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1. 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
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2. 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
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3. Modelling the transpiration of single maize plants using an explicit xylem flux model

Author

Florian, Heinlein, Xiaohong, Duan, Eckart, Priesack, Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), and Pradal, Christophe

Subjects
[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2020

4. Photosynthesis in a changing global climate: Scaling up and scaling down in crops

Author

Marouane Baslam, Toshiaki Mitsui, Michael Hodges, Eckart Priesack, Matthew T. Herritt, Iker Aranjuelo, Álvaro Sanz-Sáez, Niigata University, 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 Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), USDA-ARS, Arid-Land Agricultural Research Center, United States Department of Agriculture, Centro de Investigaciones Biológicas (CSIC), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Auburn University (AU), ANR-14-CE19-0015,Regul3P,Régulation de la photorespiration par phosphorylation protéique(2014), University of Illinois at Urbana-Champaign [Urbana], University of Illinois System, Japan Science and Technology Agency, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Ministry of Education, Culture, Sports, Science and Technology (Japan), and 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)

Subjects
0106 biological sciences, 0301 basic medicine, phenotyping, omics, Omics, Climate change, Review, Plant Science, lcsh:Plant culture, Photosynthesis, 01 natural sciences, Metabolic engineering, 03 medical and health sciences, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, lcsh:SB1-1110, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, ComputingMilieux_MISCELLANEOUS, Abiotic component, photosynthesis, Ecology, Crop yield, food and beverages, Biosphere, modeling, Climate Change, Crop Improvement, Phenotyping, Modeling, crop improvement, Salinity, 030104 developmental biology, climate change, 13. Climate action, Environmental science, Adaptation, 010606 plant biology & botany
Abstract

Photosynthesis is the major process leading to primary production in the Biosphere. There is a total of 7000bn tons of CO in the atmosphere and photosynthesis fixes more than 100bn tons annually. The CO assimilated by the photosynthetic apparatus is the basis of crop production and, therefore, of animal and human food. This has led to a renewed interest in photosynthesis as a target to increase plant production and there is now increasing evidence showing that the strategy of improving photosynthetic traits can increase plant yield. However, photosynthesis and the photosynthetic apparatus are both conditioned by environmental variables such as water availability, temperature, [CO], salinity, and ozone. The “omics” revolution has allowed a better understanding of the genetic mechanisms regulating stress responses including the identification of genes and proteins involved in the regulation, acclimation, and adaptation of processes that impact photosynthesis. The development of novel non-destructive high-throughput phenotyping techniques has been important to monitor crop photosynthetic responses to changing environmental conditions. This wealth of data is being incorporated into new modeling algorithms to predict plant growth and development under specific environmental constraints. This review gives a multi-perspective description of the impact of changing environmental conditions on photosynthetic performance and consequently plant growth by briefly highlighting how major technological advances including omics, high-throughput photosynthetic measurements, metabolic engineering, and whole plant photosynthetic modeling have helped to improve our understanding of how the photosynthetic machinery can be modified by different abiotic stresses and thus impact crop production., This work was supported by IRUEC project funded by EIG CONCERT-Japan 3rd Joint Call on “Food Crops and Biomass Production Technologies” under the Strategic International Research Cooperative Program of the Japan Science and Technology Agency (JST) and the Spanish Innovation and Universities Ministry (Acciones de programación conjunta Internacional, PCIN-2017-007), and by the ANR-14-CE19-0015 grant REGUL3P. A Grant for Promotion of KAAB Projects (Niigata University) from the Ministry of Education, Culture, Sports, Science, and Technology-Japan is also acknowledged.

Published
2020
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5. Global wheat production with 1.5 and 2.0°C above pre‐industrial warming

Author

Mónica Espadafor, Bing Liu, Frank Ewert, Mukhtar Ahmed, Liujun Xiao, Thilo Streck, Senthold Asseng, Soora Naresh Kumar, Gerrit Hoogenboom, John R. Porter, Sara Minoli, Margarita Garcia-Vila, Joost Wolf, Juraj Balkovic, Alex C. Ruane, Giacomo De Sanctis, Pierre Martre, Roberto C. Izaurralde, Marijn van der Velde, Dominique Ripoche, Roberto Ferrise, Davide Cammarano, Fulu Tao, Bruno Basso, Christoph Müller, Heidi Webber, Yujing Gao, Andrea Maiorano, Christian Klein, Ann-Kristin Koehler, Andrew J. Challinor, Reimund P. Rötter, Garry O'Leary, Manuel Montesino San Martin, Eckart Priesack, Peter J. Thorburn, Heidi Horan, Kurt Christian Kersebaum, Iwan Supit, Zhigan Zhao, Taru Palosuo, Belay T. Kassie, Christian Biernath, Pramod K. Aggarwal, Katharina Waha, Sebastian Gayler, Daniel Wallach, Yan Zhu, Marco Bindi, Zhao Zhang, Claas Nendel, Enli Wang, Curtis D. Jones, Ehsan Eyshi Rezaei, Mikhail A. Semenov, Claudio O. Stöckle, Benjamin Dumont, National Science Foundation (US), National Natural Science Foundation of China, International Food Policy Research Institute (US), CGIAR (France), Institut National de la Recherche Agronomique (France), Federal Ministry of Education and Research (Germany), Biotechnology and Biological Sciences Research Council (UK), China Scholarship Council, Department of Agriculture and Water Resources (Australia), Ministero delle Politiche Agricole Alimentari e Forestali, Gorgan University, Victoria State Government, National Institute of Food and Agriculture (US), Federal Ministry of Food and Agriculture (Germany), German Research Foundation, Academy of Finland, LabEx Agro, Natural Resources Institute Finland, National Engineering and Technology Center for Information Agriculture, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricutural University, 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), Institut für Nutzpflanzenwissenschaften und Ressourcenschutz (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), 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), University of Copenhagen = Københavns Universitet (KU), Lincoln University, University of Leeds, CGIAR-ESSP Program on Climate Change,Agriculture and Food Security, International Center for Tropical Agriculture, Potsdam Institute for Climate Impact Research (PIK), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), International Maize and Wheat Improvement Centre [Inde] (CIMMYT), International Maize and Wheat Improvement Center (CIMMYT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Biological Systems Engineering, Washington State University (WSU), Department of Agronomy, University of El-Tarf, International Institute for Applied Systems Analysis, Ecosystem Services and Management Program, affiliation inconnue, Comenius University in Bratislava, Department of Earth and Environmental Sciences [East Lansing], Michigan State University [East Lansing], Michigan State University System-Michigan State University System, W. K. Kellogg Biological Station (KBS), Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Department of Agrifood Production and Environmental Sciences (DISPAA), Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), The James Hutton Institute, GMO Unit, European Food Safety Authority = Autorité européenne de sécurité des aliments, Université de Liège, University of Córdoba, Department of Crop Sciences, Georg-August-University [Göttingen], Institute of Soil Science and Land Evaluation, University of Hohenheim, 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), Food Systems Institute [Gainesville] (UF|IFAS), Department of Geographical Sciences, College Park, University of Maryland [College Park], University of Maryland System-University of Maryland System, Texas A and M AgriLife Research, Texas A&M University System, European Food Safety Authority (EFSA), Centre for Environment Science and Climate Resilient Agriculture (CESCRA), Indian Agricultural Research Institute (IARI), Agriculture Victoria Research, Institute for Natural Resources, Agroclim (AGROCLIM), Institut National de la Recherche Agronomique (INRA), Tropical Plant Production and Agricultural Systems Modelling (TROPAGS), Centre of Biodiversity and Sustainable Land Use (CBL), University of Göttingen - Georg-August-Universität Göttingen, Rothamsted Research, Wageningen University and Research Centre (WUR), Institute of geographical sciences and natural resources research, Chinese Academy of Sciences [Changchun Branch] (CAS), European Commission - Joint Research Centre [Ispra] (JRC), 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, Plant Production Systems, Wageningen University and Research [Wageningen] (WUR), State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University (BNU), Department of Agronomy and Biotechnology, China Agricultural University (CAU), Agricultural Model Intercomparison and Improvement Project (AgMIP), and Biotechnology and Biological Sciences Research Council (BBSRC), Grant/Award Number: BB/, P016855/1

