CGIAR]-Consultative Group on International Agricultural Research [CGIAR], Natural resources institute Finland, Georg-August-University = Georg-August-Universität Göttingen, Universidad de Córdoba = University of Córdoba [Córdoba], Biotechnology and Biological Sciences Research Council (BBSRC)-Biotechnology and Biological Sciences Research Council (BBSRC), and Université de Toulouse (UT)-Université de Toulouse (UT)

Subjects
Crops, Agricultural, 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], Yield (finance), Water en Voedsel, Growing season, Climate change, klim, Plant Science, Agricultural engineering, Models, Biological, 01 natural sciences, [SHS]Humanities and Social Sciences, Crop, Life Science, Computer Simulation, Productivity, 0105 earth and related environmental sciences, 2. Zero hunger, [ SDE.BE ] Environmental Sciences/Biodiversity and Ecology, WIMEK, Water and Food, Food security, business.industry, Crop yield, Temperature, Agriculture, 04 agricultural and veterinary sciences, 15. Life on land, Climate Resilience, Agronomy, Klimaatbestendigheid, 13. Climate action, [SDE]Environmental Sciences, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Water Systems and Global Change, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, business
Abstract

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections., E.W. acknowledges support from the CSIRO project ‘Enhanced modelling of genotype by environment interactions’ and the project ‘Advancing crop yield while reducing the use of water and nitrogen’ jointly funded by CSIRO and the Chinese Academy of Sciences (CAS). Z.Z. received a scholarship from the China Scholarship Council through the CSIRO and the Chinese Ministry of Education PhD Research Program. P.M., A.M. and D.R. acknowledge support from the FACCE JPI MACSUR project (031A103B) through the metaprogram Adaptation of Agriculture and Forests to Climate Change (AAFCC) of the French National Institute for Agricultural Research (INRA). A.M. received the support of the EU in the framework of the Marie-Curie FP7 COFUND People Programme, through the award of an AgreenSkills fellowship under grant agreement No. PCOFUND-GA-2010-267196. S.A. and D.C. acknowledge support provided by the International Food Policy Research Institute (IFPRI), CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), the CGIAR Research Program on Wheat and the Wheat Initiative. C.S. was funded through USDA National Institute for Food and Agriculture award 32011-68002-30191. C.M. received financial support from the KULUNDA project (01LL0905 L) and the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (BMBF). F.E. received support from the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (2812ERA115) and E.E.R. was funded through the German Federal Ministry of Economic Cooperation and Development (Project: PARI). M.J. and J.E.O. were funded through the FACCE MACSUR project by the Danish Strategic Research Council. K.C.K. and C.N. were funded by the FACCE MACSUR project through the German Federal Ministry of Food and Agriculture (BMEL). F.T., T.P. and R.P.R. received financial support from the FACCE MACSUR project funded through the Finnish Ministry of Agriculture and Forestry (MMM); F.T. was also funded through the National Natural Science Foundation of China (No. 41071030). C.B. was funded through the Helmholtz project ‘REKLIM-Regional Climate Change: Causes and Effects’ Topic 9: ‘Climate Change and Air Quality’. M.P.R. and PD.A. received funding from the CGIAR Research Program on Climate Change, Agriculture, and Food Security (CCAFS). G.O'L. was funded through the Australian Grains Research and Development Corporation and the Department of Economic Development, Jobs, Transport and Resources Victoria, Australia. R.C.I. was funded by Texas AgriLife Research, Texas A&M University. B.B. was funded by USDA-NIFA Grant No: 2015-68007-23133.

Published
2017

7. Solving the grand challenge of phenotypic integration: allometry across scales

Author

François Vasseur, Adrianus Johannes Westgeest, Denis Vile, Cyrille Violle, Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), PHENOVIGOUR grant ERC-StG-2020-949843, ANR-17-CE02-0018,AraBreed,Exploration des réponses évolutives des plantes à des changements environnementaux à la lumière des théories écologiques : un test expérimental chez l'espèce modèle Arabidopsis thaliana(2017), and European Project: 639706,H2020,ERC-2014-STG,CONSTRAINTS(2015)

Subjects
Genome size, Allometry, Phenotype, Phenotypic integration, Insect Science, Metabolic scaling, Genetics, Body Size, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Animal Science and Zoology, Plant Science, General Medicine, Trait relationships
Abstract

Phenotypic integration is a concept related to the cascade of trait relationships from the lowest organizational levels, i.e. genes, to the highest, i.e. whole-organism traits. However, the cause-and-effect linkages between traits are notoriously difficult to determine. In particular, we still lack a mathematical framework to model the relationships involved in the integration of phenotypic traits. Here, we argue that allometric models developed in ecology offer testable mathematical equations of trait relationships across scales. We first show that allometric relationships are pervasive in biology at different organizational scales and in different taxa. We then present mechanistic models that explain the origin of allometric relationships. In addition, we emphasized that recent studies showed that natural variation does exist for allometric parameters, suggesting a role for genetic variability, selection and evolution. Consequently, we advocate that it is time to examine the genetic determinism of allometries, as well as to question in more detail the role of genome size in subsequent scaling relationships. More broadly, a possible—but so far neglected—solution to understand phenotypic integration is to examine allometric relationships at different organizational levels (cell, tissue, organ, organism) and in contrasted species.

Published
2022

8. Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environment

Author

Dueri, Sibylle, Brown, Hamish, Asseng, Senthold, Ewert, Frank, Webber, Heidi, George, Mike, Craigie, Rob, Guarin, Jose Rafael, Pequeno, Diego N.L., Stella, Tommaso, Ahmed, Mukhtar, Alderman, Phillip D., Basso, Bruno, Berger, Andres G., Mujica, Gennady Bracho, Cammarano, Davide, Chen, Yi, Dumont, Benjamin, Rezaei, Ehsan Eyshi, Fereres, Elias, Ferrise, Roberto, Gaiser, Thomas, Gao, Yujing, Garcia-Vila, Margarita, Gayler, Sebastian, Hochman, Zvi, Hoogenboom, Gerrit, Kersebaum, Kurt C., Nendel, Claas, Olesen, Jørgen E., Padovan, Gloria, Palosuo, Taru, Priesack, Eckart, Pullens, Johannes W.M., Rodríguez, Alfredo, Rötter, Reimund P., Ramos, Margarita Ruiz, Semenov, Mikhail A., Senapati, Nimai, Siebert, Stefan, Srivastava, Amit Kumar, Stöckle, Claudio, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Wang, Enli, Weber, Tobias Karl David, Xiao, Liujun, Zhao, Chuang, Zhao, Jin, Zhao, Zhigan, Zhu, Yan, Martre, Pierre, Rebetzke, Greg, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), The New Zealand Institute for Plant & Food Research Limited [Auckland] (Plant & Food Research), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Institut für Nutzpflanzenwissenschaften und Ressourcenschutz (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, Brandenburg University of Technology [Cottbus – Senftenberg] (BTU), Foundation for Arable Research (FAR), University of Florida [Gainesville] (UF), Earth Institute at Columbia University, Columbia University [New York], International Maize and Wheat Improvement Center (CIMMYT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Swedish University of Agricultural Sciences (SLU), Pir Mehr Ali Shah Arid Agriculture University = PMAS-Arid Agriculture University Rawalpindi (AAUR), Oklahoma State University [Stillwater] (OSU), Michigan State University [East Lansing], Michigan State University System, Instituto Nacional de Investigación Agropecuaria (INIA), Georg-August-University = Georg-August-Universität Göttingen, Aarhus University [Aarhus], Institute of geographical sciences and natural resources research [CAS] (IGSNRR), Chinese Academy of Sciences [Beijing] (CAS), Gembloux Agro-Bio Tech [Gembloux], Université de Liège, Instituto de Agricultura Sostenible - Institute for Sustainable Agriculture (IAS CSIC), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Universidad de Córdoba = University of Córdoba [Córdoba], Department of Agriculture, Food, Environment and Forestry (DAGRI), Università degli Studi di Firenze = University of Florence (UniFI), Institute of Crop Science and Resource Conservation [Bonn] (INRES), University of Hohenheim, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Global Change Research Centre (CzechGlobe), University of Potsdam = Universität Potsdam, Natural Resources Institute Finland (LUKE), Helmholtz Zentrum München = German Research Center for Environmental Health, German Research Center for Environmental Health - Helmholtz Center München (GmbH), Institute of Biochemical Plant Pathology (BIOP), Centro de Estudios e Investigación para la Gestión de Riesgos Agrarios y Medioambientales (CEIGRAM), Universidad Politécnica de Madrid (UPM), Universidad de Castilla-La Mancha = University of Castilla-La Mancha (UCLM), Centre for Biodiversity and Sustainable Land-use [University of Göttingen] (CBL), Rothamsted Research, Biotechnology and Biological Sciences Research Council (BBSRC), Washington State University (WSU), Wageningen University and Research [Wageningen] (WUR), Zhejiang University, Nanjing Agricultural University (NAU), China Agricultural University (CAU), Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Phase 4 and was supported by the French National Research Institute for Agriculture, Food (INRAE) and the International Maize and Wheat Improvement Center (CIMMYT) through the International Wheat Yield Partnership (IWYP, grant IWYP115)., metaprogram Agriculture and forestry in the face of climate change: adaptation and mitigation (CLIMAE) of INRAE, grant-aided support from the Biotechnology and Biological Sciences Research Council (BBSRC) through Designing Future Wheat [BB/P016855/1] and Achieving Sustainable Agricultural Systems [NE/N018125/1] jointly funded with NERC, DivCSA project funded by the Academy of Finland (decision no. 316215)., National Natural Science Foundation of China (No. 31761143006), financial support from BARISTA project (031B0811A) through ERA-NET SusCrop under EU-FACCE JPI, German Federal Ministry of Education and Research (BMBF) through the BonaRes project ’’I4S’’ (031B0513I), German Federal Ministry of Education and Research (BMBF) through the BonaRes Project 'Soil3' (FKZ 031B0026A), Ministry of Education, Youth and Sports of Czech Republic through SustES—Adaption strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/000797), Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2070 – 390732324', German Research Foundation (DFG, Grant Agreement SFB 1253/1 2017), European Project: 618105,EC:FP7:KBBE,FP7-ERANET-2013-RTD,FACCE ERA NET PLUS(2013), Institut National de la Recherche Agronomique (France), International Maize and Wheat Improvement Center, International Wheat Yield Partnership, National Natural Science Foundation of China, European Commission, Federal Ministry of Education and Research (Germany), Ministry of Education, Youth and Sports (Czech Republic), German Research Foundation, Biotechnology and Biological Sciences Research Council (UK), Natural Environment Research Council (UK), and Academy of Finland

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Physiology, Climate Change, sowing date, Plant Science, CHINA, Multi-model Ensemble, New Zealand, Sowing Date, Sowing Density, Tiller Mortality, Tillering, Wheat, Yield Potential, tillering, wheat, USE EFFICIENCY, sowing density, Life Science, Biomass, ADAPTATION, PLANT-DENSITY, Triticum, METAANALYSIS, Multi-model ensemble, WIMEK, CLIMATE-CHANGE, tiller mortality, PRODUCTIVITY, Temperature, CROP MODELS, yield potential, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, ROTATION, GROWTH, Water Systems and Global Change, Seasons
Abstract

Crop multi-model ensembles (MME) have proven to be effective in increasing the accuracy of simulations in modelling experiments. However, the ability of MME to capture crop responses to changes in sowing dates and densities has not yet been investigated. These management interventions are some of the main levers for adapting cropping systems to climate change. Here, we explore the performance of a MME of 29 wheat crop models to predict the effect of changing sowing dates and rates on yield and yield components, on two sites located in a high-yielding environment in New Zealand. The experiment was conducted for 6 years and provided 50 combinations of sowing date, sowing density and growing season. We show that the MME simulates seasonal growth of wheat well under standard sowing conditions, but fails under early sowing and high sowing rates. The comparison between observed and simulated in-season fraction of intercepted photosynthetically active radiation (FIPAR) for early sown wheat shows that the MME does not capture the decrease of crop above ground biomass during winter months due to senescence. Models need to better account for tiller competition for light, nutrients, and water during vegetative growth, and early tiller senescence and tiller mortality, which are exacerbated by early sowing, high sowing densities, and warmer winter temperatures., This study was a part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Phase 4 and was supported by the French National Research Institute for Agriculture, Food (INRAE) and the International Maize and Wheat Improvement Center (CIMMYT) through the International Wheat Yield Partnership (IWYP, grant IWYP115). SD and PM acknowledge support from the metaprogram Agriculture and forestry in the face of climate change: adaptation and mitigation (CLIMAE) of INRAE. YC and FT acknowledge support from the National Natural Science Foundation of China (No. 31761143006). RPR and GBM acknowledge financial support from BARISTA project (031B0811A) through ERA-NET SusCrop under EU-FACCE JPI. KCK was funded by the German Federal Ministry of Education and Research (BMBF) through the BonaRes project ’’I4S’’ (031B0513I). AS and TG acknowledge funding by the German Federal Ministry of Education and Research (BMBF) through the BonaRes Project “Soil3” (FKZ 031B0026A). KCK and JEO were supported by the Ministry of Education, Youth and Sports of Czech Republic through SustES—Adaption strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/000797). FE acknowledges support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2070 – 390732324”. TKDW was funded by the German Research Foundation (DFG, Grant Agreement SFB 1253/1 2017). MAS and NS at Rothamsted Research received grant-aided support from the Biotechnology and Biological Sciences Research Council (BBSRC) through Designing Future Wheat [BB/P016855/1] and Achieving Sustainable Agricultural Systems [NE/N018125/1] jointly funded with NERC. TP and FT are supported by the DivCSA project funded by the Academy of Finland (decision no. 316215).

Published
2022

9. Wild Wheat Rhizosphere-Associated Plant Growth-Promoting Bacteria Exudates: Effect on Root Development in Modern Wheat and Composition

Author

Houssein Zhour, Fabrice Bray, Israa Dandache, Guillaume Marti, Stéphanie Flament, Amélie Perez, Maëlle Lis, Llorenç Cabrera-Bosquet, Thibaut Perez, Cécile Fizames, Ezekiel Baudoin, Ikram Madani, Loubna El Zein, Anne-Aliénor Véry, Christian Rolando, Hervé Sentenac, Ali Chokr, Jean-Benoît Peltier, Bray, Fabrice, Institut des Sciences des Plantes de Montpellier (IPSIM), Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), Faculty of Sciences [Lebanese University] | Faculté des Sciences [Université Libanaise], Lebanese University [Beirut] (LU), Miniaturisation pour la Synthèse, l’Analyse et la Protéomique - UAR 3290 (MSAP), Université de Lille-Centre National de la Recherche Scientifique (CNRS), MetaToul Agromix, MetaboHUB-MetaToul, Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Laboratoire de Recherche en Sciences Végétales (LRSV), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Laboratoire des symbioses tropicales et méditerranéennes (UMR LSTM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Laboratoire de Recherche en Sciences Végétales (LRSV), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), and Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
plant–microbiome communication, Organic Chemistry, diazotroph, durum wheat, PGPR, bacterial exudate, metabolomics, proteomics, General Medicine, [SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics, [SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology, Catalysis, Computer Science Applications, Inorganic Chemistry, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [SDV.BV] Life Sciences [q-bio]/Vegetal Biology, Physical and Theoretical Chemistry, Molecular Biology, Spectroscopy, [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis
Abstract

International audience; Diazotrophic bacteria isolated from the rhizosphere of a wild wheat ancestor, grown from its refuge area in the Fertile Crescent, were found to be efficient Plant Growth-Promoting Rhizobacteria (PGPR), upon interaction with an elite wheat cultivar. In nitrogen-starved plants, they increased the amount of nitrogen in the seed crop (per plant) by about twofold. A bacterial growth medium was developed to investigate the effects of bacterial exudates on root development in the elite cultivar, and to analyze the exo-metabolomes and exo-proteomes. Altered root development was observed, with distinct responses depending on the strain, for instance, with respect to root hair development. A first conclusion from these results is that the ability of wheat to establish effective beneficial interactions with PGPRs does not appear to have undergone systematic deep reprogramming during domestication. Exo-metabolome analysis revealed a complex set of secondary metabolites, including nutrient ion chelators, cyclopeptides that could act as phytohormone mimetics, and quorum sensing molecules having inter-kingdom signaling properties. The exo-proteome-comprised strain-specific enzymes, and structural proteins belonging to outer-membrane vesicles, are likely to sequester metabolites in their lumen. Thus, the methodological processes we have developed to collect and analyze bacterial exudates have revealed that PGPRs constitutively exude a highly complex set of metabolites; this is likely to allow numerous mechanisms to simultaneously contribute to plant growth promotion, and thereby to also broaden the spectra of plant genotypes (species and accessions/cultivars) with which beneficial interactions can occur.

Published
2022

10. Optimizing Tomato Water and Fertilizer Uses in Smallholder Farms in South Africa Using the Piloten Model

Author

Nebojsa Jovanovic, W.P. de Clercq, Rami Albasha, Bruno Cheviron, Jean-Claude Mailhol, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Council for Scientific and Industrial Research [Cape Town] (CSIR), Ministery of Science and Technology, Gestion de l'Eau, Acteurs, Usages (UMR G-EAU), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-AgroParisTech-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Water Institute, Stellenbosch University, Centre de Montpellier [IRSTEA], and Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)

Subjects
Irrigation, smallholder farms, 0208 environmental biotechnology, Soil Science, 02 engineering and technology, engineering.material, Tomato, irrigation scheduling, modèle de culture, Crop, Human fertilization, petites exploitations agricoles, [SDV.SA.HORT]Life Sciences [q-bio]/Agricultural sciences/Horticulture, planification de l’irrigation, Tomates, 2. Zero hunger, biology, crop model, planification de la fertilisation, fungi, Irrigation scheduling, food and beverages, Sowing, 04 agricultural and veterinary sciences, 15. Life on land, biology.organism_classification, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, 6. Clean water, 020801 environmental engineering, fertilization scheduling, Agronomy, Soil water, 040103 agronomy & agriculture, engineering, 0401 agriculture, forestry, and fisheries, Environmental science, Fertilizer, Solanum, Agronomy and Crop Science
Abstract

The objectives of this paper are twofold: (i) to calibrate and validate the PILOTEN crop model for tomato (Solanumlycopersicum L.), and (ii) to use the model to examine the response of tomato yield to different irrigation and fertilization schedulingscenarios under varying climatic conditions in order to draw up management recommendations for smallholder farms. Thecalibration and validation were performed by using data collected from field experiments carried out in the north-east of SouthAfrica, on shallow Ferrosol and Luvisol soils. The scenarios dealt with: (i) the initial soil-water availability (fulfilling or not thesoil-water reserve at planting); (ii) the irrigation dose frequency (high versus low irrigation doses ranging from 10 to 40 mm perapplication); (iii) the fertilization dose frequency (full versus split fertilization application). The results indicated that only thefertilization scheduling may significantly affect tomato yields, while irrigation scheduling has a minor role. However, comparedto the local official irrigation guidelines, it is recommended to slightly increase the irrigation doses during the first 4 weeks ofgrowth for tomato grown between early September and mid-December, and to slightly decrease the doses in the second partof the growing cycles starting in February and May. It is also suggested to avoid applying the entire fertilizer dose after seedlingplanting for tomato grown between mid-February and late June; Ce travail a un double objectif: (i) calibrer et valider le modèle Piloten pour la tomate (Solanum lycopersicum L.) et (ii) utiliserle modèle pour analyser la réponse du rendement de la tomate à différents scénarios d’irrigation et de fertilisation, sousdifférentes conditions climatiques, afin de proposer des recommandations de conduites culturales aux petites exploitations.Le calage et la validation du modèle ont été effectués en utilisant des données recueillies par des expérimentations menées dansle nord-est de l’Afrique du Sud, sur des Ferrosols et des Luvisols peu profonds. Les scénarios ont traité: (i) de la disponibilitéinitiale en eau du sol (réserve en eau du sol reconstituée ou non à la plantation); (ii) du couple dose-fréquence d’irrigation(doses d’irrigation élevées à faibles allant de 10 à 40 mm par application); (iii) du couple dose-fréquence de fertilisation.Les résultats ont indiqué que seul le calendrier de la fertilisation peut affecter de manière significative les rendements de latomate, tandis que le calendrier d’irrigation joue un rôle mineur. En comparaison avec les recommandations locales de lagestion de l’irrigation et de la fertilisation de la tomate, il est recommandé d’augmenter légèrement les doses d’irrigation pendantles 4 premières semaines de croissance pour la tomate cultivée entre le début septembre et la mi-décembre, et de diminuerlégèrement les doses dans la deuxième partie du cycle de croissance commençant en février et en mai. Il est également suggéréd’éviter l’application de la totalité de la dose d’engrais après les semis de tomate cultivée entre mi-février et fin-juin

Published
2020

11. A Perspective on Plant Phenomics: Coupling Deep Learning and Near-Infrared Spectroscopy

Author

François Vasseur, Denis Cornet, Grégory Beurier, Julie Messier, Lauriane Rouan, Justine Bresson, Martin Ecarnot, Mark Stahl, Simon Heumos, Marianne Gérard, Hans Reijnen, Pascal Tillard, Benoît Lacombe, Amélie Emanuel, Justine Floret, Aurélien Estarague, Stefania Przybylska, Kevin Sartori, Lauren M. Gillespie, Etienne Baron, Elena Kazakou, Denis Vile, Cyrille Violle, Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, University of Waterloo [Waterloo], Département Systèmes Biologiques (Cirad-BIOS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), University of Tübingen, Institut des Sciences des Plantes de Montpellier (IPSIM), Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), ANR-17-CE02-0018-01 Exploration des réponses évolutives des plantes à des changements environnementaux à la lumière des théories écologiques : un test expérimental chez l’espèce modèle Arabidopsis thaliana – AraBreed, Centre National de la Recherche Scientifique (CNRS)European Commission, German Research Foundation (DFG)INST 37/696-1 FUGG, ANR-17-CE02-0018,AraBreed,Exploration des réponses évolutives des plantes à des changements environnementaux à la lumière des théories écologiques : un test expérimental chez l'espèce modèle Arabidopsis thaliana(2017), and European Project: 639706,H2020,ERC-2014-STG,CONSTRAINTS(2015)

Subjects
multivariate analysis, machine learning, Arabidopsis thaliana, [SDV]Life Sciences [q-bio], near-infrared spectroscopy (NIRS), trait-based ecology, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, functional traits, Plant Science, metabolomics
Abstract

International audience; The trait-based approach in plant ecology aims at understanding and classifying the diversity of ecological strategies by comparing plant morphology and physiology across organisms. The major drawback of the approach is that the time and financial cost of measuring the traits on many individuals and environments can be prohibitive. We show that combining near-infrared spectroscopy (NIRS) with deep learning resolves this limitation by quickly, non-destructively, and accurately measuring a suite of traits, including plant morphology, chemistry, and metabolism. Such an approach also allows to position plants within the well-known CSR triangle that depicts the diversity of plant ecological strategies. The processing of NIRS through deep learning identifies the effect of growth conditions on trait values, an issue that plagues traditional statistical approaches. Together, the coupling of NIRS and deep learning is a promising high-throughput approach to capture a range of ecological information on plant diversity and functioning and can accelerate the creation of extensive trait databases.

Published
2022

12. VviPLATZ1 is a major factor that controls female flower morphology determination in grapevine

Author

Mark R. Thomas, Pat Iocco-Corena, Laurent Torregrosa, Harley M. S. Smith, Jamila Chaïb, Don Mackenzie, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), HM. CLAUSE Iberica SA, Diversité, Adaptation et Amélioration de la Vigne [AGAP] (DAAV), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Wine Australia (CSP 06/01), and CSIRO Agriculture and Food.

Subjects
Agricultural genetics, 0106 biological sciences, Genotype, Science, Dioecy, Stamen, General Physics and Astronomy, Flowers, Biology, 01 natural sciences, Article, General Biochemistry, Genetics and Molecular Biology, Domestication, Magnoliopsida, Self incompatability, 03 medical and health sciences, Hermaphrodite, Gene Expression Regulation, Plant, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Vitis, Allele, Gene, Alleles, Plant Proteins, 030304 developmental biology, Gene Editing, Genetics, 0303 health sciences, Multidisciplinary, Reproduction, Homozygote, fungi, Plant morphogenesis, food and beverages, Cell Differentiation, General Chemistry, Mating system, Phenotype, DNA-Binding Proteins, Differentiation, 010606 plant biology & botany
Abstract

Plant genetic sex determinants that mediate the transition to dioecy are predicted to be diverse, as this type of mating system independently evolved multiple times in angiosperms. Wild Vitis species are dioecious with individuals producing morphologically distinct female or male flowers; whereas, modern domesticated Vitis vinifera cultivars form hermaphrodite flowers capable of self-pollination. Here, we identify the VviPLATZ1 transcription factor as a key candidate female flower morphology factor that localizes to the Vitis SEX-DETERMINING REGION. The expression pattern of this gene correlates with the formation reflex stamens, a prominent morphological phenotype of female flowers. After generating CRISPR/Cas9 gene-edited alleles in a hermaphrodite genotype, phenotype analysis shows that individual homozygous lines produce flowers with reflex stamens. Taken together, our results demonstrate that loss of VviPLATZ1 function is a major factor that controls female flower morphology in Vitis., Unlike wild Vitis species, which produce either female or male flowers, modern grapevine cultivars form hermaphrodite flowers for self-pollination. Here, the authors report that the VviPLATZ1 (plant AT-rich sequence-and zinc-binding protein1) transcription factor functions in controlling female flower morphology determination.

Published
2021

13. Physiological and genetic control of transpiration efficiency in African rice, Oryza glaberrima Steud

Author

Pablo Affortit, Branly Effa-Effa, Mame Sokhatil Ndoye, Daniel Moukouanga, Nathalie Luchaire, Llorenç Cabrera-Bosquet, Maricarmen Perálvarez, Raphaël Pilloni, Claude Welcker, Antony Champion, Pascal Gantet, Abdala Gamby Diedhiou, Baboucarr Manneh, Ricardo Aroca, Vincent Vadez, Laurent Laplaze, Philippe Cubry, Alexandre Grondin, Diversité, adaptation, développement des plantes (UMR DIADE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM), Centre national de la recherche scientifique et technologique (CENAREST), Centre d'Etude Regional Pour l'Amelioration de l'Adaptation A la Secheresse (CERAAS), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Consejo Superior de Investigaciones Científicas [Spain] (CSIC), Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD), Africa Rice Center (AfricaRice), Sahel Regional, Africa Rice Center [Côte d'Ivoire] (AfricaRice), Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Estación Experimental del Zaidín (EEZ), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), LMI Adaptation des Plantes et microorganismes associés aux Stress Environnementaux [Dakar] (LAPSE), Institut de Recherche pour le Développement (IRD), International Crops Research Institute for the Semi-Arid Tropics [Inde] (ICRISAT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Institut de Recherche pour le Développement, the CGIAR Research Program (CRP) on rice-agrifood systems (RICE, 2017-2022), French Ministry of Higher Education (doctoral fellowship), Centre National de la Recherche Scientifique et Technologique of Gabon, ANR-17-MPGA-0011,ICARUS,Improve Crops in Arid Regions and future climates(2017), European Project: 731013 ,EPPN2020(2017), Agence Nationale de la Recherche (France), European Commission, and Centre National de la Recherche Scientifique (France)

Subjects
roots, Physiology, rice, food and beverages, Water, Oryza, Plant Transpiration, Plant Science, transpiration, [SDV.BV.AP]Life Sciences [q-bio]/Vegetal Biology/Plant breeding, Plant Breeding, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, high-throughput phenotyping, Genome-Wide Association Study
Abstract

Improving crop water use efficiency, the amount of carbon assimilated as biomass per unit of water used by a plant, is of major importance as water for agriculture becomes scarcer. In rice, the genetic bases of transpiration efficiency, the derivation of water use efficiency at the whole-plant scale, and its putative component trait transpiration restriction under high evaporative demand remain unknown. These traits were measured in 2019 in a panel of 147 African rice (Oryza glaberrima) genotypes known to be potential sources of tolerance genes to biotic and abiotic stresses. Our results reveal that higher transpiration efficiency is associated with transpiration restriction in African rice. Detailed measurements in a subset of highly contrasted genotypes in terms of biomass accumulation and transpiration confirmed these associations and suggested that root to shoot ratio played an important role in transpiration restriction. Genome wide association studies identified marker-trait associations for transpiration response to evaporative demand, transpiration efficiency, and its residuals, with links to genes involved in water transport and cell wall patterning. Our data suggest that root-shoot partitioning is an important component of transpiration restriction that has a positive effect on transpiration efficiency in African rice. Both traits are heritable and define targets for breeding rice with improved water use strategies., This work was supported by the Institut de Recherche pour le Développement, the CGIAR Research Program (CRP) on rice-agrifood systems (RICE, 2017-2022) and the Agence Nationale de la Recherche (grant ANR-17-MPGA-0011 to VV). Financial support by the Access to Research Infrastructures activity in the Horizon 2020 Programme of the EU (EPPN2020 Grant Agreement 731013) is gratefully acknowledged. PA was supported by a doctoral fellowship from the French Ministry of Higher Education. BEE was supported by the Centre National de la Recherche Scientifique et Technologique of Gabon. The authors acknowledge the IRD iTrop HPC (South Green Platform) at IRD Montpellier for providing HPC resources (https://bioinfo.ird.fr, http://www.southgreen.fr).

Published
2021

14. The genetic interaction of REVOLUTA and WRKY53 links plant development, senescence, and immune responses

Author

Justine Bresson, Jasmin Doll, François Vasseur, Mark Stahl, Edda von Roepenack-Lahaye, Joachim Kilian, Bettina Stadelhofer, James M. Kremer, Dagmar Kolb, Stephan Wenkel, Ulrike Zentgraf, University of Tübingen, Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Michigan State University [East Lansing], Michigan State University System, University of Copenhagen = Københavns Universitet (UCPH), Institutional Strategy of the University of Tuebingen (Deutsche Forschungsgemeinschaft, ZUK 63), Alexander von Humboldt Foundation, and Deutsche Forschungsgemeinschaft (CRC1101, B06)

Subjects
DNA-Binding Proteins, Plant Leaves, [SDV.BV.AP]Life Sciences [q-bio]/Vegetal Biology/Plant breeding, Multidisciplinary, Arabidopsis Proteins, Gene Expression Regulation, Plant, Arabidopsis, Immunity, Plant Development, Plants, Genetically Modified, Salicylic Acid
Abstract

In annual plants, tight coordination of successive developmental events is of primary importance to optimize performance under fluctuating environmental conditions. The recent finding of the genetic interaction of WRKY53, a key senescence-related gene with REVOLUTA, a master regulator of early leaf patterning, raises the question of how early and late developmental events are connected. Here, we investigated the developmental and metabolic consequences of an alteration of the REVOLUTA and WRKY53 gene expression, from seedling to fruiting. Our results show that REVOLUTA critically controls late developmental phases and reproduction while inversely WRKY53 determines vegetative growth at early developmental stages. We further show that these regulators of distinct developmental phases frequently, but not continuously, interact throughout ontogeny and demonstrated that their genetic interaction is mediated by the salicylic acid (SA). Moreover, we showed that REVOLUTA and WRKY53 are keys regulatory nodes of development and plant immunity thought their role in SA metabolic pathways, which also highlights the role of REV in pathogen defence. Together, our findings demonstrate how late and early developmental events are tightly intertwined by molecular hubs. These hubs interact with each other throughout ontogeny, and participate in the interplay between plant development and immunity.