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, 0106 biological sciences, 010504 meteorology & atmospheric sciences, Food prices, Water en Voedsel, Climate change, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, Model ensemble, Extreme low yields, model ensemble, 1.5°C warming, Temperate climate, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Environmental Chemistry, 0105 earth and related environmental sciences, General Environmental Science, 2. Zero hunger, Global and Planetary Change, WIMEK, Water and Food, Food security, Ecology, business.industry, wheat production, Crop yield, Global warming, food security, 15. Life on land, PE&RC, climate change, Plant Production Systems, 13. Climate action, Agriculture, Plantaardige Productiesystemen, extreme low yields, 8. Economic growth, Environmental science, Wheat production, Water Systems and Global Change, business, Cropping
Abstract

Efforts to limit global warming to below 2°C in relation to the pre‐industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0°C warming above the pre‐industrial period) on global wheat production and local yield variability. A multi‐crop and multi‐climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by −2.3% to 7.0% under the 1.5°C scenario and −2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980–2010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter‐annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer—India, which supplies more than 14% of global wheat. The projected global impact of warming, We thank the Agricultural Model Intercomparison and Improvement Project (AgMIP) for support. B.L., L.X., and Y.Z. were supported by the National Science Foundation for Distinguished Young Scholars (31725020), the National Natural Science Foundation of China (31801260, 51711520319, and 31611130182), the Natural Science Foundation of Jiangsu province (BK20180523), the 111 Project (B16026), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). S.A. and B.K. received support from the International Food Policy Research Institute (IFPRI) through the Global Futures and Strategic Foresight project, the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), and the CGIAR Research Program on Wheat. P.M, D.R., and D.W. 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). F.T. and Z.Z. were supported by the National Natural Science Foundation of China (41571088, 41571493, 31761143006, and 31561143003). R.R. acknowledges support from the German Federal Ministry for Research and Education (BMBF) through project “Limpopo Living Landscapes” project (SPACES program; grant number 01LL1304A). Rothamsted Research receives grant‐aided support from the Biotechnology and Biological Sciences Research Council (BBSRC) Designing Future Wheat project [BB/P016855/1]. L.X. and Y.G. acknowledge support from the China Scholarship Council. M.B and R.F. were funded by JPI FACCE MACSUR2 through the Italian Ministry for Agricultural, Food and Forestry Policies and thank A. Soltani from Gorgan Univ. of Agric. Sci. & Natur. Resour for his support. K.C.K. and C.N. received support from the German Ministry for Research and Education (BMBF) within the FACCE JPI MACSUR project. S.M. and C.M. acknowledge financial support from the MACMIT project (01LN1317A) funded through BMBF. G.J.O. acknowledges support from the Victorian Department of Economic Development, Jobs, Transport and Resources, the Australian Department of Agriculture and Water Resources. P.K.A. was supported by the multiple donors contributing to the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). B.B. received financial support from USDA NIFA‐Water Cap Award 2015‐68007‐23133. F.E. acknowledges support from the FACCE JPI MACSUR project through the German Federal Ministry of Food and Agriculture (2815ERA01J) and from the German Science Foundation (project EW 119/5‐1). J.R.P. acknowledges the support of the Labex Agro (Agropolis no. 1501‐003). La. T.P. and F.T. received financial support from the Academy of Finland through the project PLUMES (decision nos. 277403 and 292836) and from Natural Resources Institute Finland through the project ClimSmartAgri.

Published
2019
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6. Evaluating the precision of eight spatial sampling schemes in estimating regional means of simulated yield for two crops

Author

Elisabet Lewan, Eckart Priesack, Edmar Teixeira, Davide Cammarano, Balázs Grosz, Julie Constantin, Elsa Coucheney, Senthold Asseng, Jagadeesh Yeluripati, Pier Paolo Roggero, Giacomo Trombi, Henrik Eckersten, Stefan Siebert, Specka Xenia, Reimund P. Rötter, Frank Ewert, Thomas Gaiser, Marco Bindi, Marco Moriondo, Matthias Kuhnert, Luca Doro, Christian Klein, Fulu Tao, Gang Zhao, Helene Raynal, Ralf Kiese, Kurt Christian Kersebaum, Claas Nendel, Belay T. Kassie, Christian Biernath, Holger Hoffmann, Edwin Haas, Florian Heinlein, Daniel Wallach, Institute of Crop Science and Resource Conservation [Bonn] (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, The James Hutton Institute, Departement of Soil and Environment, Swedish University of Agricultural Sciences (SLU), Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Institute of landscape systems analysis, INSTITUTE OF BIOLOGICAL AND ENVIRONMENTAL SCIENCES, University of Aberdeen, Environmental Impacts Group, Natural resources institute Finland, 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, Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Institut National de la Recherche Agronomique (INRA), Systems Modelling Team (Sustainable Production Group), Plant & Food Research, Johann Heinrich von Thünen Institut, Università degli Studi di Sassari, Dipartimento di Agraria, University of Sassari, Karlsruhe Institute of Technology (KIT), University of Agricultural Sciences (UAS), 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), Consiglio Nazionale delle Ricerche (CNR), Department of Agri-Food Production and Environmental Sciences, University delgi Studi di Firenze, Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), German Federal Ministry of Food and Agriculture (BMEL) through the Federal Office for Agriculture and Food (BLE) [2851ERA01J], Joint Programme Initiative FACCE, MACSUR Knowledge Hub, German Federal Ministry of Education and Research (BMBF) through the SPACES project 'Living Landscapes Limpopo', WASCAL (West African Science Service Center on Climate Change and Adapted Land Use) project, NOAA RISA grant, FACCE MACSUR project by the Finnish Ministry of Agriculture and Forestry (MMM), Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning [220-2007-1218], strategic funding 'Soil-Water-Landscape' from the faculty of Natural Resources and Agricultural Sciences (Swedish University of Agricultural Sciences), ACCAF INRA meta-program, and Università degli Studi di Sassari = University of Sassari [Sassari] (UNISS)

Subjects
Environmental Engineering, 010504 meteorology & atmospheric sciences, Simple random sampling, [SDV]Life Sciences [q-bio], Stratified random sampling, 01 natural sciences, [SHS]Humanities and Social Sciences, Environment variable, Ecosystem model, Statistics, [INFO]Computer Science [cs], Crop model, [MATH]Mathematics [math], 0105 earth and related environmental sciences, Mathematics, 2. Zero hunger, Ecological Modeling, Crop yield, fungi, food and beverages, Sampling (statistics), Model comparison, 04 agricultural and veterinary sciences, 15. Life on land, Simple random sample, Stratified sampling, Sample size determination, [SDE]Environmental Sciences, Soil water, Up-scaling, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Clustering, Crop Model, Model Comparison, Precision Gain, Simple Random Sampling, Stratified Random Sampling, Precision gain, Software
Abstract

We compared the precision of simple random sampling (SimRS) and seven types of stratified random sampling (StrRS) schemes in estimating regional mean of water-limited yields for two crops (winter wheat and silage maize) that were simulated by fourteen crop models. We found that the precision gains of StrRS varied considerably across stratification methods and crop models. Precision gains for compact geographical stratification were positive, stable and consistent across crop models. Stratification with soil water holding capacity had very high precision gains for twelve models, but resulted in negative gains for two models. Increasing the sample size monotonously decreased the sampling errors for all the sampling schemes. We conclude that compact geographical stratification can modestly but consistently improve the precision in estimating regional mean yields. Using the most influential environmental variable for stratification can notably improve the sampling precision, especially when the sensitivity behavior of a crop model is known. We compare eight sampling schemes for estimating regional mean crop yield.Precision of eight schemes is compared across fourteen crop models.Compact geographical stratification can always improve the precision.Stratification with soil had very high gains of precision for twelve crop models.Our findings can improve the precision of site-based regional crop modeling.