Published
2021

15. Different avenues for progress apply to drought tolerance, water use efficiency and yield in dry areas

Author

François Tardieu, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), ANR-10-BTBR-0001,AMAIZING,Développer de nouvelles variétés de maïs pour une agriculture durable: une approche intégrée de la génomique à la sélection(2010), ANR-11-INBS-0012,PHENOME,Centre français de phénomique végétale(2011), European Project: 731013 ,EPPN2020(2017), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
0106 biological sciences, Yield (finance), Drought tolerance, Biomedical Engineering, Bioengineering, Biology, 01 natural sciences, 03 medical and health sciences, Phenomics, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Water-use efficiency, Sensu stricto, 030304 developmental biology, Transpiration, 2. Zero hunger, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, 0303 health sciences, Phenology, Water, 15. Life on land, Adaptation, Physiological, Conservative strategy, Droughts, Phenotype, Agronomy, 010606 plant biology & botany, Biotechnology
Abstract

International audience; Drought tolerance, water use efficiency (WUE) and yield in dry areas are often considered as synonyms. However, they correspond to markedly different suites of physiological mechanisms, based on combinations of alleles constrained by evolution into consistent strategies. Improving (i) drought tolerance, sensu stricto, involves extreme conservative strategy with protection and repair mechanisms; (ii) WUE most often results in small plants but avenues exist with lower penalties for growth, that is, by reducing night transpiration; (iii) yield for drought prone areas involves both constititutive traits (e.g. phenology or plant architecture), favourable for most environmental scenarios, and adaptive physiological traits whose effects suited to a given scenario. Genetic improvement of the latter would requires identification of scenario-dependent combinations of alleles, involving phenomics, modelling and genomic prediction.

Published
2021

16. Invited review: Intergovernmental Panel on Climate Change, agriculture, and food—A case of shifting cultivation and history

Author

Pete Smith, Pierre Martre, Stuart Mark Howden, Andrew J. Challinor, Christian Bugge Henriksen, John R. Porter, Fonctionnement et conduite des systèmes de culture tropicaux et méditerranéens (UMR SYSTEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Plant and Environmental Sciences, University of Gothenburg (GU), University of Leeds, Climate Change Institute at the Australian National University, Australian National University (ANU), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institute of Biological and Environmental Sciences, University of Aberdeen, and Agropolis Fondation

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Crops, Agricultural, 0106 biological sciences, Livestock, Mitigation policy, 010504 meteorology & atmospheric sciences, Natural resource economics, [SDE.MCG]Environmental Sciences/Global Changes, Climate Change, Climate change, adaptation, 010603 evolutionary biology, 01 natural sciences, Food Supply, mitigation, Shifting cultivation, Animals, Humans, Environmental Chemistry, Adaptation, SolACEWP1, 0105 earth and related environmental sciences, General Environmental Science, 2. Zero hunger, Global and Planetary Change, Food security, Ecology, IPCC, business.industry, Agriculture, food security, 15. Life on land, Impact, climate change, Geography, 13. Climate action, impact, Food processing, business, Working group, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, policy
Abstract

International audience; Since 1990, the Intergovernmental Panel on Climate Change (IPCC) has produced five Assessment Reports (ARs), in which agriculture as the production of food for humans via crops and livestock have featured in one form or another. A constructed database of the ca. 2,100 cited experiments and simulations in the five ARs was analyzed with respect to impacts on yields via crop type, region, and whether adaptation was included. Quantitative data on impacts and adaptation in livestock farming have been extremely scarce in the ARs. The main conclusions from impact and adaptation are that crop yields will decline, but that responses have large statistical variation. Mitigation assessments in the ARs have used both bottom-up and top-down methods but need better to link emissions and their mitigation with food production and security. Relevant policy options have become broader in later ARs and included more of the social and nonproduction aspects of food security. Our overall conclusion is that agriculture and food security, which are two of the most central, critical, and imminent issues in climate change, have been dealt with an unfocussed and inconsistent manner between the IPCC five ARs. This is partly a result of not only agriculture spanning two IPCC working groups but also the very strong focus on projections from computer crop simulation modeling. For the future, we suggest a need to examine interactions between themes such as crop resource use efficiencies and to include all production and nonproduction aspects of food security in future roles for integrated assessment models.

Published
2019

17. Do metabolic changes underpin physiological responses to water limitation in alfalfa (Medicago sativa) plants during a regrowth period?

Author

Llorenç Cabrera-Bosquet, José Luis Araus, Iker Aranjuelo, Gemma Molero, Guillaume Tcherkez, Caroline Mauve, Salvador Nogués, Regina Roca, European Commission, Ministerio de Ciencia y Tecnología (España), Consejo Superior de Investigaciones Científicas (España), Ministerio de Educación y Ciencia (España), International Maize and Wheat Improvement Center (CIMMYT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), University of Barcelona, Australian National University (ANU), Serveis Cientificotècnics (SCT), Universitat de Barcelona (UB), Plateforme Métabolisme-Métabolome (IFR87), Université Paris-Sud - Paris 11 (UP11), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Universidad Pública de Navarra [Espagne] = Public University of Navarra (UPNA), the Spanish Ministry of Science and Technology (CGL2009-13079-C02), i-COOP-suelos y legumbres (2016SU0016) funded by the National Research Council, (Programa Nacional de Formacion de Personal Universitario, AP2005-2916) sponsored by the Spanish Ministry of Education and Science., European Project: 602139,EC:FP7:HEALTH,FP7-HEALTH-2013-INNOVATION-1,PERMED(2013), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), and Universitat de Barcelona

Subjects
Physiology, Water stress, Metabolite, Sequeres, 0208 environmental biotechnology, Growth (Plants), Soil Science, Crops, 02 engineering and technology, Photosynthesis, chemistry.chemical_compound, Botany, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Proline, Medicago sativa, Creixement (Plantes), Earth-Surface Processes, Water Science and Technology, 2. Zero hunger, chemistry.chemical_classification, Pinitol, Chemistry, Alfalfa, fungi, food and beverages, 04 agricultural and veterinary sciences, Metabolism, 15. Life on land, Droughts, 020801 environmental engineering, Amino acid, Conreu, 15N-labeling, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Photorespiration, Agronomy and Crop Science, Metabolite profile
Abstract

Drought is one of the most limiting factors on crop productivity under Mediterranean conditions, where the leguminous species alfalfa (Medicago sativa L.) is extensively cultivated. Whereas the effect of drought on plant performance has been widely described at leaf and nodule levels, less attention has been given to plant-nodule interactions and their implication on metabolites exchange during a regrowth period, when water is limiting. For this purpose, physiological characterization and metabolite profiles in different plant organs and nodules were undertaken under water deficit, including regrowth after removal of aerial parts. In order to study in more detail how nitrogen (N) metabolism was affected by water stress, plants were labelled with N-enriched isotopic air (15N2) using especially designed chambers. Water stress affected negatively water status and photosynthetic machinery. Metabolite profile and isotopic composition analyses revealed that, water deficit induced major changes in the accumulation of amino acids (proline, asparagine, histidine, lysine and cysteine), carbohydrates (sucrose, xylose and pinitol) and organic acids (fumarate, succinate and maleic acid) in the nodules in comparison with other organs. The lower 15N-labeling observed in serine, compared with other amino acids, was related with its high turnover rate, which in turn, indicates its potential implication in photorespiration. Isotopic analysis of amino acids also revealed that proline synthesis in the nodule was a local response to water stress and not associated with a feedback inhibition from the leaves. Water deficit induced extensive reprogramming of whole-plant C and N metabolism, including when the aerial part was removedto trigger regrowth., This study was supported in part by the European research project PERMED (INCO- CT-2004-509140), the Spanish Ministry of Science and Technology (CGL2009-13079-C02) and i-COOP-suelos y legumbres (2016SU0016) funded by the National Research Council. GM was the recipient of a doctoral fellowship (Programa Nacional de Formación de Personal Universitario, AP2005–2916) sponsored by the Spanish Ministry of Education and Science.

Published
2019

18. Sublethal effects of metal toxicity and the measure of plant fitness in ecotoxicological experiments

Author

Julien Nowak, Nathalie Faure, Cédric Glorieux, Denis Vile, Maxime Pauwels, Hélène Frérot, Université de Lille, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Évolution, Écologie et Paléontologie (Evo-Eco-Paleo) - UMR 8198 (Evo-Eco-Paléo (EEP)), Université de Lille-Centre National de la Recherche Scientifique (CNRS), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 (LASIRE), Institut de Chimie du CNRS (INC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), French Ministry of Higher Education, Research and Innovation., and ANR-12-JSV7-0010,ELOCANTH,Evolution de l'adaptation locale en environnement anthropisé(2012)

Subjects
Performance, [SDV]Life Sciences [q-bio], Health, Toxicology and Mutagenesis, food and beverages, General Medicine, Toxicology, Pollution, Sublethal effects, Zinc, Experimental evolution, Metals, Fitness, Brassicaceae, Seeds, Humans, Evolutionary ecotoxicology, [SDV.TOX.ECO]Life Sciences [q-bio]/Toxicology/Ecotoxicology, Biomass, Ecological risk assessment, Environmental Pollution, ComputingMilieux_MISCELLANEOUS
Abstract

International audience; Anthropogenic pollution is a major driver of global environmental change. To be properly addressed, the study of the impact of pollutants must consider both lethal effects and sublethal effects on individual fitness. However, measuring fitness remains challenging. In plants, the total number of seeds produced, i.e. the seed set, is traditionally considered, but is not readily accessible. Instead, performance traits related to survival, e.g., vegetative biomass and reproductive success, can be measured, but their correlation with seed set has rarely been investigated. To develop accurate estimates of seed set, relationships among 15 vegetative and reproductive traits were analyzed. For this purpose, Noccaea caerulescens (Brassicaceae), a model plant to study local adaptation to metalcontaminated environments, was used. To investigate putative variation in trait relationships, sampling included several accessions cultivated in contrasting experimental conditions. To test their applicability, selected estimates were used in the first generation of a Laboratory Natural Selection (LNS) experiment exposing experimentally plants to zinc soil pollution. Principal component analyses revealed statistical independence between vegetative and reproductive traits. Traits showing the strongest positive correlation with seed set were the number of non-aborted silicles, and the product of this number and mean silicle length. They thus appeared the most appropriate to document sublethal or fitness effects of environmental contaminants in plant ecotoxicological studies. The relevance of both estimates was confirmed by using them to assess the fitness of parental plants of the first generation of an LNS experiment: the same families consistently displayed the highest or the lowest performance values in two independent experimental metal-exposed populations. Thus, both these fitness estimates could be used to determine the expected number of offspring and the composition of successive generations in further LNS experiments investigating the impact of multi-generational exposure of a plant species to environmental pollution.

Published
2022

19. Seedling survival under drought differs between an annual (Hordeum vulgare) and a perennial grass (Dactylis glomerata)

Author

Florence Volaire, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)

Subjects
0106 biological sciences, Perennial plant, Physiology, Drought tolerance, DACTYLE AGGLOMERE, Plant Science, 01 natural sciences, 03 medical and health sciences, Poaceae, Water content, 030304 developmental biology, 2. Zero hunger, 0303 health sciences, biology, fungi, food and beverages, 15. Life on land, biology.organism_classification, [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy, Dactylis glomerata, Agronomy, 13. Climate action, Seedling, Hordeum vulgare, Annual plant, RESISTANCE, 010606 plant biology & botany
Abstract

Summary • In semiarid areas, populations of cereal crop plants can be reduced by severe drought occurring during the vegetative stage, leading to subsequent serious yield reduction. This study aimed to analyse and compare survival and dehydration tolerance in two contrasting barley ( Hordeum vulgare ) cultivars (cvs) and in a drought resistant perennial grass, cocksfoot ( Dactylis glomerata ). • In pot experiments, seedlings were subjected to intensifying droughts for analysis of adaptive responses and survival following a range of final soil water potentials (SWP). • Survival rates were 100% in cocksfoot and 32% in the drought resistant barley cv. Tadmor at a SWP of − 2.5 MPa. In cocksfoot, lamina water potentials decreased earlier and water content in enclosed leaf bases stabilized at low SWP. This strategy of dehydration tolerance was associated with high survival. • At moderate water deficit, barley cv. Tadmor exhibited a 5-fold greater osmotic adjustment in lamina, lower senescence and higher accumulation of dehydrins in enclosed leaf bases than the drought sensitive cv. Plaisant. However, under severe drought, water content in enclosed leaf bases declined constantly and was associated with similar mortality in both cvs. Dehydration tolerance was low in barley and not correlated with dehydrin accumulation or resistance to moderate drought.

Published
2021

20. Physiological roles of Casparian strips and suberin in the transport of water and solutes

Author

Marc S. Frenger, Christopher Hidalgo-Shrestha, Zoe Ribeyre, Patrick Diehl, Christophe Maurel, Thierry Simonneau, David E. Salt, Guilhem Reyt, Rochus Franke, Myriam Dauzat, Bertrand Muller, Monica Calvo-Polanco, Yann Boursiac, Biochimie et Physiologie Moléculaire des Plantes (BPMP), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Universidad de Salamanca, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), University of Nottingham, UK (UON), University of Bonn, ERA-NET Coordinating Action in Plant Sciences program project ERACAPS13.089_RootBarriers, the German Research Foundation (DFG, grant FR 1721/2-1 to R.B.F), FEDER-Junta de Castilla y León, CLU-2018-04., Transnational Cooperation within the PLANT-KBBE Initiative, with funding from the German Federal Ministry of Education to RBF, ANR-10-INBS-0004,France-BioImaging,Développment d'une infrastructure française distribuée coordonnée(2010), European Project: 609398,EC:FP7:PEOPLE,FP7-PEOPLE-2013-COFUND,AGREENSKILLSPLUS(2014), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and Universität Bonn = University of Bonn

Subjects
0106 biological sciences, water transport, Arabidopsis thaliana, Physiology, Arabidopsis, Aquaporin, Plant Science, solutes diffusion, 01 natural sciences, Plant Roots, 03 medical and health sciences, suberin, Suberin, Cell Wall, Casparian strips, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, aquaporins, 030304 developmental biology, 0303 health sciences, Water transport, biology, Chemistry, fungi, Plant physiology, food and beverages, Water, biology.organism_classification, Lipids, Apoplast, apoplastic barriers, Biophysics, root hydraulic conductivity, Endodermis, Casparian strip, 010606 plant biology & botany
Abstract

International audience; The formation of Casparian strips (CS) and the deposition of suberin at the endodermis of plant roots are thought to limit the apoplastic transport of water and ions. We investigated the specific role of each of these apoplastic barriers in the control of hydro-mineral transport by roots and the consequences on shoot growth.A collection of Arabidopsis thaliana mutants defective in suberin deposition and/or CS development was characterized under standard conditions using a hydroponic system and the Phenopsis platform.Mutants altered in suberin deposition had enhanced root hydraulic conductivity, indicating a restrictive role for this compound in water transport. In contrast, defective CS directly increased solute leakage and indirectly reduced root hydraulic conductivity. Defective CS also led to a reduction in rosette growth, which was partly dependent on the hydro-mineral status of the plant. Ectopic suberin was shown to partially compensate for defective CS phenotypes. Altogether, our work shows that the functionality of the root apoplastic diffusion barriers greatly influences the plant physiology, and that their integrity is tightly surveyed.

Published
2021

21. Identification of key tissue-specific, biological processes by integrating enhancer information in maize gene regulatory networks

Author

Anthony Venon, Julien Rozière, Johann Joets, Olivier Turc, Stéphanie Pateyron, Marieke L. Kuijjer, Maike Stam, Clémentine Vitte, Maud Fagny, Génétique Quantitative et Evolution - Le Moulon (Génétique Végétale) (GQE-Le Moulon), AgroParisTech-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre for Molecular Medicine Norway (NCMM), Faculty of Medicine [Oslo], University of Oslo (UiO)-University of Oslo (UiO)-Rigshospitalet [Copenhagen], Copenhagen University Hospital-Copenhagen University Hospital, Leiden University Medical Center (LUMC), Swammerdam Institute for Life Sciences (SILS), University of Amsterdam [Amsterdam] (UvA), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut des Sciences des Plantes de Paris-Saclay (IPS2 (UMR_9213 / UMR_1403)), Université d'Évry-Val-d'Essonne (UEVE)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), ANR-10-BTBR-0001,AMAIZING,Développer de nouvelles variétés de maïs pour une agriculture durable: une approche intégrée de la génomique à la sélection(2010), ANR-17-EURE-0007,SPS-GSR,Ecole Universitaire de Recherche de Sciences des Plantes de Paris-Saclay(2017), Investment for the Future ANR-10-BTBR-01-01 Amaizing program, Amaizing, Plant Development & (Epi)Genetics (SILS, FNWI), Universiteit Leiden, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and Université d'Évry-Val-d'Essonne (UEVE)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
0106 biological sciences, Systems biology, Gene regulatory network, Computational biology, Biology, Zea mays, 01 natural sciences, 03 medical and health sciences, mite, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Gene expression, Genetics, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, TIR transposon, Enhancer, gene regulatory networks, Transcription factor, Gene, Original Research, 030304 developmental biology, Epigenomics, 2. Zero hunger, 0303 health sciences, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], husk, Maize, DNA binding site, transcription factor binding sites, enhancers, transposable elements, 010606 plant biology & botany
Abstract

Enhancers are important regulators of gene expression during numerous crucial processes including tissue differentiation across development. In plants, their recent molecular characterization revealed their capacity to activate the expression of several target genes through the binding of transcription factors. Nevertheless, identifying these target genes at a genome-wide level remains a challenge, in particular in species with large genomes, where enhancers and target genes can be hundreds of kilobases away. Therefore, the contribution of enhancers to regulatory network is still poorly understood in plants. In this study, we investigate the enhancer-driven regulatory network of two maize tissues at different stages: leaves at seedling stage and husks (bracts) at flowering. Using a systems biology approach, we integrate genomic, epigenomic and transcriptomic data to model the regulatory relationship between transcription factors and their potential target genes. We identify regulatory modules specific to husk and V2-IST, and show that they are involved in distinct functions related to the biology of each tissue. We evidence enhancers exhibiting binding sites for two distinct transcription factor families (DOF and AP2/ERF) that drive the tissue-specificity of gene expression in seedling immature leaf and husk. Analysis of the corresponding enhancer sequences reveals that two different transposable element families (TIR transposon Mutator and MITE Pif/Harbinger) have shaped the regulatory network in each tissue, and that MITEs have provided new transcription factor binding sites that are involved in husk tissue-specificity.SignificanceEnhancers play a major role in regulating tissue-specific gene expression in higher eukaryotes, including angiosperms. While molecular characterization of enhancers has improved over the past years, identifying their target genes at the genome-wide scale remains challenging. Here, we integrate genomic, epigenomic and transcriptomic data to decipher the tissue-specific gene regulatory network controlled by enhancers at two different stages of maize leaf development. Using a systems biology approach, we identify transcription factor families regulating gene tissue-specific expression in husk and seedling leaves, and characterize the enhancers likely to be involved. We show that a large part of maize enhancers is derived from transposable elements, which can provide novel transcription factor binding sites crucial to the regulation of tissue-specific biological functions.

Published
2020

22. Evaluation of pulse crops’ functional diversity supporting food production

Author

Hélène Marrou, Michel Edmond Ghanem, Denis Vile, Jacques Wery, Julie Guiguitant, Fonctionnement et conduite des systèmes de culture tropicaux et méditerranéens (UMR SYSTEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), International Center for Agricultural Research in the Dry Areas [Syrie] (ICARDA), Mohammed VI Polytechnic University [Marocco] (UM6P), International Center for Agricultural Research in the Dry Areas [Egypte] (ICARDA), International Center for Agricultural Research in the Dry Areas (ICARDA), Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), French National Research Agency (ANR), Arimnet international program, Occitanie Region, European Project: 219262,EC:FP7:KBBE,FP7-ERANET-2007-RTD,ARIMNET(2008), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, and Université Mohammed VI Polytechnique [Ben Guerir] (UM6P)

Subjects
Crops, Agricultural, 0106 biological sciences, Agroecosystem, Adaptive strategies, Plant physiology, lcsh:Medicine, Biology, Models, Biological, 010603 evolutionary biology, 01 natural sciences, Article, Plant breeding, Ecosystem services, lcsh:Science, Plant ecology, Ecosystem, Environmental gradient, 2. Zero hunger, Multidisciplinary, lcsh:R, food and beverages, Interspecific competition, 15. Life on land, Crop Production, [SDV.BV.AP]Life Sciences [q-bio]/Vegetal Biology/Plant breeding, Natural variation in plants, Agronomy, Trait, Food systems, lcsh:Q, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Weed, Agroecology, 010606 plant biology & botany
Abstract

Pulses, defined as legumes which produce dry seed used for human consumption, are plants of great agronomic value, at the food system level as much as the field level but their diversity has been largely underused. This study aimed at analyzing existing data on cultivated pulse species in the literature to provide a broad and structured description of pulses’ interspecific functional diversity. We used a functional trait-based approach to evaluate how pulse diversity could support food production in agroecosystems constrained by low water and nutrient availability and exposed to high weed pressure. We gathered data for 17 functional traits and six agroecosystem properties for 43 pulse species. Our analytical framework highlights the correlations and combinations of functional traits that best predict values of six agroecosystem properties defined as ecosystem services estimates. We show that pulse diversity has been structured both by breeding and by an environmental gradient. The covariance space corresponding to agroecosystem properties was structured by three properties: producers, competitors, stress-tolerant species. The distribution of crop species in this functional space reflected ecological adaptive strategies described in wild species, where the size-related axis of variation is separated from variation of leaf morpho-physiological traits. Six agroecosystem properties were predicted by different combinations of traits. However, we identified ubiquitous plant traits such as leaflet length, days to maturity, seed weight, and leaf nitrogen content, that discriminated agroecosystem properties and allowed us to gather individual species into three clusters, representative of the three strategies highlighted earlier. Implications for pulses provisioning of services in agroecosystems are discussed.

Published
2020

23. Domestication-driven changes in plant traits associated with changes in the assembly of the rhizosphere microbiota in tetraploid wheat

Author

Denis Vile, Agathe Roucou, Marie-Christine Breuil, Aymé Spor, Cyrille Violle, Pierre Roumet, Laurent Philippot, David Bru, Florian Fort, Arnaud Mounier, Agroécologie [Dijon], Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), European Research Council (ERC) Starting Grant Project 'Ecophysiological and biophysical constraints on domestication in crop plants' (Grant ERC-StG-2014-639706-CONSTRAINTS), INRAE Pari Scientifique (IDIOME-Ble)., European Project: 639706,H2020,ERC-2014-STG,CONSTRAINTS(2015), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, and Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro

Subjects
0301 basic medicine, Genotype, Science, 030106 microbiology, Introgression, Microbial communities, Triticum turgidum, [SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, Plant Roots, Article, Domestication, [SDV.GEN.GPL]Life Sciences [q-bio]/Genetics/Plants genetics, 03 medical and health sciences, Ophiostomataceae, Abundance (ecology), Mycorrhizae, Botany, Relative species abundance, Soil Microbiology, Triticum, 2. Zero hunger, Rhizosphere, Multidisciplinary, Bacteria, Ecology, biology, Obligate, Microbiota, Domestication des plantes, fungi, food and beverages, 15. Life on land, biology.organism_classification, Rhizobiales, Tetraploidy, Phenotype, 030104 developmental biology, Medicine, Mycobiome
Abstract

International audience; Despite the large morphological and physiological changes that plants have undergone through domestication, little is known about their impact on their microbiome. Here we characterized rhizospheric bacterial and fungal communities as well as the abundance of N-cycling microbial guilds across thirty-nine accessions of tetraploid wheat, Triticum turgidum, from four domestication groups ranging from the wild subspecies to the semi dwarf elite cultivars. We identified several microbial phylotypes displaying significant variation in their relative abundance depending on the wheat domestication group with a stronger impact of domestication on fungi. The relative abundance of potential fungal plant pathogens belonging to the Sordariomycetes class decreased in domesticated compared to wild emmer while the opposite was found for members of the Glomeromycetes, which are obligate plant symbionts. The depletion of nitrifiers and of arbuscular mycorrhizal fungi in elite wheat cultivars compared to primitive domesticated forms suggests that the Green Revolution has decreased the coupling between plant and rhizosphere microbes that are potentially important for plant nutrient availability. Both plant diameter and fine root percentage exhibited the highest number of associations with microbial taxa, highlighting their putative role in shaping the rhizosphere microbiota during domestication. Aside from domestication, significant variation of bacterial and fungal community composition was found among accessions within each domestication group. In particular, the relative abundances of Ophiostomataceae and of Rhizobiales were strongly dependent on the host accession, with heritability estimates of ~ 27% and ~ 25%, indicating that there might be room for genetic improvement via introgression of ancestral plant rhizosphere-beneficial microbe associations. Crop domestication events led to spectacular modifications of plant traits increasing their suitability to human requirements. Cereals and especially wheat have been domesticated in the Middle East 1. Domestication process led to dramatic phenotypic changes in cultivated species in relation to cultivation conditions and human needs. The Domestication syndrome 2 refers to the whole set of phenotypic changes occurred during this process, including: loss of dormancy, increasing seed size, modifying seed dispersal mode and apical dominance as well photoperiod sensitivity. open

Published
2020
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24. Understanding effects of genotype × environment × sowing window interactions for durum wheat in the Mediterranean basin

Author

Alberto Masoni, G. Padovan, Roberto Ferrise, Domenico Ventrella, Mikhail A. Semenov, Camilla Dibari, Marco Bindi, Ignacio J. Lorite, Pierre Martre, Simone Bregaglio, C. Santos, Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Rothamsted Research, Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria (CREA), IFAPA Centro Alameda del Obispo, Instituto Andaluz de Investigación y Formación Agraria y Pesquera (IFAPA), FACCE JPI MACSUR2 through the Italian Ministry for Agricultural, Food and Forestry Policies (D.M. n. 24064/7303/15), Biotechnology and Biological Sciences Research Council, through the Designing Future Wheat (DFW) program (BB/P016855/1), AgriDigit-Agromodelli project (DM n. 36502 of 20/12/2018), funded by the Italian Ministry of Agricultural, Food and Forestry Policies and Tourism, project PR.AVA2018.051 (Innova-Clima) funded by the European Regional Development Fund (FEDER), European Project: 727247,H2020,H2020-SFS-2016-2,SolACE(2017), Università degli Studi di Firenze = University of Florence (UniFI), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Biotechnology and Biological Sciences Research Council (BBSRC), and Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria = Council for Agricultural Research and Economics (CREA)

Subjects
0106 biological sciences, Mediterranean climate, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Sowing window, Soil Science, Growing season, Biology, 01 natural sciences, Mediterranean Basin, SiriusQuality, Anthesis, Mediterranean environments, Cultivar, SolACEWP1, Durum wheat, 2. Zero hunger, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Biomass (ecology), Sowing, 04 agricultural and veterinary sciences, 15. Life on land, Agronomy, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Crop simulation model, Agronomy and Crop Science, 010606 plant biology & botany
Abstract

Durum wheat is one of the most important crops in the Mediterranean basin. The choice of the cultivar and the sowing time are key management practices that ensure high yield. Crop simulation models could be used to investigate the genotype × environment × sowing window (G × E×SW) interactions in order to optimize farmers’ actions. The aim of this study was to evaluate the performance of the wheat model SiriusQuality in simulating durum wheat yields in Mediterranean environments and its potential to explore the G × E×SW interactions. SiriusQuality was assessed in multiple growing seasons at seven sites located in Italy, Spain and Morocco, where locally adapted cultivars were grown. The model showed good ability in predicting anthesis and maturity date (Pearson r >0.8), as well as above ground biomass and grain yield (6 % < nRMSE < 18 %). The model was then used to find the optimal 30-day sowing window to maximize grain yields at four sites, two were located in Italy (Florence, Foggia), and the other two were in Spain (Santaella) and Morocco (Sidi El Aydi) respectively. Among the cultivars, on the average between all sowing window, Amilcar had the best performance in Foggia (+33 % compared to the traditional cultivar Simeto) and in Sidi El Aydi (+22 % compared to Karim), Karim in Florence (+19 % compared to Creso) and in Santaella (+6 % compared to Amilcar). Instead Creso and Simeto showed the lowest production at all locations. The results showed that an earlier sowing window compared to the traditional one would have a positive effect on wheat yields in all environments tested, because of increased maximum leaf area index, grain number and size, and grain filling duration. Moreover, with earlier sowing, grain filling coincides with higher soil water availability, reducing the water stress and increasing the accumulation of dry mass in grains. In cooler and wetter locations, cultivars characterized by higher leaf area index and radiation use efficiency had the higher number of grains, while in the hottest and driest locations, short-cycle cultivars with high grain dry matter potential (e.g. through enhanced “stay green” capacity) should be preferred.

Published
2020

25. Parameterising wheat leaf and tiller dynamics for faithful reconstruction of wheat plants by structural plant models

Author

Tino Dornbusch, Bruno Andrieu, Camille Chambon, Christian Fournier, David Gouache, Benoit de Solan, Mariem Abichou, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Modeling plant morphogenesis at different scales, from genes to phenotype (VIRTUAL PLANTS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA)-Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), ARVALIS - Institut du végétal [Paris], National Research Agency (Wheatamix project ANR-13-AGRO-0008), ANR-13-AGRO-0008,WHEATAMIX,Augmenter la diversité génétique au sein des parcelles de blé pour renforcer la multifonctionnalité et la durabilité de la production dans le Bassin Parisien(2013), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)

Subjects
0106 biological sciences, plant architecture, Population, croissance foliaire, Soil Science, Growing season, Structural plant model, Tiller (botany), Biology, three dimensional model, 01 natural sciences, modèle structure fonction, Crop, blé, wheat, Architecture, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Phyllochron, triticum aestivum, Cultivar, education, 2. Zero hunger, education.field_of_study, modèle 3d, Sowing, 04 agricultural and veterinary sciences, 15. Life on land, Phenotype, Agronomy, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Agronomy and Crop Science, architecture de la plante, 010606 plant biology & botany, Main stem
Abstract

International audience; Structural 3D plant models aim at mimicking the dynamics of plant and crop structure based on experimental data. Such models can be interfaced with physical models to investigate plant-environment interactions. This work aimed at defining functions that represent the leaf and tiller development of individual wheat plants, and that could be fitted to the specific traits produced in a broad range of situations.A dataset of the dynamics of wheat plant (Triticum aestivum) architecture was collected for 55 experimental situations, including 11 growing seasons, three sowing densities, three sowing dates, and 13 commercial cultivars. Data were analysed to identify conserved patterns in the dynamics of leaf emergence and of tiller emergence and senescence.The broad range of conditions tested allowed us to evaluate the robustness of relationships proposed in previous studies and to identify novel patterns. Amongst them, we observed: (i) that leaf emergence dynamics may follow either a linear or a bilinear pattern for the same genotype. When a change in phyllochron occurred, it coincided with the initiation of the flag leaf; (ii) the delay between leaf and tiller emergence was not constant, but increased very regularly for successive phytomers; (iii) the number of leaves emerged at tillering cessation decreased with plant density but depended also on the final number of leaves on the main stem (MS) and marked differences existed between cultivars. Finally, we defined functions representing leaf and tiller dynamics with parameters that have a simple botanical interpretation and are easy to derive from field measurements. Assessing plant density, crop leaf stage at 5–6 dates and tiller population at 2 dates during the cycle provide the required data.This study defines a rationale to analyse and represent the dynamics of the architecture of individual wheat plants. The method can be used to determine the dynamics of architecture in 3D models and should be transposable to a wide range of cereal species.

Published
2018

26. Stomatal Response to Humidity: Blurring the Boundary between Active and Passive Movement

Author

Florent Pantin, Michael R. Blatt, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Laboratory of Plant Physiology and Biophysics, University of Glasgow, Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
0106 biological sciences, 0301 basic medicine, Stomatal conductance, Vapor Pressure, Physiology, Movement, Plant Science, Atmospheric sciences, Models, Biological, 01 natural sciences, 03 medical and health sciences, chemistry.chemical_compound, Commentaries, Genetics, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Abscisic acid, Transpiration, Abscisic acid metabolism, Humidity, Plant Transpiration, 030104 developmental biology, chemistry, Mutation, Plant Stomata, Environmental science, Abscisic Acid, 010606 plant biology & botany
Abstract

Two recent publications suggest that VPD drives stomatal conductance independent of ABA and that hydropassive and active stomatal movements are interlocked within a single, mechanistic framework.