Published
2016
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7. Post-translational Modifications in Plant Nuclear Signaling: Novel Insights Into Responses to Environmental Changes

Author

Stéphane Bourque, Christian Lindermayr, Christian Mazars, Agroécologie [Dijon], 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), Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Laboratoire de Recherche en Sciences Végétales (LRSV), Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, 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, Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS), Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), and Bourque, Stéphane

Subjects
[SDV]Life Sciences [q-bio], SUMO protein, Plant Science, lcsh:Plant culture, 03 medical and health sciences, 0404 agricultural biotechnology, nucleus, post-translation modification (PTM), phosphorylation, acetylation, SUMOylation, medicine, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, lcsh:SB1-1110, 030304 developmental biology, 0303 health sciences, Chemistry, 04 agricultural and veterinary sciences, 040401 food science, Cell biology, medicine.anatomical_structure, Editorial, Acetylation, [SDE]Environmental Sciences, Posttranslational modification, Phosphorylation, Nucleus, Post-translation Modification (ptm), Sumoylation
Abstract

Just imagine a Plant Science professor in front of a classroom full of interested and attentive students. Imagine what their answers to this intriguing question would be: “What are, according to you, the functions ensured by the plant cell nucleus?” It would be very surprising if some of them would answer cell signaling in response to biotic and abiotic stresses or developmental processes. Most of them would probably answer according to a classical point of view: DNA replication or gene expression. Hence it is still admitted in recent publications (see for instance Fedorenko et al., 2010) that molecules smaller than 40 kDa can diffuse freely across the nuclear envelope pores. However, Pauly et al. (2000) showed by studying nuclear Ca2+ signaling that elevations in the extranuclear Ca2+ concentration do not induce an automatic increase of nuclear [Ca2+] as it could be expected. Hence Ca2+ does not freely diffuse across the nuclear envelop pores, indicating that its transport is finely regulated. Then it becomes evident that we should now consider the nucleus as a key component of cell signaling processes leading to the regulation of specific sets of genes. The aim of this topic was to point out how nuclear post-translational modifications (PTMs) play fundamental roles in the signaling pathways initiated in response to environmental changes. Two major points were assessed. First, different papers clearly demonstrate that the nucleus is fully equipped to perform the main PTMs: (de)phosphorylation (Bigeard and Hirt; Krysan and Colcombet), (de)acetylation (Luo et al.; Fül et al.; Ramirez-Prado et al.), oxidoreduction (Martins et al.) or SUMOylation/ubiquitination (Mazur et al.; Serrano et al.). Hence the nucleus can easily integrate a complex network of second messengers including changes in Ca2+ concentration, reactive oxygen species or nitric oxide. Martins et al. nicely exemplified how changes in the nuclear redox status regulate fundamental processes such as cell cycle, protein transport or transcription via S-nitrosylation or S-glutationylation. Activation of nuclear PTMs can also be achieved by the translocation of enzymes which are both substrates and effectors of these PTMs. This is the case for mitogen-activated protein kinases (MAPKs) that in some specific contexts, translocate from the cytosol to the nucleus upon their activation by their corresponding MAPK kinases (Bigeard and Hirt). Relocation of proteins in response to or through PTMs can also be considered at the intranuclear level. Hence in response to SUMO conjugation several Arabidopsis transcription factors were shown to be re-localized in certain nuclear foci (Mazur et al.). PTMs can also affect the behavior of nuclear proteins and in fine their activity. Serrano et al. highlight how the ubiquitin-proteasome system contributes to the nuclear proteome plasticity. Focusing on E3-Ub-ligases, they illustrate how these enzymes attenuate the signaling pathway once the stress has ceased and how they control the homeostasis of nuclear proteins (transcription factors, immune receptors). The second major point of this topic concerns the target proteins of these PTMs. Of course histones are a piece of choice. The review by Ramirez-Prado et al. illustrates how removing or adding marks (phosphorylation, acetylation, methylation, or ubiquitination) on specific histone lysine residues associated to defense genes (WRKYs, pathogenesis-related proteins, etc.) mostly under the control of salicylic acid or jasmonic acid/ethylene signaling pathways, will control the outcome of the plant-microorganism interaction. A second interesting aspect in this review is the illustration of how pathogens manipulate the chromatin regulatory network of the host to achieve their infection process through for example the production of toxins inhibiting histone deacetylases (HDACs), leading to plant susceptibility. PTMs on histones are also of major importance in the response to abiotic stresses. Luo et al reviewed how HDACs, by deacetylating specific lysine residues (mainly H3K9, H3K14, and H4K15) of specific genes regulate responses to salt, drought, cold or heat. However, chromatin remodeling and in fine regulation of gene expression is not only linked to histone modifications. Fül et al. as a perspective in this topic remind us that subunits of key chromatin remodelers (such as MED12, MED13, and MED19A) or transcription factors like Yin Yang 1 in the response to abscisic acid are also targeted and regulated by lysine deacetylases. Hence lysine (de)acetylation regulates gene expression by acting on histones, but also on the whole transcriptional machinery. In conclusion this topic clearly illustrates the diversity of nuclear PTMs, the crosstalks between some of them, and finally their major roles in the regulation of gene expression. A first fascinating challenge is now to decipher at the molecular level the ways cells are using to translocate signals from cytoplasm to the nucleus that regulate nuclear PTMs. A second one is to go further in the characterization of their target proteins: as it is now nicely exemplified by the interplay of histone marks in epigenetics, this is the sine qua non condition to fully understand the power of nuclear PTMs.

Published
2019
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8. Simulation of maize evapotranspiration: An inter-comparison among 29 maize models

Author

Amit Kumar Srivastava, Sotirios V. Archontoulis, Qianjing Jiang, Kenneth J. Boote, Delphine Deryng, Sophie Moulin, Jean-Louis Durand, Munir P. Hoffmann, Lajpat R. Ahuja, Sebastian Gayler, Jerry L. Hatfield, Philip Parker, Thomas Gaiser, Dennis Timlin, Tracy E. Twine, Claudio O. Stöckle, Benjamin Dumont, Jon I. Lizaso, Claas Nendel, Soo-Hyung Kim, Kelly R. Thorp, Karina Williams, Christian Baron, Tommaso Stella, Zhiming Qi, Bruno Basso, Heidi Webber, F. Ewert, Taru Palosuo, Fulu Tao, Magali Willaume, Eckart Priesack, Julie Constantin, Patrick Bertuzzi, Bruce A. Kimball, USDA-ARS : Agricultural Research Service, Agronomy Department, University of Florida [Gainesville] (UF), National laboratory for agriculture and the environment, Agricultural Systems Research Unit, USDA, Biological Systems Engineering, Washington State University (WSU), Department of Agronomy, Purdue University [West Lafayette], Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre national du machinisme agricole, du génie rural, des eaux et forêts (CEMAGREF), Université de Montpellier (UM), Michigan State University [East Lansing], Michigan State University System, Agroclim (AGROCLIM), Institut National de la Recherche Agronomique (INRA), 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, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), IRI THESys, Humboldt State University (HSU), Université de Liège, Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères (P3F), Institute of Crop Science and Resource Conservation [Bonn], Rheinische Friedrich-Wilhelms-Universität Bonn, Institute of Soil Science and Land Evaluation, Biogeophysics, University of Hohenheim, Department of Bioresource Engineering, McGill University = Université McGill [Montréal, Canada], School of Environmental and Forest Sciences, University of Washington [Seattle], Technical University of Madrid, Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Spatial Business Integration, Partenaires INRAE, Natural Resources Institute Finland (LUKE), Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Institute of Geographic Sciences and Natural Resources Research, CAS, Crop Systems and Global Change Research Unit, Met Office Hadley Centre, (BMBF, Germany) FKZ031A258B, and German Federal Ministry of Education and Research 01LL1304A

Subjects
0106 biological sciences, Atmospheric Science, Yield, 010504 meteorology & atmospheric sciences, maïs, F60 - Physiologie et biochimie végétale, Crop water use, Eddy covariance, Zea mays, 01 natural sciences, Maize, Simulation, Evapotranspiration, Water Use, Model, Statistics, Range (statistics), [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Squared deviations, 0105 earth and related environmental sciences, Mathematics, 2. Zero hunger, Global and Planetary Change, U10 - Informatique, mathématiques et statistiques, Phenology, Forestry, Évapotranspiration, 13. Climate action, Besoin en eau, Agronomy and Crop Science, Modèle mathématique, Water use, 010606 plant biology & botany
Abstract

International audience; Crop yield can be affected by crop water use and vice versa, so when trying to simulate one or the other, it can be important that both are simulated well. In a prior inter-comparison among maize growth models, evapotranspiration (ET) predictions varied widely, but no observations of actual ET were available for comparison. Therefore, this follow-up study was initiated under the umbrella of AgMIP (Agricultural Model Inter-Comparison and Improvement Project). Observations of daily ET using the eddy covariance technique from an 8-year-long (2006-2013) experiment conducted at Ames, IA were used as the standard for comparison among models. Simulation results from 29 models are reported herein. In the first "blind" phase for which only weather, soils, phenology, and management information were provided to the modelers, estimates of seasonal ET varied from about 200 to about 700 mm. Subsequent three phases provided (1) leaf area indices for all years, (2) all daily ET and agronomic data for a typical year (2011), and (3) all data for all years, thus allowing the modelers to progressively calibrate their models as more information was provided, but the range among ET estimates still varied by a factor of two or more. Much of the variability among the models was due to differing estimates of potential evapotranspiration, which suggests an avenue for substantial model improvement. Nevertheless, the ensemble median values were generally close to the observations, and the medians were best (had the lowest mean squared deviations from observations, MSD) for several ET categories for inter-comparison, but not all. Further, the medians were best when considering both ET and agronomic parameters together. The best six models with the lowest MSDs were identified for several ET and agronomic categories, and they proved to vary widely in complexity in spite of having similar prediction accuracies. At the same time, other models with apparently similar approaches were not as accurate. The models that are widely used tended to perform better, leading us speculate that a larger number of users testing these models over a wider range of conditions likely has led to improvement. User experience and skill at calibration and dealing with missing input data likely were also a factor in determining the accuracy of model predictions. In several cases different versions of a model within the same family of models were run, and these within-family inter-comparisons identified particular approaches that were better while other factors were held constant. Thus, improvement is needed in many of the models with regard to their ability to simulate ET over a wide range of conditions, and several aspects for progress have been identified, especially in their simulation of potential ET.