Published
2018

27. Estimating wheat green area index from ground-based LiDAR measurement using a 3D canopy structure model

Author

Mariem Abichou, Frédéric Boudon, Matthieu Hemmerlé, Kamran Irfan, Christian Fournier, Frédéric Baret, Kaiguang Zhao, Scott Thomas, Bruno Andrieu, Shouyang Liu, Benoit de Solan, Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Modeling plant morphogenesis at different scales, from genes to phenotype (VIRTUAL PLANTS), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), ARVALIS - Institut du Végétal [Boigneville], ARVALIS - Institut du végétal [Paris], Ohio Agricultural Research and Development Ohio Agricultural Research and Development Center, The Ohio State University, Ohio State University [Columbus] (OSU), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Hiphen Integrated Plant Phenotyping Systems, AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Simulation et Analyse de la morphogenèse in siliCo (MOSAIC), Inria Grenoble - Rhône-Alpes, Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA)-Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut National de la Recherche Agronomique (INRA)-Avignon Université (AU), 'Programme d’investissement d’Avenir' PHENOME (ANR-11-INBS-012) and Breedwheat (ANR-10-BTR-03), France Agrimer, 'Fonds de Soutien à l’Obtention Végétale', Chinese Scholarship Council (CSC)., ANR-11-INBS-0012,PHENOME,Centre français de phénomique végétale(2011), ANR-10-BTBR-0003,BREEDWHEAT,Développer de nouvelles variétés de blé pour une agriculture durable(2010), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)

Subjects
0106 biological sciences, Canopy, Atmospheric Science, LiDAR, 010504 meteorology & atmospheric sciences, Point cloud, F62 - Physiologie végétale - Croissance et développement, 01 natural sciences, ADEL-Wheat, Poisson model, 3D canopy structure model, Structured model, 0105 earth and related environmental sciences, Remote sensing, 2. Zero hunger, Global and Planetary Change, GAI, Artificial neural network, Forestry, Ranging, Green area index, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Lidar, Phenotyping, Wheat, Environmental science, U30 - Méthodes de recherche, Interception, Agronomy and Crop Science, Neural networks, 010606 plant biology & botany
Abstract

International audience; The use of active remote sensing techniques based on light detection and ranging (LiDAR) was investigated here to estimate the green area index (GAI) of wheat crops. Emphasis was put on the maximum GAI development stage when saturation effects are known to limit the performances of standard indirect methods based either on the gap fraction or reflectance measurements. The LiDAR provides both the three dimensional (3D) point cloud from which the vertical distribution (Z profile) of the interception points is computed, as well as the intensity of the returned signal from which the green fraction (GF) is derived. The data were interpreted by exploiting the 3D ADEL-Wheat model that synthesizes the knowledge accumulated on wheat canopy structure. A LiDAR simulator that accounts for the specific observation configuration used was developed to mimic the actual LiDAR measurements. The in-silico experiments were conducted to generate training and validation dataset. Neural network were then used to estimate GAI from the Z profile and GF derived from the LiDAR measurements. Performances of GAI estimates by the several methods investigated were evaluated using either experimental data with 3 < GAI < 6 and data simulated with the 3D structure model with 1 < GAI < 7. Results confirm that using only the GF provides poor estimates of GAI (0.89 < RMSE < 1.28; 0.22 < rRMSE < 0.31), regardless of turbid medium or realistic assumptions on canopy 3D structure. The introduction of the Z profile information improved significantly the GAI estimation accuracy (0.48 < RMSE < 0.55; 0.12 < rRMSE < 0.13). This study demonstrates the interest of using the third dimension provided by LiDAR to better estimate GAI in crops under high GAI values. However, this requires the use of a realistic 3D structure crop model over which the LiDAR data could be simulated under the observational configuration used.

Published
2017

28. Bridging the gap between data and decisions: A review of process-based models for viticulture

Author

Cassandra Collins, Seth Westra, Bree Bennett, Bertram Ostendorf, Anne Pellegrino, Matthew J. Knowling, Everard J. Edwards, Rob R. Walker, Vinay Pagay, Dylan Grigg, University of Adelaide, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Wine Australia, with co-funding from Riverland Wine

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, 0106 biological sciences, Bridging (networking), 010504 meteorology & atmospheric sciences, Computer science, Process (engineering), Control (management), Context (language use), 15. Life on land, 01 natural sciences, Vineyard, Bridge (nautical), Decision support, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Vineyard management, Risk analysis (engineering), Process-based model, Yield (wine), Digital agriculture, Animal Science and Zoology, Viticulture, Agronomy and Crop Science, 010606 plant biology & botany, 0105 earth and related environmental sciences
Abstract

International audience; Context: Effective vineyard decision making at strategic and operational timescales requires consideration of many factors, including vineyard design and management options, exogenous factors that are outside of the decision maker's control such as climate/weather, and desired outcomes such as yield and grape composition attributes. Process-based models enable prediction of vineyard outcomes in response to different decisions and with respect to exogenous factors.Objective: We present a review of process-based models that can simulate both key vineyard outcomes and their sensitivity to decisions and exogenous factors, and highlight how these models can ‘bridge the gap’ between data and decisions.Methods: We assess the suitability of process-based models to water, canopy and nutrient management contexts using a conceptual systems framework.Results and Conclusions:Currently available process-based models are most advanced in terms of supporting decisions regarding water management, and least advanced regarding nutrient management. They are also better suited to support decisions with respect to yield, compared to grape composition attributes.Significance: This paper provides guidance to modelling practitioners regarding appropriate process-based models for a range of vineyard decision contexts and assists viticulturists and decision makers in understanding how these models can support decisions for improved outcomes.

Published
2021

29. Increasing the total productivity of a land by combining mobile photovoltaic panels and food crops

Author

Angélique Christophe, P. Hamard, Francis Sourd, P. Pechier, B. Valle, T. Frisson, M. Ryckewaert, Thierry Simonneau, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), SAS, Slovak Academy of Sciences (SAS), Smart Energy, SunR, ANRT (Association Nationale Recherche Technologie, France), Sun’R (contract 2013/1353), Région PACA, CAPI, BPI FRANCE, Communauté du pays d’Aix, Région Rhônes-Alpes, Grand Lyon, and SunAgri2B FUI project.

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Solar trackers, 020209 energy, Microclimate, 02 engineering and technology, Agricultural engineering, 010501 environmental sciences, Management, Monitoring, Policy and Law, 7. Clean energy, 01 natural sciences, Agrivoltaic, Solar tracker, Photovoltaic panels, 0202 electrical engineering, electronic engineering, information engineering, Land use conflict, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, 0105 earth and related environmental sciences, 2. Zero hunger, Biomass (ecology), Land use, Ecology, Mechanical Engineering, Photovoltaic system, Energy conversion efficiency, Building and Construction, Lettuce, 15. Life on land, General Energy, Productivity (ecology), Environmental science, Shading
Abstract

Agrivoltaic systems, consisting of the combination of photovoltaic panels (PVPs) with crops on the same land, recently emerged as an opportunity to resolve the competition for land use between food and energy production. Such systems have proved efficient when using stationary PVPs at half their usual density. Dynamic agrivoltaic systems improved the concept by using orientable PVPs derived from solar trackers. They offer the possibility to intercept the variable part of solar radiation, as well as new means to increase land productivity. The matter was analysed in this work by comparing fixed and dynamic systems with two different orientation policies. Performances of the resulting agrivoltaic systems were studied for two varieties of lettuce over three different seasons. Solar tracking systems placed all plants in a new microclimate where light and shade bands alternated several times a day at any plant position, while stationary systems split the land surface into more stable shaded and sunlit areas. In spite of these differences, transient shading conditions increased plant leaf area in all agrivoltaic systems compared to full-sun conditions, resulting in a higher conversion of the transmitted radiation by the crop. This benefit was lower during seasons with high radiation and under controlled tracking with more light transmitted to the crop. As expected, regular tracking largely increased electric production compared to stationary PVPs but also slightly increased the transmitted radiation, hence crop biomass. A large increase in transmitted radiation was achieved by restricting solar tracking around midday, which resulted in higher biomass in the spring but was counterbalanced by a lower conversion efficiency of transmitted radiation in summer. As a result, high productivity per land area unit was reached using trackers instead of stationary photovoltaic panels in agrivoltaic systems, while maintaining biomass production of lettuce close or even similar to that obtained under full-sun conditions.

Published
2017

30. Are subsidies to weather-index insurance the best use of public funds? A bio-economic farm model applied to the Senegalese groundnut basin

Author

Charlotte Poeydebat, Bertrand Muller, Françoise Gérard, Moussa Sall, Aymeric Ricome, Philippe Quirion, François Affholder, European Commission - Joint Research Centre [Ispra] (JRC), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Gestion des ressources renouvelables et environnement (UPR GREEN), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), centre international de recherche sur l'environnement et le développement (CIRED), Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École des hautes études en sciences sociales (EHESS)-AgroParisTech-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Institut Sénégalais de Recherches Agricoles (ISRA), ISRA, Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Gestion des ressources renouvelables et environnement (Cirad-Es-UPR 47 GREEN), Département Environnements et Sociétés (Cirad-ES), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Centre International de Recherche sur l'Environnement et le Développement (CIRED), and Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École des hautes études en sciences sociales (EHESS)-AgroParisTech

Subjects
Index (economics), 010504 meteorology & atmospheric sciences, 01 natural sciences, Agricultural economics, F01 - Culture des plantes, Economics, media_common, 2. Zero hunger, U10 - Informatique, mathématiques et statistiques, Assurance, 1. No poverty, Subsidy, 04 agricultural and veterinary sciences, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Rendement des cultures, Cash, Economic model, système d'aide à la décision, Modèle mathématique, Agriculteur, P40 - Météorologie et climatologie, Ferme pilote, media_common.quotation_subject, Developing country, Conditions météorologiques, Scarcity, Sécheresse, Arachis hypogaea, Production (economics), 0105 earth and related environmental sciences, Intensification, Modélisation des cultures, Modèle de simulation, Analyse économique, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, H50 - Troubles divers des plantes, Animal Science and Zoology, Agronomy and Crop Science, Welfare
Abstract

International audience; While crop yields in Sub-Saharan Africa are low compared to most other parts of the world, weather-index insurance is often presented as a promising tool, which could help resource-poor farmers in developing countries to invest and adopt yield-enhancing technologies. Here, we test this hypothesis on two contrasting areas (in terms of rainfall scarcity) of the Senegalese groundnut basin through the use of a bio-economic farm model, coupling the crop growth model CELSIUS with the economic model ANDERS, both specifically designed for this purpose. We introduce a weather-index insurance whose index is currently being used for pilot projects in Senegal and West Africa. Results show that insurance leads to a welfare gain only for those farmers located in the driest area. These farmers respond to insurance mostly by increasing the amount of cow fattening, which leads to higher crop yields thanks to the larger production of manure. We also find that subsidizing insurance is not the best possible use of public funds: for a given level of public funding, reducing credit rates, subsidizing fertilizers, or just transferring cash as a lump-sum generally brings a higher expected utility to farmers and leads to a higher increase in grain production levels.

Published
2017

31. Relevance of limited-transpiration trait for lentil ( Lens culinaris Medik.) in South Asia

Author

Julie Guiguitant, Michel Edmond Ghanem, Thomas R. Sinclair, Shiv Kumar, Priyanka Gupta, Hélène Marrou, Afshin Soltani, Vincent Vadez, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Crop Physiology Laboratory, North-Africa Platform, International Center for Agricultural Research in the Dry Areas (ICARDA), Fonctionnement et conduite des systèmes de culture tropicaux et méditerranéens (UMR SYSTEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), System Analysis for Climate Smart Agriculture, Patancheru, Greater Hyderabad, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Agronomy Group, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan University of Agricultural Sciences and Natural Resources, Department of Crop Science, North Carolina State University [Raleigh] (NC State), University of North Carolina System (UNC)-University of North Carolina System (UNC), CGIAR Research Program on Grain Legumes, USAID/CGIAR-US Universities Linkage Program, International Center for Agricultural Research in the Dry Areas [Syrie] (ICARDA), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), International Crops Research Institute for the Semi-Arid Tropics [Inde] (ICRISAT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), European Project: 609398,EC:FP7:PEOPLE,FP7-PEOPLE-2013-COFUND,AGREENSKILLSPLUS(2014), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, 0106 biological sciences, Germplasm, South asia, Vapour Pressure Deficit, Soil Science, Environment controlled, South Asia, 01 natural sciences, lentil, Crop production, lens culinaris, Transpiration, SSM, 2. Zero hunger, crop model, vapor pressure deficit, fungi, food and beverages, 04 agricultural and veterinary sciences, asie du sud, limited transpiration trait, southern asia, Agronomy, 13. Climate action, 040103 agronomy & agriculture, Trait, 0401 agriculture, forestry, and fisheries, Legume crops, Agronomy and Crop Science, 010606 plant biology & botany
Abstract

Drought is one of the most important environmental factors that limit crop production. It has been hypothesized that a limited-transpiration trait under high vapor pressure deficit (VPD) is a mechanism for water conservation leading to yield increase under water-deficit conditions, The first research objective was to compare expression of limited-transpiration (TRlim) in lentil (Lens culinaris Medik.) observed by whole-plant measurements in controlled environments and under natural conditions outdoors during a high VPD period. Seventeen lentil genotypes were studied. All genotypes showed a linear increase with increasing VPD under natural conditions. Differences were observed among genotypes in their expression of TRE, with increasing VPD in the controlled environment. Almost all genotypes showed a VPD breakpoint at approximately 3.4 kPa. A simulation analysis was conducted across South Asia to identify where, how often, and how much this trait in lentil would benefit farmers with four different VPD breakpoint scenarios (VPD breakpoint at 3.4, 2.2, 1.1 kPa, and VPD-insensitive). Results showed that the limited-transpiration trait at a low simulated threshold (1.1 kPa) can result in improved lentil performance in drought-prone environments and that the impact of the trait on lentil productivity varies with geography and environment. The largest average yield increase was simulated for drought-prone environments (250 g m(-2)). Outcomes from this simulation study provide insights into the plausible role of the limited-transpiration trait under high VPD in future lentil genetic improvement and implies that a search for germplasm with a breakpoint as low as 1.1 kPa needs to be made.