Published
2019
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9. Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

Author

Hoffmann, Holger, Zhao, Gang, Asseng, Senthold, Bindi, Marco, Biernath, Christian, Constantin, Julie, Coucheney, Elsa, Dechow, Rene, Doro, Luca, Eckersten, Henrik, Gaiser, Thomas, Grosz, Balázs, Heinlein, Florian, Kassie, Belay T., Klein, Christian, Kuhnert, Matthias, Lewan, Elisabet, Moriondo, Marco, Nendel, Claas, Priesack, Eckart, Raynal, Helene, Roggero, Pier P., Rötter, Reimund P., Siebert, Stefan, Specka, Xenia, Tao, Fulu, Teixeira, Edmar, Trombi, Giacomo, Wallach, Daniel, Weihermüller, Lutz, Yeluripati, Jagadeesh, Ewert, Frank, Kersebaum, Kurt Christian, Crop Science Group, Rheinische Friedrich-Wilhelms-Universität Bonn, 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), Department of Agri-Food Production and Environmental Sciences, University delgi Studi di Firenze, Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), 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, Department of Soil and Environment, University of Agricultural Sciences (UAS), Johann Heinrich von Thünen Institut, Desertification Research Group, University of Sassari, Department of Crop Production Ecology, Swedish University of Agricultural Sciences (SLU), Institute of landscape systems analysis, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Helmholtz-Zentrum Dresden-Rossendorf (HZDR), University of Aberdeen, Consiglio Nazionale delle Ricerche (CNR), Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Institut National de la Recherche Agronomique (INRA), Environmental Impacts Group, Natural resources institute Finland, Plant & Food Research, Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association, Craigiebuckler, The James Hutton Institute, German Federal Ministry of Food and Agriculture (BMEL) through Federal Office for Agriculture and Food (BLE) [2851ERA01J], FACCE MACSUR through Finnish Ministry of Agriculture and Forestry (MMM) [3200009600], Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning [220-2007-1218], faculty of Natural Resources and Agricultural Sciences (Swedish University of Agricultural Sciences), INRA ACCAF metaprogram, UR MIAT INRA, Helmholtz project 'REKLIM - Regional Climate Change', HGF Alliance 'Remote Sensing and Earth System Dynamics' (EDA), German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) [FOR1695], German Science Foundation [EW 119/5-1], Università degli Studi di Sassari = University of Sassari [Sassari] (UNISS), and Hoffmann, Holger

Subjects
winter-wheat, 010504 meteorology & atmospheric sciences, Databases, Factual, SYSTEMS SIMULATION, NITROGEN DYNAMICS, WINTER-WHEAT, CROP MODELS, DATA RESOLUTION, SCALE, WATER, VARIABILITY, CALIBRATION, WEATHER, [SDV]Life Sciences [q-bio], nitrogen dynamics, 01 natural sciences, [SHS]Humanities and Social Sciences, Geographical Locations, Soil, Yield (wine), Agricultural Soil Science, Germany, Range (statistics), [MATH]Mathematics [math], Triticum, 2. Zero hunger, Multidisciplinary, Simulation and Modeling, Sampling (statistics), Agriculture, 04 agricultural and veterinary sciences, Plants, data resolution, Europe, Agricultural soil science, [SDE]Environmental Sciences, Wheat, Medicine, ddc:500, Seasons, Maize, Simulation and modeling, Winter, Cereal crops, Research Article, Crops, Agricultural, Climate Change, Science, Soil Science, Soil science, Crops, Research and Analysis Methods, Zea mays, crop models, scale, Model Organisms, Plant and Algal Models, Calibration, [INFO]Computer Science [cs], Computer Simulation, Grasses, Agricultural Science, 0105 earth and related environmental sciences, AGR/02 Agronomia e coltivazioni erbacee, variability, Crop yield, Ecology and Environmental Sciences, Organisms, Biology and Life Sciences, Water, Oryza, 15. Life on land, calibration, Data aggregator, 13. Climate action, People and Places, 040103 agronomy & agriculture, Earth Sciences, 0401 agriculture, forestry, and fisheries, Environmental science, systems, Scale (map), water, Crop Science, Cereal Crops
Abstract

International audience; We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by

Published
2016
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10. Soil Organic Carbon and Nitrogen Feedbacks on Crop Yields under Climate Change

Author

Basso, B., Dumont, B., Maestrini, B., Shcherbak, I., Robertson, G.P., Porter, J.R., Smith, P.J., Paustian, K., Grace, P.R., Asseng, S., Bassu, S., Biernath, C.J., Boote, K.J., Cammarano, D., de Sanctis, G., Durand, J.L., Ewert, F., Gayler, S., Grant, R., Hyndman, D.W., Kent, J.W., Martre, P., Nendel, C., Priesack, E., Ripoche, D., Ruane, A.C., Sharp, J., Thorburn, P.J., Hatfield, J.L., Jones, J.W., Rosenzweig, C., Michigan State University [East Lansing], Michigan State University System, W. K. Kellogg Biological Station (KBS), Michigan State University System-Michigan State University System, Université de Liège, 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), INSTITUTE OF BIOLOGICAL AND ENVIRONMENTAL SCIENCES, University of Aberdeen, Colorado State University [Fort Collins] (CSU), Institute for Future Environments, Queensland University of Technology, University of Florida [Gainesville] (UF), European Commission, Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), The James Hutton Institute, European Food Safety Authority (EFSA), Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères (P3F), Institut National de la Recherche Agronomique (INRA), Institute of Crop Science and Resource Conservation [Bonn] (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, Institute of Soil Science and Land Evaluation, University of Hohenheim, 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), Leibniz Association, Agroclim (AGROCLIM), National Aeronautics and Space Administration, Partenaires INRAE, Plant & Food Research, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), USDA-ARS : Agricultural Research Service, UKAID for its primary financial support to the Agricultural Model Intercomparison and Improvement Project (AgMIP), USDA-NIFA under awards 2015-68007-23133, 2011-67003-3025, and 2011-68002-30190, FACCE JPI MACSUR project (031A103B), metaprogram Adaptation of Agriculture and Forests to Climate Change (AAFCC) of the French National Institute for Agricultural Research (INRA), and Swiss National Science Foundation (project number 167689).

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, scénario climatique, 010504 meteorology & atmospheric sciences, Soil Science, Climate change, Management, Monitoring, Policy and Law, 01 natural sciences, modèle de rendement, zea mays, Derivative (finance), carbone organique du sol, triticum aestivum, License, Publication, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, Explicit permission, 2. Zero hunger, changement climatique, business.industry, Crop yield, 04 agricultural and veterinary sciences, Soil carbon, 15. Life on land, Environmental economics, Agricultural sciences, 13. Climate action, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Business, Agronomy and Crop Science, Sciences agricoles, modèle de production
Abstract

A critical omission from climate change impact studies on crop yield is the interaction between soil organic carbon (SOC), nitrogen (N) availability, and carbon dioxide (CO2). We used a multimodel ensemble to predict the effects of SOC and N under different scenarios of temperatures and CO2 concentrations on maize (Zea mays L.) and wheat (Triticum aestivum L.) yield in eight sites across the world. We found that including feedbacks from SOC and N losses due to increased temperatures would reduce yields by 13% in wheat and 19% in maize for a 3°C rise temperature with no adaptation practices. These losses correspond to an additional 4.5% (+3°C) when compared to crop yield reductions attributed to temperature increase alone. Future CO2 increase to 540 ppm would partially compensate losses by 80% for both maize and wheat at +3°C, and by 35% for wheat and 20% for maize at +6°C, relative to the baseline CO2 scenario.

Published
2018
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11. Large-Scale Phenomics Identifies Primary and Fine-Tuning Roles for CRKs in Responses Related to Oxidative Stress

Author

Gildas Bourdais, Paweł Burdiak, Adrien Gauthier, Lisette Nitsch, Jarkko Salojärvi, Channabasavangowda Rayapuram, Niina Idänheimo, Kerri Hunter, Sachie Kimura, Ebe Merilo, Aleksia Vaattovaara, Krystyna Oracz, David Kaufholdt, Andres Pallon, Damar Tri Anggoro, Dawid Glów, Jennifer Lowe, Ji Zhou, Omid Mohammadi, Tuomas Puukko, Andreas Albert, Hans Lang, Dieter Ernst, Hannes Kollist, Mikael Brosché, Jörg Durner, Jan Willem Borst, David B Collinge, Stanisław Karpiński, Michael F Lyngkjær, Silke Robatzek, Michael Wrzaczek, Jaakko Kangasjärvi, CRK Consortium, Department of Agricultural Sciences, Biosciences, Bioinformatics for Molecular Biology and Genomics (BMBG), Viikki Plant Science Centre (ViPS), Receptor-Ligand Signaling Group, Plant Biology, Plant-Fungal Interactions Group, Plant stress and natural variation, Plant ROS-Signalling, Institut de Recherche en Horticulture et Semences (IRHS), Université d'Angers (UA)-Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Plante - microbe - environnement : biochimie, biologie cellulaire et écologie (PMEBBCE), Etablissement National d'Enseignement Supérieur Agronomique de Dijon (ENESAD)-Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), University of Oulu, Physiologie des Semences, Université Pierre et Marie Curie - Paris 6 (UPMC), Fisico-Quimica Biologica, Universidade Federal do Rio de Janeiro (UFRJ), Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), 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 National de la Recherche Scientifique (CNRS)-Université de Bourgogne (UB)-Institut National de la Recherche Agronomique (INRA)-Etablissement National d'Enseignement Supérieur Agronomique de Dijon (ENESAD), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA)-Université d'Angers (UA), and Universidade Federal do Rio de Janeiro [Rio de Janeiro] (UFRJ)

Subjects
0106 biological sciences, Cancer Research, [SDV]Life Sciences [q-bio], Arabidopsis, protein-kinase, Pseudomonas syringae, 01 natural sciences, Biochemistry, Adapter molecule crk, light acclimation, Phenomics, Gene Expression Regulation, Plant, Arabidopsis thaliana, transcriptional regulation, Genetics (clinical), ComputingMilieux_MISCELLANEOUS, Regulation of gene expression, 0303 health sciences, biology, EPS-1, 1184 Genetics, developmental biology, physiology, flagellin perception, Adaptation, Physiological, Cell biology, receptor-like kinase, multiple sequence alignment, Signal Transduction, Research Article, DNA, Bacterial, Xanthine Oxidase, lcsh:QH426-470, stomatal immunity, Protein domain, Biochemie, arabidopsis-thaliana, Protein Serine-Threonine Kinases, pseudomonas-syringae, 03 medical and health sciences, Ascomycota, Genetics, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, Molecular Biology, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, Plant Diseases, Arabidopsis Proteins, biology.organism_classification, cell-death, [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy, Oxidative Stress, lcsh:Genetics, Adaptation, Reactive Oxygen Species, Function (biology), 010606 plant biology & botany
Abstract

Cysteine-rich receptor-like kinases (CRKs) are transmembrane proteins characterized by the presence of two domains of unknown function 26 (DUF26) in their ectodomain. The CRKs form one of the largest groups of receptor-like protein kinases in plants, but their biological functions have so far remained largely uncharacterized. We conducted a large-scale phenotyping approach of a nearly complete crk T-DNA insertion line collection showing that CRKs control important aspects of plant development and stress adaptation in response to biotic and abiotic stimuli in a non-redundant fashion. In particular, the analysis of reactive oxygen species (ROS)-related stress responses, such as regulation of the stomatal aperture, suggests that CRKs participate in ROS/redox signalling and sensing. CRKs play general and fine-tuning roles in the regulation of stomatal closure induced by microbial and abiotic cues. Despite their great number and high similarity, large-scale phenotyping identified specific functions in diverse processes for many CRKs and indicated that CRK2 and CRK5 play predominant roles in growth regulation and stress adaptation, respectively. As a whole, the CRKs contribute to specificity in ROS signalling. Individual CRKs control distinct responses in an antagonistic fashion suggesting future potential for using CRKs in genetic approaches to improve plant performance and stress tolerance., Author Summary Receptor-like kinases (RLKs) are important regulators in signal transduction in plants. However, the large number of RLKs and their high sequence similarity has hampered the analysis of RLKs. One of the largest subgroups of RLKs, the cysteine-rich receptor-like kinases (CRKs), has been suggested to be involved in mediating the effects of reactive oxygen species (ROS). While ROS are recognized as important signalling elements with a large variety of roles in plants, their ligands and achievement of signalling specificity remain unknown. Using insertion mutants we analysed the roles of CRKs in plant development and stress responses and show that CRKs have important roles as mediators of signalling specificity during regulation of stomatal aperture. Our study shows that, despite their large number and high sequence conservation, individual CRKs have intriguingly distinct functions in different aspects of plant life. This makes the CRKs promising candidates for future studies of their biochemical function.

Published
2015
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12. Sesquiterpene volatile organic compounds (VOCs) are markers of elicitation by sulfated laminarine in grapevine

Author

Jörg-Peter Schnitzler, Sophie Trouvelot, Xavier Daire, Marielle Adrian, Karine Gourrat, J. B. Winkler, Malik Chalal, Frank Jamois, Agroécologie [Dijon], 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, Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Centre des Sciences du Goût et de l'Alimentation (CSGA), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), and Laboratoires Goëmar S.A.S.

Subjects
[SDV]Life Sciences [q-bio], Defence mechanisms, Plant Science, lcsh:Plant culture, Sesquiterpene, Terpene, chemistry.chemical_compound, Laminarin, PTR-QMS, SPME-GC-MS, downy mildew, methylsalicylate, plant defenses, terpenes, Botany, [SDV.IDA]Life Sciences [q-bio]/Food engineering, Plant defense against herbivory, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, lcsh:SB1-1110, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering, Original Research, Ptr-qms, Spme-gc-ms, Downy Mildew, Methylsalicylate, Plant Defenses, Terpenes, food and beverages, Elicitor, Horticulture, chemistry, [SDE]Environmental Sciences, Downy mildew, Methyl salicylate
Abstract

SPE IPM UB CT1; International audience; Inducing resistance in plants by the application of elicitors of defense reactions is an attractive plant protection strategy, particularly for grapevine (Vitis vinifera), which is susceptible to severe fungal diseases. Although induced resistance (IR) can be successful under controlled conditions, in most cases, IR is not sufficiently effective for practical disease control under outdoor conditions. Progress in the application of IR requires a better understanding of grapevine defense mechanisms and the ability to monitor defense markers to identify factors, such as physiological and environmental factors, that can impact IR in the vineyard. Volatile organic compounds (VOCs) are well-known plant defense compounds that have received little or no attention to date in the case of grape-pathogen interactions. This prompted us to investigate whether an elicitor, the sulfated laminarin (PS3), actually induces the production of VOCs in grapevine. An online analysis (proton-transfer-reaction quadrupole mass spectrometry) of VOC emissions in dynamic cuvettes and passive sampling in gas-tight bags with solid-phase microextraction-GC-MS under greenhouse conditions showed that PS3 elicited the emission of VOCs. Some of them, such as (E,E)-α-farnesene, may be good candidates as biomarkers of elicitor-IR, whereas methyl salicylate appears to be a biomarker of downy mildew infection. A negative correlation between VOC emission and disease severity suggests a positive role of VOCs in grape defense against diseases.