Published
2017

32. InfraPhenoGrid: A scientific workflow infrastructure for plant phenomics on the Grid

Author

Simon Artzet, Christian Fournier, Vincent Negre, Michael Mielewczik, Christophe Pradal, Patrick Valduriez, Jérôme Chopard, Sarah Cohen-Boulakia, Pascal Neveu, Dimitri Dupuis, Didier Parigot, Modeling plant morphogenesis at different scales, from genes to phenotype (VIRTUAL PLANTS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA)-Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut de Biologie Computationnelle (IBC), Institut National de la Recherche Agronomique (INRA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Scientific Data Management (ZENITH), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), École nationale supérieure d'architecture de Paris-La Villette (ENSAPLV), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Laboratoire de Recherche en Informatique (LRI), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), The authors acknowledge the support of France Grilles for providing computing resources on the French National Grid Infrastructure, ANR-11-INBS-0012,PHENOME,Centre français de phénomique végétale(2011), European Project: 267196,EC:FP7:PEOPLE,FP7-PEOPLE-2010-COFUND,AGREENSKILLS(2012), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Université de Montpellier (UM)-Institut National de la Recherche Agronomique (INRA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), ANR-11-INBS-0012/11-INBS-0012,PHENOME,Centre français de phénomique végétale(2011), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)

Subjects
0106 biological sciences, 0301 basic medicine, Computer Networks and Communications, Computer science, F60 - Physiologie et biochimie végétale, Distributed computing, acquisition de données, Context (language use), Phenome, 01 natural sciences, F30 - Génétique et amélioration des plantes, 03 medical and health sciences, Phenomics, phénotypage, caractère physiologique, condition environnementale, base de données, 2. Zero hunger, Vegetal Biology, Food security, SIMPLE (military communications protocol), Point (typography), U10 - Informatique, mathématiques et statistiques, Scientic Work ows, Grid, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Data science, plateforme de phénotypage, Scientific workflows, Provenance, Grid computing, 030104 developmental biology, Workflow, C30 - Documentation et information, OpenAlea, 13. Climate action, Hardware and Architecture, dispositif de recherche, Biologie végétale, Software, 010606 plant biology & botany
Abstract

International audience; Plant phenotyping consists in the observation of physical and biochemical traits of plant genotypes in response to environmental conditions. Challenges , in particular in context of climate change and food security, are numerous. High-throughput platforms have been introduced to observe the dynamic growth of a large number of plants in different environmental conditions. Instead of considering a few genotypes at a time (as it is the case when phenomic traits are measured manually), such platforms make it possible to use completely new kinds of approaches. However, the data sets produced by such widely instrumented platforms are huge, constantly augmenting and produced by increasingly complex experiments, reaching a point where distributed computation is mandatory to extract knowledge from data. In this paper, we introduce InfraPhenoGrid, the infrastructure we designed and deploy to efficiently manage data sets produced by the PhenoArch plant phenomics platform in the context of the French Phenome Project. Our solution consists in deploying scientific workflows on a Grid using a middle-ware to pilot workflow executions. Our approach is user-friendly in the sense that despite the intrinsic complexity of the infrastructure, running scientific workflows and understanding results obtained (using provenance information) is kept as simple as possible for end-users.

Published
2017

33. Phenotypic and genetic analysis to identify secondary physiological traits for improving grain yield in wheat considering anthesis time variability

Author

Santiago Alvarez Prado, Jose M. Costa, L. Gabriela Abeledo, Laura Elena Puhl, Yaopeng Zhou, Daniel J. Miralles, Departamento de Producción Vegetal, Facultad de Agronomía, University of Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Universidad de Buenos Aires (UBA), University of Maryland [College Park], University of Maryland System, USDA-ARS : Agricultural Research Service, and University of Buenos Aires (UBACYT 20020160100112)

Subjects
0106 biological sciences, 0301 basic medicine, Extreme phenotypes, Quantitative trait loci, Grain number, Population, Plant Science, Horticulture, Biology, Quantitative trait locus, 01 natural sciences, Genetic analysis, 03 medical and health sciences, Dry weight, Anthesis, Genetic variation, Genetics, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, education, 2. Zero hunger, education.field_of_study, Phenology, Spike dry weight, food and beverages, 030104 developmental biology, Agronomy, Doubled haploidy, Agronomy and Crop Science, 010606 plant biology & botany
Abstract

Identification of secondary traits in mapping populations is usually hindered by the strong effect of anthesis time. Thus, considering the variability in time to anthesis in combination with an accurate phenotyping of mapping populations and available molecular tools is a possible way for recognising secondary traits to improve yield potential. The aim of this work was to identify secondary traits to perform indirect selection for grain yield (GY) in a bread wheat mapping population consisting of 124 doubled haploid lines, derived from the cross between two soft red winter wheat genotypes with contrasting photoperiod response. Genomic regions linked to different traits were analysed under two environments. The population showed a strong effect of time to anthesis over GY, as expected. A large variability in GY was observed but only two QTLs were detected on chromosome 5A for this trait, which co-localized with QTLs of time to anthesis. GY variation was partially associated with above-ground dry matter at maturity (AGDM) and to a lesser extent with harvest index (HI). Detected QTLs for grains per m2 (GN), grain weight, AGDM and HI explained between 25 and 61% of the GY additive genetic variance. GN, defined as the product between spike dry weight at anthesis (SDW) and fruiting efficiency (FE), was the main numerical component that explained most of the variation in GY. Five QTLs were detected for SDW, which did not co-localize with QTLs of time to anthesis and captured ca. 50% of the additive genetic variance, while there was a weak relationship between NG and FE. When genotypes were filtered by similar anthesis time and plant height, SDW was identified as a promising secondary trait to be targeted for indirect selection of GY.

Published
2019

34. Gradual responses of grapevine yield components and carbon status to nitrogen supply

Author

Pellegrino Anne, Leporatti Romain, Gharibi Shiva, Fraga Alana, Roland Gaëlle, Sylvain Vrignon-Brenas, Metay Aurélie, Dauzat Myriam, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Fonctionnement et conduite des systèmes de culture tropicaux et méditerranéens (UMR SYSTEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, 0106 biological sciences, Perennial plant, Nitrogen, growth, Yield components, SPAD, Grapevine, Quantitative responses, N supply, Horticulture, Biology, Photosynthesis, 01 natural sciences, Petiole (botany), Veraison, storage, lcsh:Agriculture, lcsh:Botany, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Dry matter, carbon balance, 2. Zero hunger, Vegetal Biology, Crop yield, lcsh:S, food and beverages, 04 agricultural and veterinary sciences, 15. Life on land, nutrition azotée, lcsh:QK1-989, Agricultural sciences, sauvignon blanc, fertilisation azotée, Inflorescence, Shoot, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, écophysiologie végétale, vigne, Biologie végétale, Sciences agricoles, 010606 plant biology & botany, Food Science
Abstract

International audience; Aim: Nitrogen is a major element conditioning grapevine growth, yield and aromatic profiles of berries and wines. Different tools can be used in order to detect differences in N status of the plant, including direct measurements of soil, plant nitrogen status (eg. petiole; must), or indirect observations of plant nutritional status such as leaf transmittance or reflectance (eg. SPAD; NDVI). However, the relationships between these indicators of nitrogen status and the overall plant functioning over vintages remain poorly known. The present study aimed at quantifying key vegetative and reproductive responses to plant nitrogen status over two successive seasons under different nitrogen supply levels. Methods and results: Potted plants of Sauvignon Blanc grafted onto SO4 were grown outdoors in 2017 and 2018 with no water limitation. Four mineral nitrogen fertilization levels (equivalent to 0 kg of N ha-1 or 0U, 20U, 40U, 80U) and one organic nitrogen fertilization level (40U) were imposed in 2017. These treatments were doubled in 2018 to increase the degree of nitrogen supply and consequently, the range of observed effects on plant growth and yield. Plant nitrogen status (SPAD) was monitored weekly during both growing cycles. Yield components were determined over the two seasons. Lastly, plant carbon status was addressed through dynamic measurement of plant development and photosynthesis, and destructive measurement of dry matter accumulation and carbon storage in annual and perennial organs at flowering, veraison and harvest. The SPAD values progressively decreased under lower N supply (0N) during the first year (from 31 to 16) and they were more than halved between the maximum and the minimum N treatments straight after budburst in year two (40 for 160N and 19 for 0N). Then, the differences in SPAD values among treatments were maintained up to harvest (2018). The gradient of N status resulted in a gradient of berry numbers per inflorescence (from 180 to 34 berries/inflorescence for 80N and 0N, respectively in 2018) and of individual berry dry matter at harvest (from 0.13 to 0.41 g for 160N and 0N, respectively in 2018). Quantitative relationships between N status and the relative reductions (% of reduction per %SPAD decrease) in terms of C gain (leaf area, photosynthesis), C growth (shoot, berry, trunk and root dry matter) and C storage (trunk and root) were fitted at flowering, veraison and harvest. The reduction in C gain under lower N supply was mainly related to the decrease in total leaf area before flowering (-1.64%). Although the photosynthesis rate tended to decrease under N deficiency over the season, it only poorly contributed to the reduction in C gain. The whole plant C growth was inhibited when N status decreased (-1.13% at harvest), due to the inhibition of shoot dry matter before veraison (-1.81%) and to a lower extent, to the lower dry matter in berries (-0.80%), trunks (-0.42%) and roots (-0.84%) at harvest. Part of the reduction in root dry matter was related to the lower starch reserves (-0.31%) at harvest. Interestingly, starch reserves tended to be higher under organic N supply than mineral N supply. Conclusion: The present results provided a general framework of carbon gain and use over time (within and between seasons) as impacted by N supply levels and form. Such a framework will be useful when building a model of the pluri-annual dynamics of carbon balance related to yield elaboration in grapevines.

Published
2019

35. Using crop growth model stress covariates and AMMI decomposition to better predict genotype-by-environment interactions

Author

Pierre Martre, F.A. van Eeuwijk, Gaëtan Touzy, Agathe Mini, Renaud Rincent, J. Le Gouis, Matthieu Bogard, Behnam Ababaei, Marcos Malosetti, Génétique Diversité et Ecophysiologie des Céréales (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Biometris, Wageningen University and Research [Wageningen] (WUR), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Groupe Limagrain, ARVALIS - Institut du végétal [Paris], Genetics and Genomics in Cereals, BIOGEMMA, French National Research National Agency under Investment for the Future (BreedWheat Project ANR-10-BTBR-03), FranceAgriMer., French National Research National Agency under the Investment for the Future Phenome project (ANR-11-INBS-12), European Regional Development Fund (AV0011535), AgreenSkills + fellowship Grant Agreement No. FP7- 609398, ANR-10-BTBR-0003,BREEDWHEAT,Développer de nouvelles variétés de blé pour une agriculture durable(2010), ANR-11-INBS-0012,PHENOME,Centre français de phénomique végétale(2011), European Project: 609398,EC:FP7:PEOPLE,FP7-PEOPLE-2013-COFUND,AGREENSKILLSPLUS(2014), and Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)

Subjects
Crops, Agricultural, 0106 biological sciences, Mixed model, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Genotype, Context (language use), 01 natural sciences, Wiskundige en Statistische Methoden - Biometris, Similarity (network science), Covariate, Statistics, Genetics, Decomposition (computer science), Life Science, SolACEWP4, Mathematical and Statistical Methods - Biometris, Triticum, 2. Zero hunger, Models, Statistical, Models, Genetic, biology, food and beverages, Regression analysis, Ammi, General Medicine, 15. Life on land, Covariance, biology.organism_classification, PE&RC, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Phenotype, 13. Climate action, Gene-Environment Interaction, Agronomy and Crop Science, 010606 plant biology & botany, Biotechnology
Abstract

Key message: We propose new methods to predict genotype × environment interaction by selecting relevant environmental covariates and using an AMMI decomposition of the interaction. Abstract: Farmers are asked to produce more efficiently and to reduce their inputs in the context of climate change. They have to face more and more limiting factors that can combine in numerous stress scenarios. One solution to this challenge is to develop varieties adapted to specific environmental stress scenarios. For this, plant breeders can use genomic predictions coupled with environmental characterization to identify promising combinations of genes in relation to stress covariates. One way to do it is to take into account the genetic similarity between varieties and the similarity between environments within a mixed model framework. Molecular markers and environmental covariates (EC) can be used to estimate relevant covariance matrices. In the present study, based on a multi-environment trial of 220 European elite winter bread wheat (Triticum aestivum L.) varieties phenotyped in 42 environments, we compared reference regression models potentially including ECs, and proposed alternative models to increase prediction accuracy. We showed that selecting a subset of ECs, and estimating covariance matrices using an AMMI decomposition to benefit from the information brought by the phenotypic records of the training set are promising approaches to better predict genotype-by-environment interactions (G × E). We found that using a different kinship for the main genetic effect and the G × E effect increased prediction accuracy. Our study also demonstrates that integrative stress indexes simulated by crop growth models are more efficient to capture G × E than climatic covariates.

Published
2019
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36. Identifying developmental phases in theArabidopsis thalianarosette using integrative segmentation models

Author

Maryline Lièvre, Christine Granier, Yann Guédon, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Modeling plant morphogenesis at different scales, from genes to phenotype (VIRTUAL PLANTS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA)-Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
0106 biological sciences, 0301 basic medicine, Genotype, Arabidopsis thaliana, Physiology, Ontogeny, heteroblasty, Arabidopsis, F62 - Physiologie végétale - Croissance et développement, Plant Science, 01 natural sciences, Rosette (botany), 03 medical and health sciences, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Botany, Image Processing, Computer-Assisted, Leaf size, Segmentation, [SDV.BDD]Life Sciences [q-bio]/Development Biology, Models, Statistical, biology, U10 - Informatique, mathématiques et statistiques, semi-Markov switching model, segmentation model, multiscale analysis, shoot development, biology.organism_classification, Plant Leaves, Plant development, Phenotype, 030104 developmental biology, Seedlings, Evolutionary biology, Mutation, Trait, 010606 plant biology & botany
Abstract

International audience; The change in leaf size and shape during ontogeny associated with heteroblastic development is a composite trait for which extensive spatiotemporal data can be acquired using phe-notyping platforms. However, only part of the information contained in such data is exploited, and developmental phases are usually defined using a selected organ trait. We here introduce new methods for identifying developmental phases in the Arabidopsis rosette using various traits and minimum a priori assumptions. A pipeline of analysis was developed combining image analysis and statistical models to integrate morphological, shape, dimensional and expansion dynamics traits for the successive leaves of the Arabidopsis rosette. Dedicated segmentation models called semi-Markov switching models were built for selected genotypes in order to identify rosette developmental phases. Four successive developmental phases referred to as seedling, juvenile, transition and adult were identified for the different genotypes. We show that the degree of covering of the leaf abaxial surface with trichomes is insufficient to define these developmental phases. Using our pipeline of analysis, we were able to identify the supplementary seedling phase and to uncover the structuring role of various leaf traits. This enabled us to compare on a more objective basis the vegetative development of Arabidopsis mutants.

Published
2016

37. European infrastructures for sustainable agriculture

Author

François Tardieu, Jacques Roy, Michèle Tixier-Boichard, Ulrich Schurr, Écotron Européen de Montpellier, Centre National de la Recherche Scientifique (CNRS), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Génétique Diversité et Ecophysiologie des Céréales (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), European Commission grant 731013 (EPPN2020), European Commission grant number 312690, Écotron Européen de Montpellier - UPS 3248, Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Institut National de la Recherche Agronomique (INRA), and Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)

Subjects
0106 biological sciences, 0301 basic medicine, Conservation of Natural Resources, [SDE.MCG]Environmental Sciences/Global Changes, [SDV]Life Sciences [q-bio], Ecology (disciplines), Sustainable Agriculture Innovation Network, Plant Science, Environment, 01 natural sciences, Food Supply, 03 medical and health sciences, Phenomics, Sustainable agriculture, Humans, ComputingMilieux_MISCELLANEOUS, 2. Zero hunger, business.industry, Environmental resource management, Crop Production, Europe, 030104 developmental biology, 13. Climate action, Agriculture, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, business, 010606 plant biology & botany
Abstract

This opinion paper was drawn from an international FACCE JPI workshop in Wageningen, the Netherlands, on 27/28 October 2016; International audience; The European infrastructures EMPHASIS and AnaEE aim to collaborate in bringing innovative solutions for a sustainable intensification of agriculture. By integrating the study of plant phenomics and agricultural ecology they hope to foster the development of novel scientific concepts, sensors and integrated models.

Published
2017

38. Barley Plants Overexpressing Ferrochelatases (HvFC1 and HvFC2) Show Improved Photosynthetic Rates and Have Reduced Photo-Oxidative Damage under Drought Stress than Non-Transgenic Controls

Author

Everard J. Edwards, Ryan Whitford, Dilrukshi S. K. Nagahatenna, Boris Parent, Peter Langridge, School of Agriculture, Food and Wine, University of Adelaide, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Julius Kühn-Institut - Federal Research Centre for Cultivated Plants (JKI), Australian Research Council, the Grains Research and Development Corporation, the Government of South Australia, the University of Adelaide, and DuPont Agricultural Biotechnology, USA.