Published
2015
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13. Dual Roles of Reactive Oxygen Species and NADPH Oxidase RBOHD in an Arabidopsis-Alternaria Pathosystem

Author

Levente Kiss, Anita Dongo, Günther Bahnweg, Alexandra Pintye, Sebastian Grün, Miklós Pogány, Balázs Barna, Jörg Durner, Philippe Simoneau, Uta von Rad, Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Unité de recherche Pathologie végétale et phytobactériologie, Institut National de la Recherche Agronomique (INRA), Plant Protection Institute, and Shanxi Academy of Agricultural Sciences

Subjects
DNA, Bacterial, Programmed cell death, Physiology, Molecular Sequence Data, Arabidopsis, Glycine, Plant Science, MOSAIC VIRUS INFECTION, ALTERNARIA, [SDV.GEN.GPL]Life Sciences [q-bio]/Genetics/Plants genetics, chemistry.chemical_compound, BOTRYTIS CINEREA, Gene Expression Regulation, Plant, DISEASE RESISTANCE RESPONSE, Thiadiazoles, Genetics, Arabidopsis thaliana, HYDROGEN PEROXIDE, Oligonucleotide Array Sequence Analysis, Plant Diseases, chemistry.chemical_classification, Alternaria brassicicola, HYPERSENSITIVE RESPONSE, Reactive oxygen species, DEFENSE RESPONSE, NADPH oxidase, Cell Death, biology, Arabidopsis Proteins, Gene Expression Profiling, Wild type, NADPH Oxidases, Ethylenes, biology.organism_classification, SALICYLIC ACID, OXIDATIVE BURST, Cell biology, Mutagenesis, Insertional, chemistry, Biochemistry, RNA, Plant, biology.protein, INDUCED CELL DEATH, Reactive Oxygen Species, Salicylic acid, NITRIC OXIDE, Research Article
Abstract

Arabidopsis (Arabidopsis thaliana) NADPH oxidases have been reported to suppress the spread of pathogen- and salicylic acid-induced cell death. Here, we present dual roles of RBOHD (for respiratory burst oxidase homolog D) in an Arabidopsis-Alternaria pathosystem, suggesting either initiation or prevention of cell death dependent on the distance from pathogen attack. Our data demonstrate that a rbohD knockout mutant exhibits increased spread of cell death at the macroscopic level upon inoculation with the fungus Alternaria brassicicola. However, the cellular patterns of reactive oxygen species accumulation and cell death are fundamentally different in the AtrbohD mutant compared with the wild type. Functional RBOHD causes marked extracellular hydrogen peroxide accumulation as well as cell death in distinct, single cells of A. brassicicola-infected wild-type plants. This single cell response is missing in the AtrbohD mutant, where infection triggers spreading-type necrosis preceded by less distinct chloroplastic hydrogen peroxide accumulation in large clusters of cells. While the salicylic acid analog benzothiadiazole induces the action of RBOHD and the development of cell death in infected tissues, the ethylene inhibitor aminoethoxyvinylglycine inhibits cell death, indicating that both salicylic acid and ethylene positively regulate RBOHD and cell death. Moreover, A. brassicicola-infected AtrbohD plants hyperaccumulate ethylene and free salicylic acid compared with the wild type, suggesting negative feedback regulation of salicylic acid and ethylene by RBOHD. We propose that functional RBOHD triggers death in cells that are damaged by fungal infection but simultaneously inhibits death in neighboring cells through the suppression of free salicylic acid and ethylene levels.

Published
2009
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14. Role of a Single Aquaporin Isoform in Root Water Uptake

Author

Josette Güçlü, Hélène Javot, Virginie Lauvergeat, Christophe Maurel, Joëlle Vinh, Fabrice Martin-Laurent, Véronique Santoni, Katja I. Franck, David Bouchez, Anton R. Schäffner, Julian A. Heyes, Signalisation de l'Adaptation des Végétaux à l'Environnement (SAVE), Institut de Biosciences et Biotechnologies d'Aix-Marseille (ex-IBEB) (BIAM), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Biochimie et Physiologie Moléculaire des Plantes (BPMP), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-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), Microbiologie du Sol et de l'Environnement (MSE), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB), Neurobiologie et diversité cellulaire (NDC), Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Université Paris sciences et lettres (PSL), Institute of Biochemical Plant Pathology, German Research Center for Environmental Health - Helmholtz Center München (GmbH), Institut Jean-Pierre Bourgin (IJPB), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Université de Montpellier (UM)-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 National de la Recherche Scientifique (CNRS), ESPCI ParisTech-Centre National de la Recherche Scientifique (CNRS), Ecole Superieure de Physique et Chimie Industrielles (ESPCI), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Unité de recherche Génétique et amélioration des plantes (GAP), Institut National de la Recherche Agronomique (INRA), Institut des sciences du végétal (ISV), Centre National de la Recherche Scientifique (CNRS), Institute of Biochemical Plant Pathology (BIOP), Laboratoire de Biologie du Développement des Plantes ( LBDP ), Université de la Méditerranée - Aix-Marseille 2-Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Centre National de la Recherche Scientifique ( CNRS ), Biochimie et Physiologie Moléculaire des Plantes ( BPMP ), Centre international d'études supérieures en sciences agronomiques ( Montpellier SupAgro ) -Institut national de la recherche agronomique [Montpellier] ( INRA Montpellier ) -Université de Montpellier ( UM ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Microbiologie du Sol et de l'Environnement ( MSE ), Institut National de la Recherche Agronomique ( INRA ) -Université de Bourgogne ( UB ), Neurobiologie et diversité cellulaire ( NDC ), ESPCI ParisTech-Centre National de la Recherche Scientifique ( CNRS ), Ecole Superieure de Physique et Chimie Industrielles ( ESPCI ), Institut Jean-Pierre Bourgin ( IJPB ), and Institut National de la Recherche Agronomique ( INRA ) -AgroParisTech

Subjects
0106 biological sciences, ADNT, Mads-box genes, [SDV]Life Sciences [q-bio], Mutant, Arabidopsis, Plant Science, channels, 01 natural sciences, [ CHIM ] Chemical Sciences, Plant Roots, Ion Channels, [ SDE ] Environmental Sciences, Gene Expression Regulation, Plant, Protein Isoforms, ComputingMilieux_MISCELLANEOUS, Plant Proteins, 0303 health sciences, phenotypes, Gene Expression Regulation, Developmental, Fluid transport, secretion, Biochemistry, t-dna, [SDE]Environmental Sciences, lipids (amino acids, peptides, and proteins), GENE MAD-BOX, Research Article, Gene isoform, mice, Molecular Sequence Data, Aquaporin, arabidopsis-thaliana, Biology, Aquaporins, [SDV.GEN.GPL]Life Sciences [q-bio]/Genetics/Plants genetics, 03 medical and health sciences, expression, [CHIM]Chemical Sciences, Amino Acid Sequence, 030304 developmental biology, intrinsic proteins, [ SDV ] Life Sciences [q-bio], Base Sequence, Sequence Homology, Amino Acid, Arabidopsis Proteins, transformation, Wild type, Major intrinsic proteins, Water, Plant Transpiration, Cell Biology, biology.organism_classification, Mutation, Endodermis, ABSORPTION HYDRIQUE, 010606 plant biology & botany
Abstract

43 ref.; International audience; Aquaporins are ubiquitous channel proteins that facilitate the transport of water across cell membranes. Aquaporins show a typically high isoform multiplicity in plants, with 35 homologs in Arabidopsis. The integrated function of plant aquaporins and the function of each individual isoform remain poorly understood. Matrix-assisted laser desorption/ionization time- of-flight analyses suggested that Plasma Membrane Intrinsic Protein2;2 (PIP2;2) is one of the abundantly expressed aquaporin isoforms in Arabidopsis root plasma membranes. Two independent Arabidopsis knockout mutants of PIP2;2 were isolated using a PCR-based strategy from a library of plant lines mutagenized by the insertion of Agrobacterium tumefaciens T-DNA. Expression in transgenic Arabidopsis of a PIP2;2 promoter-beta-glucuronidase gene fusion indicated that PIP2;2 is expressed predominantly in roots, with a strong expression in the cortex, endodermis, and stele. The hydraulic conductivity of root cortex cells, as measured with a cell pressure probe, was reduced by 25 to 30% in the two allelic PIP2;2 mutants compared with the wild type. In addition, free exudation measurements revealed a 14% decrease, with respect to wild-type values, in the osmotic hydraulic conductivity of roots excised from the two PIP2;2 mutants. Together, our data provide evidence for the contribution of a single aquaporin gene to root water uptake and identify PIP2;2 as an aquaporin specialized in osmotic fluid transport. PIP2;2 has a close homolog, PIP2;3, showing 96.8% amino acid identity. The phenotype of PIP2;2 mutants demonstrates that, despite their high homology and isoform multiplicity, plant aquaporins have evolved with nonredundant functions.