Subjects
0106 biological sciences, ferrochelatase, Transgene, Mutant, drought, Biology, medicine.disease_cause, 01 natural sciences, lcsh:Agriculture, 03 medical and health sciences, chemistry.chemical_compound, retrograde signal, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], medicine, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, heme, Heme, 030304 developmental biology, 2. Zero hunger, chemistry.chemical_classification, 0303 health sciences, Reactive oxygen species, photosynthesis, fungi, lcsh:S, barley, food and beverages, ROS, Ferrochelatase, Tetrapyrrole, Cell biology, chemistry, biology.protein, tetrapyrrole, Hordeum vulgare, Agronomy and Crop Science, Oxidative stress, 010606 plant biology & botany
Abstract

We investigated the roles of two Ferrochelatases (FCs), which encode the terminal enzyme for heme biosynthesis, in drought and oxidative stress tolerance in model cereal plant barley (Hordeum vulgare). Three independent transgenic lines ectopically overexpressing either barley FC1 or FC2 were selected and evaluated under well-watered, drought, and oxidative stress conditions. Both HvFC1 and HvFC2 overexpressing transgenics showed delayed wilting and maintained higher photosynthetic performance relative to controls, after exposure to soil dehydration. In each case, HvFC overexpression significantly upregulated the nuclear genes associated with detoxification of reactive oxygen species (ROS) upon drought stress. Overexpression of HvFCs, also suppressed photo-oxidative damage induced by the deregulated tetrapyrrole biosynthesis mutant tigrinad12. Previous studies suggest that only FC1 is implicated in stress defense responses, however, our study demonstrated that both FC1 and FC2 affect drought stress tolerance. As FC-derived free heme was proposed as a chloroplast-to-nuclear signal, heme could act as an important signal, stimulating drought responsive nuclear gene expression. This study also highlighted tetrapyrrole biosynthetic enzymes as potential targets for engineering improved crop performance, both in well-watered and water-limited environments.

Published
2020

39. Testing a crop model with extreme low yields from historical district records

Author

Senthold Asseng, Jose Rafael Guarin, Pierre Martre, Nikolay Bliznyuk, University of Florida [Gainesville] (UF), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
0106 biological sciences, Soil Science, 01 natural sciences, Crop, Wheat stress, Extreme weather, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Precipitation, Crop model, 2. Zero hunger, food and beverages, Model testing, Food security, 04 agricultural and veterinary sciences, Extreme events, 15. Life on land, Historical district yield records, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, 13. Climate action, Excess water, Climatology, Soil water, Frost, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Grain yield, Environmental science, Crop simulation model, Agronomy and Crop Science, 010606 plant biology & botany
Abstract

International audience; Extreme weather events across the world cause large variations in daily seasonal temperature and precipitation, potentially reducing grain yield and negatively affecting global food security. Thus, it is important to assess if crop growth models can simulate the yield losses caused by these extreme weather events. We tested if the DSSAT-NWheat crop simulation model, which has been successfully validated with many controlled field-experimental data across the world, can reproduce historical extreme low-yielding years at three global locations in the USA, France, and Australia. The crop model reproduced extreme low yields in some of the driest and hottest years at all three locations. However, the model failed to simulate some of the observed extreme low-yielding years. Also, the model simulated extreme low yields in some years that were not extreme low yielding in the observed records. Surprisingly, some of the driest and hottest years did not show up as observed extreme low-yielding years in the district records. This discrepancy could be explained by reporting yields, or in this case “not reporting extreme low yields” in district records, as indicated by large drops in harvested areas in extreme dry and hot seasons. Other discrepancies exist because crop models do not often consider many factors under farmer-field conditions that lead to extreme low yields in district records, including frost, hail and lodging, pests and diseases, and excess water. Historical district yield records are also limited for model testing due to unknown and changing aggregation across a district, possible omission of extreme low-yielding fields in some years, and unknown spatial and temporal varying cultivars and crop management, particularly in initial soil water conditions. In conclusion, we do not recommend using historical district yield records for model testing of extreme low yields.

Published
2020

40. The use of thermal time in plant studies has a sound theoretical basis provided that confounding effects are avoided

Author

François Tardieu, Emilie J. Millet, Boris Parent, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), ANR-10-BTBR-0001,AMAIZING,Développer de nouvelles variétés de maïs pour une agriculture durable: une approche intégrée de la génomique à la sélection(2010), ANR-11-INBS-0012,PHENOME,Centre français de phénomique végétale(2011), European Project: 618105,EC:FP7:KBBE,FP7-ERANET-2013-RTD,FACCE ERA NET PLUS(2013), and Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)

Subjects
0106 biological sciences, 0301 basic medicine, Crops, Agricultural, Ground truth, Growth cycle, Genotype, Physiology, Confounding, Temperature, Plant Development, Plant Science, Atmospheric temperature range, 01 natural sciences, Rotation formalisms in three dimensions, Plant Leaves, 03 medical and health sciences, Plant development, 030104 developmental biology, Temporal resolution, Thermal, Statistics, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, 010606 plant biology & botany, Mathematics
Abstract

International audience; The use of thermal time is essential in plant studies and crop growth modeling because correcting time for temperature allows working in fluctuating conditions as if temperature was constant. However, thermal time is often seen as a loose concept because of a multitude of thermal functions and case-specific parameter values. Our hypothesis is that these different formalisms and parameterization could emerge from common principles and a common response of plant development to temperature, but with several counfounding factors which are not taken into account. We first show that these calculations of thermal time are based on sound common principles and mathematical formalisms. We test, via a modelling exercise of nine case studies using maize plants grown in three field sites, how a given “ground truth” response of plant development rate to temperature can be affected if an experimenter either considers or ignores confounding factors. We also show that apparent differences in temperature responses between phenological stages of the growth cycle, between day and night, or between plant genotypes may be due to the confounding effects of evaporative demand, the range of temperatures, and the time interval at which measurements are taken. On the basis of our findings, we propose that the critical point in the use of a given formalism of thermal time calculation is to ensure that the chosen model is compatible with the temporal definition, temperature range, and environmental scenario in the considered dataset.

Published
2018

41. Progress in understanding drought tolerance: from alleles to cropping systems

Author

Roberto Tuberosa, François Tardieu, Rajeev K. Varshney, Varshney R.K., Tuberosa R., Tardieu F., Consultative Group on International Agricultural Research (CGIAR), Department of Agricultural and Food Sciences, University of Bologna, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)

Subjects
0106 biological sciences, 0301 basic medicine, Physiology, approche interdisciplinaire, drought tolerance, Plant Science, root architecture, 01 natural sciences, Plant Roots, Phenomics, architecture racinaire, 2. Zero hunger, Allele, education.field_of_study, Food security, Vegetal Biology, Agroforestry, Special Issue Editorial, production végétale, Crop Production, Droughts, plateforme de phénotypage, Arable land, seed development, Abortion, Crop yield, Dehydration, Osmotic adjustment, Root architecture, Seed development, Turgor management, Crops, Agricultural, Population, Drought tolerance, Plant Development, Biology, eXtra Botany, turgescence cellulaire, 03 medical and health sciences, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, ajustement osmotique, Desiccation, education, Alleles, Plant Physiological Phenomena, Drought, Abiotic stress, tolérance à la sécheresse, Plant Root, dehydration, osmotic adjustment, 15. Life on land, crop yield, 030104 developmental biology, 13. Climate action, adaptation au changement climatique, développement de la graine, Cropping, turgor management, Biologie végétale, 010606 plant biology & botany
Abstract

International audience; Improving crop yields under rainfed environments is key to meeting the food security demands of an everincreasing population, but climate change-associated expansion of drought-affected arable land means that resilient crops and agronomic practices are critical. High-throughput plant phenomics and modern genetic approaches must be directed towards precise understanding of factors controlling crop yield. This special issue covers root dynamics, turgor management under desiccation, molecular responses to dehydration, impact of drought on plant development and seed abortion, and adjustment of traits to the most frequent patterns of drought. It also addresses interdisciplinary views for enhancing genetic gains and achieving a more sustainable climate-resilient agronomy.

Published
2018

42. Co-inoculation of a Pea Core-Collection with Diverse Rhizobial Strains Shows Competitiveness for Nodulation and Efficiency of Nitrogen Fixation Are Distinct traits in the Interaction

Author

Catherine Delaitre, Marianne Chabert-Martinello, Brigitte Brunel, Marc Lepetit, Mathieu Siol, Denis Vile, Pierre Tisseyre, Gérard Duc, Véronique Aubert, Marjorie Pervent, Judith Burstin, Virginie Bourion, Karine Heulin-Gotty, Agroécologie [Dijon], Université de Bourgogne (UB)-Institut National de la Recherche Agronomique (INRA)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Laboratoire des symbioses tropicales et méditerranéennes (UMR LSTM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université Montpellier 1 (UM1)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), French ANR GENOPEA program, 'INRA-BAP projet scientifique' SYMBIOPEA program, ANR-09-GENM-0026,GENOPEA,Génomique comparative du cycle de l'azote entre M. truncatula et le pois : étude des potentialités de transfert des connaissances entre espèces modèles et cultivées(2009), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC), and Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)

Subjects
0301 basic medicine, competitiveness for nodulation, Plant Science, lcsh:Plant culture, Biology, medicine.disease_cause, Genetic diversity, Plant breeding, Rhizobium leguminosarum, Pisum, 03 medical and health sciences, plant breeding, medicine, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, nodulation, lcsh:SB1-1110, Partner choice, Competitiveness for nodulation, Pea-rhizobium symbiosis, Nitrogen fixation efficiency, Pisum sativum, Rhizobium leguminosarum sv. viciae, rhizobium leguminosarum, Microbial inoculant, pea-rhizobium symbiosis, Original Research, 2. Zero hunger, Vegetal Biology, Strain (biology), food and beverages, genetic diversity, biology.organism_classification, nitrogen fixation efficiency, 030104 developmental biology, Agronomy, fixation de l'azote, diversité génétique, partner choice, Nitrogen fixation, Co inoculation, Biologie végétale, amélioration des plantes
Abstract

International audience; Pea forms symbiotic nodules with Rhizobium leguminosarum sv. viciae (Rlv). In the field, pea roots can be exposed to multiple compatible Rlv strains. Little is known about the mechanisms underlying the competitiveness for nodulation of Rlv strains and the ability of pea to choose between diverse compatible Rlv strains. The variability of pea-Rlv partner choice was investigated by co-inoculation with a mixture of five diverse Rlv strains of a 104-pea collection representative of the variability encountered in the genus Pisum. The nitrogen fixation efficiency conferred by each strain was determined in additional mono-inoculation experiments on a subset of 18 pea lines displaying contrasted Rlv choice. Differences in Rlv choice were observed within the pea collection according to their genetic or geographical diversities. The competitiveness for nodulation of a given pea-Rlv association evaluated in the multi-inoculated experiment was poorly correlated with its nitrogen fixation efficiency determined in mono-inoculation. Both plant and bacterial genetic determinants contribute to pea-Rlv partner choice. No evidence was found for co-selection of competitiveness for nodulation and nitrogen fixation efficiency. Plant and inoculant for an improved symbiotic association in the field must be selected not only on nitrogen fixation efficiency but also for competitiveness for nodulation.

Published
2018

43. Maize yields over Europe may increase in spite of climate change, with an appropriate use of the genetic variability of flowering time

Author

Mikhail A. Semenov, Sébastien Lacube, Pierre Martre, François Tardieu, Boris Parent, Claude Welcker, Margot Leclere, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Biotechnology and Biological Sciences Research Council, Agence Nationale de la Recherche projects ANR-10-BTBR-01 (Amaizing), ANR-11-INBS-0012 (Phenome), strategic funding from the Biotechnology and Biological Sciences Research Council., ANR-10-BTBR-0001,AMAIZING,Développer de nouvelles variétés de maïs pour une agriculture durable: une approche intégrée de la génomique à la sélection(2010), ANR-11-INBS-0012,PHENOME,Centre français de phénomique végétale(2011), European Project: 244374,EC:FP7:KBBE,FP7-KBBE-2009-3,DROPS(2010), and Biotechnology and Biological Sciences Research Council (BBSRC)

Subjects
Crops, Agricultural, 0106 biological sciences, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Yield, Time Factors, 010504 meteorology & atmospheric sciences, Management practices, Climate change, Flowers, Biology, Zea mays, 01 natural sciences, Crop, Effects of global warming, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, management practices, Genetic variability, Duration (project management), Baseline (configuration management), Fowering time, 0105 earth and related environmental sciences, 2. Zero hunger, Multidisciplinary, Agricultural Sciences, Crop yield, Modeling, Sowing, Agriculture, modeling, flowering time, Biological Sciences, Adaptation, Physiological, Europe, climate change, Agronomy, 13. Climate action, 010606 plant biology & botany
Abstract

Significance The consequences of climate change on European maize yields may become positive if farmers in 2050 use the decision rules they currently follow for adapting plant cycle duration and sowing dates to the diversity of environmental conditions. Experiments and simulations show that the current genetic variability of flowering time allows identifying a cycle duration that maximizes yield at every maize field in Europe. The assumption that farmers use this optimal cycle length in each site was supported by comparison with historical data. Simulated European production for 2050 was stable under the hypotheses of unchanged practices but was increased if farmers continued adopting the decision rules they currently use for adjusting sowing date and crop cycle duration to local environment., Projections based on invariant genotypes and agronomic practices indicate that climate change will largely decrease crop yields. The comparatively few studies considering farmers’ adaptation result in a diversity of impacts depending on their assumptions. We combined experiments and process-based modeling for analyzing the consequences of climate change on European maize yields if farmers made the best use of the current genetic variability of cycle duration, based on practices they currently use. We first showed that the genetic variability of maize flowering time is sufficient for identifying a cycle duration that maximizes yield in a range of European climatic conditions. This was observed in six field experiments with a panel of 121 accessions and extended to 59 European sites over 36 years with a crop model. The assumption that farmers use optimal cycle duration and sowing date was supported by comparison with historical data. Simulations were then carried out for 2050 with 3 million combinations of crop cycle durations, climate scenarios, management practices, and modeling hypotheses. Simulated grain production over Europe in 2050 was stable (−1 to +1%) compared with the 1975–2010 baseline period under the hypotheses of unchanged cycle duration, whereas it was increased (+4–7%) when crop cycle duration and sowing dates were optimized in each local environment. The combined effects of climate change and farmer adaptation reduced the yield gradient between south and north of Europe and increased European maize production if farmers continued to make the best use of the genetic variability of crop cycle duration.

Published
2018

44. Dealing with multi-source and multi-scale information in plant phenomics: the ontology-driven Phenotyping Hybrid Information System

Author

François Tardieu, Romain Chapuis, Vincent Negre, Jonathan Mineau-Cesari, Brigitte Charnomordic, Nadine Hilgert, Isabelle Sanchez, Pascal Neveu, Anne Tireau, Nicolas Brichet, Cyril Pommier, Llorenç Cabrera-Bosquet, Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Domaine expérimental de Melgueil (MONTP MELGUEIL UE), Institut National de la Recherche Agronomique (INRA), Unité de Recherche Génomique Info (URGI), 'Infrastructure Biologie Sante' PHENOME-EMPHASIS project, 'Programme d'Investissements d'Avenir' (PIA), and ANR-11-INBS-0012,PHENOME,Centre français de phénomique végétale(2011)

Subjects
0106 biological sciences, 0301 basic medicine, knowledge, Databases, Factual, Physiology, Computer science, [SDV]Life Sciences [q-bio], Method, interoperability, Plant Science, Information System, Ontology (information science), computer.software_genre, 01 natural sciences, Plot (graphics), Field (computer science), Workflow, User-Computer Interface, 03 medical and health sciences, Phenomics, open source, Methods, Information system, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [INFO]Computer Science [cs], ontology, [MATH]Mathematics [math], data integration, Data Curation, Internet, Information retrieval, Research, Data Visualization, phenomics, Plants, Metadata, Phenotype, 030104 developmental biology, Biological Ontologies, système d'information, [SDE]Environmental Sciences, sélection phénomique, data science, Web service, computer, Information Systems, 010606 plant biology & botany, Data integration
Abstract

International audience; Summary : . Phenomic datasets need to be accessible to the scientific community. Their reanalysis requires tracing relevant information on thousands of plants, sensors and events. . The open-source Phenotyping Hybrid Information System (PHIS) is proposed for plant phenotyping experiments in various categories of installations (field, glasshouse). It unambiguously identifies all objects and traits in an experiment and establishes their relations via ontologies and semantics that apply to both field and controlled conditions. For instance, the genotype is declared for a plant or plot and is associated with all objects related to it. Events such as successive plant positions, anomalies and annotations are associated with objects so they can be easily retrieved. . Its ontology-driven architecture is a powerful tool for integrating and managing data from multiple experiments and platforms, for creating relationships between objects and enriching datasets with knowledge and metadata. It interoperates with external resources via web services, thereby allowing data integration into other systems; for example, modelling platforms or external databases. . It has the potential for rapid diffusion because of its ability to integrate, manage and visualize multi-source and multi-scale data, but also because it is based on 10 yr of trial and error in our groups.

Published
2018
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45. Multivariate genetic analysis of plant responses to water deficit and high temperature revealed contrasting adaptive strategies

Author

Denis Vile, François Vasseur, Christine Granier, Myriam Dauzat, Thibaut Bontpart, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), and Vile, Denis

Subjects
water use efficiency, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, 0106 biological sciences, Arabidopsis thaliana, QTL, Physiology, Arabidopsis, Plant Science, 01 natural sciences, variance génétique, Gene–environment interaction, Transpiration, 2. Zero hunger, Principal Component Analysis, 0303 health sciences, education.field_of_study, Vegetal Biology, Ecotype, déficit hydrique, Phenology, Temperature, efficacité d'utilisation de l'eau, food and beverages, Antagonistic pleiotropy, Genotype by environment interactions, G-matrix, Mixed-effects model, Water use efficiency, Adaptation, Physiological, Agricultural sciences, interaction génotype environnement, Phenotype, pleiotropie, écophysiologie végétale, Research Paper, Genotype, Quantitative Trait Loci, Population, Plant Development, Environment, Quantitative trait locus, Biology, Models, Biological, 03 medical and health sciences, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, photosynthèse, Water-use efficiency, education, Alleles, 030304 developmental biology, photosynthesis, Water, 15. Life on land, Genetic architecture, Agronomy, Multivariate Analysis, Gene-Environment Interaction, Factor Analysis, Statistical, Sciences agricoles, Biologie végétale, 010606 plant biology & botany
Abstract

Summary Plants need to control transpiration and photosynthesis tightly in order to grow under drought and high temperature. Contrasting genetic-by-environment interactions are exploited by Arabidopsis thaliana to improve stress tolerance., How genetic factors control plant performance under stressful environmental conditions is a central question in ecology and for crop breeding. A multivariate framework was developed to examine the genetic architecture of performance-related traits in response to interacting environmental stresses. Ecophysiological and life history traits were quantified in the Arabidopsis thaliana Ler×Cvi mapping population exposed to constant soil water deficit and high air temperature. The plasticity of the genetic variance–covariance matrix (G-matrix) was examined using mixed-effects models after regression into principal components. Quantitative trait locus (QTL) analysis was performed on the predictors of genotype effects and genotype by environment interactions (G×E). Three QTLs previously identified for flowering time had antagonistic G×E effects on carbon acquisition and the other traits (phenology, growth, leaf morphology, and transpiration). This resulted in a size-dependent response of water use efficiency (WUE) to high temperature but not soil water deficit, indicating that most of the plasticity of carbon acquisition and WUE to temperature is controlled by the loci that control variation of development, size, growth, and transpiration. A fourth QTL, MSAT2.22, controlled the response of carbon acquisition to specific combinations of watering and temperature irrespective of plant size and development, growth, and transpiration rate, which resulted in size-independent plasticity of WUE. These findings highlight how the strategies to optimize plant performance may differ in response to water deficit and high temperature (or their combination), and how different G×E effects could be targeted to improve plant tolerance to these stresses.

Published
2014

46. Assessing the effects of architectural variations on light partitioning within virtual wheat–pea mixtures

Author

Didier Combes, Abraham J. Escobar-Gutiérrez, Romain Barillot, Christian Fournier, Pierre Huynh, UPSP Légumineuses, Ecophysiologie Végétale, Agroécologie, LUNAM Université [Nantes Angers Le Mans]-Ecole supérieure d'Agricultures d'Angers (ESA), Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères (P3F), Institut National de la Recherche Agronomique (INRA), Modeling plant morphogenesis at different scales, from genes to phenotype (VIRTUAL PLANTS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA)-Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Groupe ESA, Ecole supérieure d'Agricultures d'Angers (ESA)-Ecole supérieure d'Agricultures d'Angers (ESA)-LUNAM, Unité de recherche Pluridisciplinaire Prairie et Plantes Fourragères [Lusignan], Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)

Subjects
plant architecture, Light, pea, Triticum aestivum, Plant Science, Biology, Models, Biological, Architectural parameters, light interception, plant height, Sativum, wheat, Computer Simulation, Leaf area index, Triticum, Pisum sativum, Plant stem, 2. Zero hunger, Peas, Intercropping, Plant models, Articles, 15. Life on land, biology.organism_classification, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, LAI, Plant Leaves, L-systems, Agronomy, functional –structural plant model, Interception, intercropping
Abstract

International audience; Background and Aims Predicting light partitioning in crop mixtures is a critical step in improving the productivity of such complex systems, and light interception has been shown to be closely linked to plant architecture. The aim of the present work was to analyse the relationships between plant architecture and light partitioning within wheat –pea (Triticum aestivum– Pisum sativum) mixtures. An existing model for wheat was utilized and a new model for pea morphogenesis was developed. Both models were then used to assess the effects of architectural variations in light partitioning. Methods First, a deterministic model (L-Pea) was developed in order to obtain dynamic reconstructions of pea architecture. The L-Pea model is based on L-systems formalism and consists of modules for 'vegetative develop-ment' and 'organ extension'. A tripartite simulator was then built up from pea and wheat models interfaced with a radiative transfer model. Architectural parameters from both plant models, selected on the basis of their contribution to leaf area index (LAI), height and leaf geometry, were then modified in order to generate contrasting architectures of wheat and pea. Key results By scaling down the analysis to the organ level, it could be shown that the number of branches/tillers and length of internodes significantly determined the partitioning of light within mixtures. Temporal relationships between light partitioning and the LAI and height of the different species showed that light capture was mainly related to the architectural traits involved in plant LAI during the early stages of development, and in plant height during the onset of interspecific competition. Conclusions In silico experiments enabled the study of the intrinsic effects of architectural parameters on the par-titioning of light in crop mixtures of wheat and pea. The findings show that plant architecture is an important criterion for the identification/breeding of plant ideotypes, particularly with respect to light partitioning.

Published
2014

47. Phenotyping and beyond: modelling the relationships between traits

Author

Denis Vile, Christine Granier, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), DAGOLIGN Research Training Network (an European Community Human Potential Program) [HPRN-CT-2002-00267], Institut National de Recherches Agronomiques (INRA, 'Ecogene'), GABI-GENOPLANTE project [AF 2001 094], GENOPLANTE [GPLA-06014G], ARABRAS [ERAPG-003-03], AGRONOMICS Integrated Project - sixth European Framework Programme [LSHG-CT-2006-037704], European Union [284443], EIT Climate-KIC project AgWaterBreed, European Project: 284443,EC:FP7:INFRA,FP7-INFRASTRUCTURES-2011-1,EPPN(2012), and Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)

Subjects
business.industry, Plant Science, 15. Life on land, Biology, Plant phenotyping, Models, Biological, Data science, Biotechnology, Phenotype, Quantitative Trait, Heritable, Databases as Topic, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Plant traits, business
Abstract

International audience; Plant phenotyping technology has become more advanced with the capacity to measure many morphological and physiological traits on a given individual. With increasing automation, getting access to various traits on a high number of genotypes over time raises the need to develop systems for data storage and analyses, all congregating into plant phenotyping pipelines. In this review, we highlight several studies that illustrate the latest advances in plant multi-trait phenotyping and discuss future needs to ensure the best use of all these quantitative data. We assert that the next challenge is to disentangle how plant traits are embedded in networks of dependencies (and independencies) by modelling the relationships between them and how these are affected by genetics and environment.

Published
2014

48. Genetic and Physiological Controls of Growth under Water Deficit

Author

François Tardieu, Claude Welcker, Cecílio Frois Caldeira, Boris Parent, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), ANR-08-GENM-003, ANR-08-GENM-0003,DROMADAiR,Un maïs adapté à la sécheresse : développement de l'épi et surface foliaire(2008), European Project: 244374,EC:FP7:KBBE,FP7-KBBE-2009-3,DROPS(2010), and Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, geography, geography.geographical_feature_category, Physiology, Soil water deficit, Plant Science, 15. Life on land, Quantitative trait locus, Biology, Photosynthesis, Lower limit, Sink (geography), Source strength, Agronomy, Genetics, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Genetic variability, Expansive
Abstract

The sensitivity of expansive growth to water deficit has a large genetic variability, which is higher than that of photosynthesis. It is observed in several species, with some genotypes stopping growth in a relatively wet soil, whereas others continue growing until the lower limit of soil-available water. The responses of growth to soil water deficit and evaporative demand share an appreciable part of their genetic control through the colocation of quantitative trait loci as do the responses of the growth of different organs to water deficit. This result may be caused by common mechanisms of action discussed in this paper (particularly, plant hydraulic properties). We propose that expansive growth, putatively linked to hydraulic processes, determines the sink strength under water deficit, whereas photosynthesis determines source strength. These findings have large consequences for plant modeling under water deficit and for the design of breeding programs.

Published
2014

49. Regional and global shifts in crop diversity through the Anthropocene

Author

Denis Vile, Rubén Milla, Marc W. Cadotte, Cyrille Violle, Marney E. Isaac, Adam R. Martin, University of Toronto at Scarborough, Universidad Rey Juan Carlos [Madrid] (URJC), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Natural Sciences and Engineering Research Council of Canada Discovery Grant, Canada Foundation for Innovation, Ontario Research Fund, Natural Sciences and Engineering Research Council of Canada (Grant number 386151), Région Languedoc-Roussillon, 'Chercheur d’Avenir' (FEDER FSE IEJ 2014–2020, Grant Project 'APSEVIR'), Ministerio de Economía y Competitividad of Spain (grants CGL2014-56567-R and PCIN-2014-053), European Union (Eco-serve project, BiodivERsA/001/2014, Horizon 2020), Marie Curie International Outgoing Fellowship (DiversiTraits project, no. 221060), uropean Research Council (ERC) Starting Grant Project StG-2014-639706-CONSTRAINTS., European Project: 221060,EC:FP7:PEOPLE,FP7-PEOPLE-2007-4-1-IOF,DIVERSITRAITS(2009), University of Toronto [Scarborough, Canada], Université Paul-Valéry - Montpellier 3 (UM3)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Université Paul-Valéry - Montpellier 3 (UPVM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut de Recherche pour le Développement (IRD [France-Sud])

Subjects
Plant Phylogenetics, 0106 biological sciences, Conservation genetics, Plant Evolution, Conservation Biology, Biodiversité et Ecologie, Plant Science, 01 natural sciences, Data Management, Conservation Science, 2. Zero hunger, Plant evolution, 0303 health sciences, Multidisciplinary, Geography, Ecology, Agricultural diversification, food and beverages, Agriculture, Biodiversity, Crop Production, Phylogenetics, Phylogeography, Biogeography, Conservation Genetics, Medicine, Research Article, Crops, Agricultural, Computer and Information Sciences, Ecological Metrics, Science, Crops, Biodiversity and Ecology, 03 medical and health sciences, Anthropocene, Genetics, Humans, Evolutionary Systematics, Taxonomy, 030304 developmental biology, Evolutionary Biology, Population Biology, business.industry, Ecology and Environmental Sciences, fungi, Biology and Life Sciences, Species diversity, Species Diversity, 15. Life on land, [SDE.ES]Environmental Sciences/Environmental and Society, Organismal Evolution, Phylogenetic diversity, Crop diversity, 13. Climate action, Earth Sciences, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, business, human activities, Population Genetics, Crop Science, 010606 plant biology & botany
Abstract

International audience; The Anthropocene epoch is partly defined by anthropogenic spread of crops beyond their centres of origin. At global scales, evidence indicates that species-level taxonomic diversity of crops being cultivated on large-scale agricultural lands has increased linearly over the past 50 years. Yet environmental and socioeconomic differences support expectations that temporal changes in crop diversity vary across regions. Ecological theory also suggests that changes in crop taxonomic diversity may not necessarily reflect changes in the evolutionary diversity of crops. We used data from the Food and Agricultural Organization (FAO) of the United Nations to assess changes in crop taxonomic-and phylogenetic diversity across 22 subcontinental-scale regions from 1961-2014. We document certain broad consistencies across nearly all regions: i) little change in crop diversity from 1961 through to the late 1970s; followed by ii) a 10-year period of sharp diversification through the early 1980s; followed by iii) a "levelling-off" of crop diversification beginning in the early 1990s. However, the specific onset and duration of these distinct periods differs significantly across regions and are unrelated to agricultural expansion, indicating that unique policy or environmental conditions influence the crops being grown within a given region. Additionally, while the 1970s and 1980s are defined by region-scale increases in crop diversity this period marks the increasing dominance of a small number of crop species and lineages; a trend resulting in detectable increases in the similarity of crops being grown across regions. Broad similarities in the species-level taxonomic and phylogenetic diversity of crops being grown across regions, primarily at large industrial scales captured by FAO data, represent a unique feature of the Anthropocene epoch. Yet nuanced asymmetries in regional-scale trends suggest that environmental and socioeconomic factors play a key role in shaping observed macro-ecological changes in the plant diversity on agricultural lands.

Published
2019

50. Modeling soil temperature to predict emergence

Author

Véronique Letort, Paul-Henry Cournède, Jérémie Lecoeur, Etienne Claverie, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Mathématiques et Informatique pour la Complexité et les Systèmes (MICS), CentraleSupélec, Mathématiques Appliquées aux Systèmes - EA 4037 (MAS), Ecole Centrale Paris, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)

Subjects
0106 biological sciences, 2. Zero hunger, Hydrology, [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], [SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy, Energy balance, Soil science, 04 agricultural and veterinary sciences, Atmospheric model, Vegetation, 15. Life on land, 01 natural sciences, [SDV.BV.AP]Life Sciences [q-bio]/Vegetal Biology/Plant breeding, Soil water, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Soil horizon, Seedbed, Precipitation, Water content, 010606 plant biology & botany
Abstract

International audience; or annual field crops, the early development phase is crucial in establishing potential crop yield and thus to achieve high yield. Despite its importance, this phase is often neglected in current crop models that focus on later stages and on how plants produce biomass and allocate it to the different organs after emergence. Modeling stand establishment requires assessing accurately enough the conditions of the seedbed, the top 10 cm of the soil profile that serve as growing medium for germinating seeds and plantlets, which drive early development. In this zone, atmospheric conditions generate intense energy and water fluxes, results of biophysical phenomena at the soil-atmosphere interface, and consequently rapid and dramatic changes in temperature and water content that are not yet completely understood. Thus, our goal is to propose a modeling approach to improve the estimation of emergence timing by a simulation of the dynamics of seedbed temperature in response to a few standard meteorological factors that can be routinely acquired: global radiation, air temperature, relative humidity, wind speed and precipitation. The use of these five meteorological factors will allow an easier deployment and use of this model at large scale. We developed a soil model that uses the energy balance approach for the soil surface and a system of coupled partial differential equations for heat and water diffusion in the soil. We made the assumption of a homogeneous soil, without vegetation or residue cover. Our results show that this model is able to capture temporal and spatial variations of the soil temperature and the soil water content. Moreover, this model provides the most critical input data for models predicting the dynamics of emergence. Using data of maize (Zea Mays L.), we evaluate three thermal time models with respectively one, two and three parameters to predict the timing to 50 % of emergence and show that the model with one parameter corresponds to more heat-tolerant varieties and the one with three parameters is more adapted to sensitive cultivars. Finally, we choose the best thermal time model for each cultivar and use the simulated soil temperature to predict emergence on an independent validation dataset. This new emergence model should contribute to the improvement of emergence timing prediction, a key step in reducing the uncertainty in yield prediction.

Published
2016

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