Published
2003
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15. Prediction of Evapotranspiration and Yields of Maize: An Inter-comparison among 31 Maize Models

Author

Bruce Kimball, Boote, K., Hatfield, J., Ahuja, L., Stockle, C., Archontoulis, S., Baron, C., Bruno Basso, Patrick Bertuzzi, Chen, M., Julie Constantin, Derying, D., Dumont, B., Jean-Louis Durand, Ewert, F., Gaiser, T., Gayler, S., Griffis, T., Hoffmann, M., Jiang, Q., Soo-Hyung Kim, Lizaso, J., Sophie Moulin, Nendel, C., Parker, P., Palosuo, T., Priesack, E., Zhiming Qi Z., Srivastava, A., Stella, T., Tao, F., Thorp, K., Timlin, D., Twine, T., Heidi Webber, Magali Willaume, Williams, K., ProdInra, Migration, USDA-ARS : Agricultural Research Service, Agronomy Department, University of Florida [Gainesville], National laboratory for agriculture and the environment, Agricultural Systems Research Unit, USDA, Agricultural Research Service, United States Department of Agriculture - Agricultural Research Service, Biological Systems Engineering, University of Wisconsin-Madison, Department of Agronomy, Purdue University [West Lafayette], Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS), Department of Geological Sciences and W. K. Kellogg Biological Station, Michigan State University [East Lansing], Michigan State University System-Michigan State University System, UE Agroclim (UE AGROCLIM), Institut National de la Recherche Agronomique (INRA), Department of Soil, Water, and Climate, University of Minnesota System, UMR : AGroécologie, Innovations, TeRritoires, Ecole Nationale Supérieure Agronomique de Toulouse, Computation Institute, Loyola University of Chicago, ULg-GxABT, Gembloux Agro-Bio Tech Faculty, Dpt. Agronomy, Bio-Engineering and Chemistry, Crop Science Unit, Université de Liège, Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères (P3F), Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Institute of Crop Science and Resource Conservation, University of Bonn-Division of Plant Nutrition, Institute of Soil Science and Land Evaluation, Biogeophysics, University of Hohenheim, Crop Production Systems in the Tropics, Georg-August-Universität Göttingen, Department of Bioresource Engineering, Macdonald Campus, Université McGill, Center for Urban Horticulture, University of Washington, Dept. Producción Agraria-CEIGRAM, Universidad Politécnica de Madrid (UPM), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Natural Resources Institute Finland, Institute of Biochemical Plant Pathology, German Research Center for Environmental Health - Helmholtz Center München (GmbH), Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences [Beijing] (CAS), Crop Systems and Global Change Research Unit, Climate Adaptation Scientist Meteorological Office, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), University of Florida [Gainesville] (UF), Agroclim (AGROCLIM), 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, Institute of Crop Science and Resource Conservation [Bonn] (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, Georg-August-University [Göttingen], McGill University = Université McGill [Montréal, Canada], Natural resources institute Finland, Washington State University (WSU), Michigan State University System, Department of Soil, Water and Climate, Institute of Crop Science and Resource Conservation [Bonn], Natural Resources Institute Finland (LUKE), Institute of Biochemical Plant Pathology (BIOP), and Agricultural Model Intercomparison and Improvement Project (AgMIP). USA.

Subjects
[SDE] Environmental Sciences, Evapotranspiration, maïs, [SDV]Life Sciences [q-bio], évapotranspiration, analyse de covariance, modèle de croissance, [SHS]Humanities and Social Sciences, caracteristique variétale, Maize, covariance analysis, [SDV] Life Sciences [q-bio], densité de surface foliaire, potentiel de croissance, [SDE]Environmental Sciences, rendement agricole, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [SDV.BV] Life Sciences [q-bio]/Vegetal Biology, [SHS] Humanities and Social Sciences, Crop model
Abstract

International audience; An important aspect that determines the ability of crop growth models to predict growth and yield is their ability to predict the rate of water consumption or evapotranspiration (ET) of the crop, especially for rain-fed crops. If, for example, the predicted ET rate is too high, the simulated crop may exhaust its soil water supply before the next rain event, thereby causing growth and yield predictions that are too low. In a prior inter-comparison among maize growth models, ET predictions varied widely, but no observations of actual ET were available for comparison. Therefore, another study has been initiated under the umbrella of AgMIP (Agricultural Model Inter-Comparison and Improvement Project). This time observations of ET using the eddy covariance technique from an 8-year-long experiment conducted at Ames, IA are being used as the standard. Simulation results from 31 models have been completed. In the first “blind” phase for which only weather, soils, and management information were furnished to the modelers, estimates of seasonal ET varied from about 200 to about 700 mm. A detailed statistical analysis of the daily ET data from 2011, a “typical” rainfall year, showed that, as expected, the median of all the models was more accurate across several criteria (correlation, root mean square error, average difference, regression slope) than any particular model. However, some individual models were better than the median for a particular criteria. Predictions improved in later stages when the modelers were provided additional leaf area, growth, and the actual ET observations that allowed them to “calibrate” some of the parameters in their models to account for varietal characteristics, etc. Bruce

16. European oak chemical diversity - from ecotypes to herbivore resistance.

Author

Bertić M, Schroeder H, Kersten B, Fladung M, Orgel F, Buegger F, Schnitzler JP, and Ghirardo A

Subjects
Animals, Ecotype, Forests, Herbivory, Trees, Quercus
Abstract

Climate change is increasing insect pressure and forcing plants to adapt. Although chemotypic differentiation and phenotypic plasticity in spatially separated tree populations are known for decades, understanding their importance in herbivory resistance across forests remains challenging. We studied four oak forest stands in Germany using nontarget metabolomics, elemental analysis, and chemometrics and mapped the leaf metabolome of herbivore-resistant (T-) and herbivore-susceptible (S-) European oaks (Quercus robur) to Tortrix viridana, an oak pest that causes severe forest defoliation. Among the detected metabolites, we identified reliable metabolic biomarkers to distinguish S- and T-oak trees. Chemotypic differentiation resulted in metabolic shifts of primary and secondary leaf metabolism. Across forests, T-oaks allocate resources towards constitutive chemical defense enriched of polyphenolic compounds, e.g. the flavonoids kaempferol, kaempferol and quercetin glucosides, while S-oaks towards growth-promoting substances such as carbohydrates and amino-acid derivatives. This extensive work across natural forests shows that oaks' resistance and susceptibility to herbivory are linked to growth-defense trade-offs of leaf metabolism. The discovery of biomarkers and the developed predictive model pave the way to understand Quercus robur's susceptibility to herbivore attack and to support forest management, contributing to the preservation of oak forests in Europe., (© 2021 The Authors. New Phytologist © 2021 New Phytologist Foundation.)

Published
2021
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17. Fusarium head blight resistance in European winter wheat: insights from genome-wide transcriptome analysis.

Author

Buerstmayr M, Wagner C, Nosenko T, Omony J, Steiner B, Nussbaumer T, Mayer KFX, and Buerstmayr H

Subjects
Disease Resistance genetics, Gene Expression Profiling, Plant Diseases genetics, Triticum genetics, Fusarium
Abstract

Background: Fusarium head blight (FHB) is a devastating disease of wheat worldwide. Resistance to FHB is quantitatively controlled by the combined effects of many small to medium effect QTL. Flowering traits, especially the extent of extruded anthers, are strongly associated with FHB resistance., Results: To characterize the genetic basis of FHB resistance, we generated and analyzed phenotypic and gene expression data on the response to Fusarium graminearum (Fg) infection in 96 European winter wheat genotypes, including several lines containing introgressions from the highly resistant Asian cultivar Sumai3. The 96 lines represented a broad range in FHB resistance and were assigned to sub-groups based on their phenotypic FHB severity score. Comparative analyses were conducted to connect sub-group-specific expression profiles in response to Fg infection with FHB resistance level. Collectively, over 12,300 wheat genes were Fusarium responsive. The core set of genes induced in response to Fg was common across different resistance groups, indicating that the activation of basal defense response mechanisms was largely independent of the resistance level of the wheat line. Fg-induced genes tended to have higher expression levels in more susceptible genotypes. Compared to the more susceptible non-Sumai3 lines, the Sumai3-derivatives demonstrated higher constitutive expression of genes associated with cell wall and plant-type secondary cell wall biogenesis and higher constitutive and Fg-induced expression of genes involved in terpene metabolism. Gene expression analysis of the FHB QTL Qfhs.ifa-5A identified a constitutively expressed gene encoding a stress response NST1-like protein (TraesCS5A01G211300LC) as a candidate gene for FHB resistance. NST1 genes are key regulators of secondary cell wall biosynthesis in anther endothecium cells. Whether the stress response NST1-like gene affects anther extrusion, thereby affecting FHB resistance, needs further investigation., Conclusion: Induced and preexisting cell wall components and terpene metabolites contribute to resistance and limit fungal colonization early on. In contrast, excessive gene expression directs plant defense response towards programmed cell death which favors necrotrophic growth of the Fg pathogen and could thus lead to increased fungal colonization.

Published
2021
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18. Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat.

Author

Michel S, Wagner C, Nosenko T, Steiner B, Samad-Zamini M, Buerstmayr M, Mayer K, and Buerstmayr H

Subjects
Genome, Plant, Genomics, Plant Diseases genetics, RNA-Seq, Selection, Genetic, Triticum microbiology, Disease Resistance genetics, Fusarium pathogenicity, Plant Breeding methods, Plant Diseases microbiology, Triticum genetics
Abstract

Genomic selection with genome-wide distributed molecular markers has evolved into a well-implemented tool in many breeding programs during the last decade. The resistance against Fusarium head blight (FHB) in wheat is probably one of the most thoroughly studied systems within this framework. Aside from the genome, other biological strata like the transcriptome have likewise shown some potential in predictive breeding strategies but have not yet been investigated for the FHB-wheat pathosystem. The aims of this study were thus to compare the potential of genomic with transcriptomic prediction, and to assess the merit of blending incomplete transcriptomic with complete genomic data by the single-step method. A substantial advantage of gene expression data over molecular markers has been observed for the prediction of FHB resistance in the studied diversity panel of breeding lines and released cultivars. An increase in prediction ability was likewise found for the single-step predictions, although this can mostly be attributed to an increased accuracy among the RNA-sequenced genotypes. The usage of transcriptomics can thus be seen as a complement to already established predictive breeding pipelines with pedigree and genomic data, particularly when more cost-efficient multiplexing techniques for RNA-sequencing will become more accessible in the future.

Published
2021
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19. Publisher Correction: Extensive signal integration by the phytohormone protein network.

Author

Altmann M, Altmann S, Rodriguez PA, Weller B, Vergara LE, Palme J, la Rosa NM, Sauer M, Wenig M, Villaécija-Aguilar JA, Sales J, Lin CW, Pandiarajan R, Young V, Strobel A, Gross L, Carbonnel S, Kugler KG, Garcia-Molina A, Bassel GW, Falter C, Mayer KFX, Gutjahr C, Vlot AC, Grill E, and Falter-Braun P

Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2020
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20. Extensive signal integration by the phytohormone protein network.

Author

Altmann M, Altmann S, Rodriguez PA, Weller B, Elorduy Vergara L, Palme J, Marín-de la Rosa N, Sauer M, Wenig M, Villaécija-Aguilar JA, Sales J, Lin CW, Pandiarajan R, Young V, Strobel A, Gross L, Carbonnel S, Kugler KG, Garcia-Molina A, Bassel GW, Falter C, Mayer KFX, Gutjahr C, Vlot AC, Grill E, and Falter-Braun P

Subjects
Arabidopsis genetics, Arabidopsis Proteins genetics, Protein Binding, Protein Interaction Mapping, Reproducibility of Results, Transcription, Genetic, Arabidopsis metabolism, Arabidopsis Proteins metabolism, Plant Growth Regulators metabolism, Protein Interaction Maps, Signal Transduction
Abstract

Plant hormones coordinate responses to environmental cues with developmental programs 1 , and are fundamental for stress resilience and agronomic yield 2 . The core signalling pathways underlying the effects of phytohormones have been elucidated by genetic screens and hypothesis-driven approaches, and extended by interactome studies of select pathways 3 . However, fundamental questions remain about how information from different pathways is integrated. Genetically, most phenotypes seem to be regulated by several hormones, but transcriptional profiling suggests that hormones trigger largely exclusive transcriptional programs 4 . We hypothesized that protein-protein interactions have an important role in phytohormone signal integration. Here, we experimentally generated a systems-level map of the Arabidopsis phytohormone signalling network, consisting of more than 2,000 binary protein-protein interactions. In the highly interconnected network, we identify pathway communities and hundreds of previously unknown pathway contacts that represent potential points of crosstalk. Functional validation of candidates in seven hormone pathways reveals new functions for 74% of tested proteins in 84% of candidate interactions, and indicates that a large majority of signalling proteins function pleiotropically in several pathways. Moreover, we identify several hundred largely small-molecule-dependent interactions of hormone receptors. Comparison with previous reports suggests that noncanonical and nontranscription-mediated receptor signalling is more common than hitherto appreciated.

Published
2020
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21. Physiological responses of date palm (Phoenix dactylifera) seedlings to acute ozone exposure at high temperature.

Author

Du B, Kreuzwieser J, Winkler JB, Ghirardo A, Schnitzler JP, Ache P, Alfarraj S, Hedrich R, White P, and Rennenberg H

Subjects
Air Pollutants metabolism, Ascorbic Acid metabolism, Glutathione Reductase metabolism, Nitrogen metabolism, Ozone metabolism, Plant Leaves drug effects, Plant Roots metabolism, Seedlings drug effects, Seedlings physiology, Air Pollutants toxicity, Ozone toxicity, Phoeniceae physiology, Temperature
Abstract

Vegetation in the Arabian Peninsula is facing high and steadily rising tropospheric ozone pollution. However, little is known about the impacts of elevated ozone on date palms, one of the most important indigenous economic species. To elucidate the physiological responses of date palm to peak levels of acute ozone exposure, seedlings were fumigated with 200 ppb ozone for 8 h. Net CO 2 assimilation rate, stomatal conduction, total carbon, its isotope signature and total sugar contents in leaves and roots were not significantly affected by the treatment and visible symptoms of foliar damage were not induced. Ozone exposure did not affect hydrogen peroxide and thiol contents but diminished the activities of glutathione reductase and dehydroascorbate reductase, stimulated the oxidation of ascorbate, and resulted in elevated total ascorbate contents. Total nitrogen, soluble protein and lignin contents remained unchanged upon ozone exposure, but the abundance of low molecular weight nitrogen (LMWN) compounds such as amino acids and nitrate as well as other anions were strongly diminished in leaves and roots. Other nitrogen pools did not benefit from the decline of LMWN, indicating reduced uptake and/or enhanced release of these compounds into the soil as a systemic response to aboveground ozone exposure. Several phenolic compounds, concurrent with fatty acids and stearyl alcohol, accumulated in leaves, but declined in roots, whereas total phenol contents significantly increased in the roots. Together these results indicate that local and systemic changes in both, primary and secondary metabolism contribute to the high tolerance of date palms to short-term acute ozone exposure., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Published
2018
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22. Sesquiterpene emissions from Alternaria alternata and Fusarium oxysporum: Effects of age, nutrient availability, and co-cultivation.

Author

Weikl F, Ghirardo A, Schnitzler JP, and Pritsch K

Subjects
Alternaria growth & development, Coculture Techniques, Fusarium growth & development, Gas Chromatography-Mass Spectrometry, Sesquiterpenes analysis, Volatile Organic Compounds analysis, Alternaria metabolism, Fusarium metabolism, Sesquiterpenes metabolism, Volatile Organic Compounds metabolism
Abstract

Alternaria alternata is one of the most studied fungi to date because of its impact on human life - from plant pathogenicity to allergenicity. However, its sesquiterpene emissions have not been systematically explored. Alternaria regularly co-occurs with Fusarium fungi, which are common plant pathogens, on withering plants. We analyzed the diversity and determined the absolute quantities of volatile organic compounds (VOCs) in the headspace above mycelial cultures of A. alternata and Fusarium oxysporum under different conditions (nutrient rich and poor, single cultures and co-cultivation) and at different mycelial ages. Using stir bar sorptive extraction and gas chromatography-mass spectrometry, we observed A. alternata to strongly emit sesquiterpenes, particularly during the early growth stages, while emissions from F. oxysporum consistently remained comparatively low. The emission profile characterizing A. alternata comprised over 20 sesquiterpenes with few effects from nutrient quality and age on the overall emission profile. Co-cultivation with F. oxysporum resulted in reduced amounts of VOCs emitted from A. alternata although its profile remained similar. Both fungi showed distinct emission profiles, rendering them suitable biomarkers for growth-detection of their phylotype in ambient air. The study highlights the importance of thorough and quantitative evaluations of fungal emissions of volatile infochemicals such as sesquiterpenes.

Published
2016
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