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4. Multi-environment field trials for wheat yield, stability and breeding progress in Germany.

Author

Wang, Tien-Cheng, Rose, Till, Zetzsche, Holger, Ballvora, Agim, Friedt, Wolfgang, Kage, Henning, Léon, Jens, Lichthardt, Carolin, Ordon, Frank, Snowdon, Rod J, Stahl, Andreas, Stützel, Hartmut, Wittkop, Benjamin, and Chen, Tsu-Wei

Subjects
CROP science, AGRICULTURE, PLANT yields, AGRICULTURAL policy, CROP management
Abstract

Multi-environmental trials (MET) with temporal and spatial variance are crucial for understanding genotype-environment-management (GxExM) interactions in crops. Here, we present a MET dataset for winter wheat in Germany. The dataset encompasses MET spanning six years (2015–2020), six locations and nine crop management scenarios (consisting of combinations for three treatments, unbalanced in each location and year) comparing 228 cultivars released between 1963 and 2016, amounting to a total of 526,751 data points covering 24 traits. Beside grain yield, ten agronomic traits, four baking quality traits, plant height, heading date, maturity date and six fungal disease infection indices are included. Additionally, we provide management records, including fertilizer use, plant protection measures, irrigation, and weather data. We demonstrate how this dataset can address four agronomic questions related to GxExM interactions. Further potential applications of the dataset include empirical analyses, genomic and enviromic analyses for breeding targets, or development of decision-supporting models for agricultural management and policy decisions. [ABSTRACT FROM AUTHOR]

Published
2025
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5. Affine and Regional Dynamic Time Warpng

Author

Chen, Tsu-Wei, Abdelmaseeh, Meena, and Stashuk, Daniel

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Computational Engineering, Finance, and Science, Computer Science - Learning
Abstract

Pointwise matches between two time series are of great importance in time series analysis, and dynamic time warping (DTW) is known to provide generally reasonable matches. There are situations where time series alignment should be invariant to scaling and offset in amplitude or where local regions of the considered time series should be strongly reflected in pointwise matches. Two different variants of DTW, affine DTW (ADTW) and regional DTW (RDTW), are proposed to handle scaling and offset in amplitude and provide regional emphasis respectively. Furthermore, ADTW and RDTW can be combined in two different ways to generate alignments that incorporate advantages from both methods, where the affine model can be applied either globally to the entire time series or locally to each region. The proposed alignment methods outperform DTW on specific simulated datasets, and one-nearest-neighbor classifiers using their associated difference measures are competitive with the difference measures associated with state-of-the-art alignment methods on real datasets.

Published
2015

11. Breeding improves wheat productivity under contrasting agrochemical input levels

Author

Voss-Fels, Kai P., Stahl, Andreas, Wittkop, Benjamin, Lichthardt, Carolin, Nagler, Sabrina, Rose, Till, Chen, Tsu-Wei, Zetzsche, Holger, Seddig, Sylvia, Majid Baig, Mirza, Ballvora, Agim, Frisch, Matthias, Ross, Elizabeth, Hayes, Ben J., Hayden, Matthew J., Ordon, Frank, Leon, Jens, Kage, Henning, Friedt, Wolfgang, Stützel, Hartmut, and Snowdon, Rod J.

Published
2019
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13. Plant nutritional value of aquaculture water produced by feeding Nile tilapia (Oreochromis niloticus) alternative protein diets: A lettuce and basil case study.

Author

Jones, Jeffrey J., Shaw, Christopher, Chen, Tsu‐Wei, Staß, Christopher Martin, Ulrichs, Christian, Riewe, David, Kloas, Werner, and Geilfus, Christoph‐Martin

Subjects
FISH feeds, PLANT nutrients, DIETARY proteins, BASIL, NILE tilapia, NUTRITIONAL value, LETTUCE, HERMETIA illucens, AQUACULTURE
Abstract

Societal Impact Statement: Refining circular multitrophic food production methods, which integrate plant, fish, and insect outputs, is imperative for environmental sustainability. Our findings suggest that the right protein choices in fish feed, like black soldier fly meal and poultry meal, can notably enhance the nutrient profile of fish waste water. This, in turn, is conducive for hydroponic cultivation, enhancing the nutritional attributes of plants like basil and lettuce. As we reduce environmental impact and optimize resource use, it is evident that our food ecosystems are deeply intertwined. Harnessing these synergies could redefine our approach to food production, paving the way for a more sustainable global future. Summary: Optimization of nutrient use efficiencies in circular multitrophic food production systems (i.e., plant, fish, and insect production) is crucial for sustainability. This study tested how protein ingredient choice in fish feed influences the plant nutritional value of the fish waste water when used for hydroponic crop production.Waste water samples were obtained from recirculating aquaculture systems (RAS) in which Nile tilapia (Oreochromis niloticus) were fed different single protein source diets—black soldier fly meal (BSFM), poultry by‐product meal (PM), poultry blood meal (PBM), and fish meal. Water was analyzed for plant nutrients and used for lettuce and basil cultivation to evaluate their suitability for hydroponic crop production—viz. yield, mineral nutrient, and selected secondary metabolite levels.BSFM RAS water had the highest concentrations of K, Mg, and micronutrients (Cu, Mn, Mo, Zn) of the RAS waters, whereas PM RAS water contained the highest P concentration and had a mean pH of 6.5 closer to the optimum pH for hydroponic plants. These RAS waters consequently lead to the highest yields in basil and lettuce indicating the importance of the aforementioned factors.From a plant production perspective, BSFM appears promising as a protein source in fish feeds for aquaponics. Usage of RAS waters for plant production helps reduce (i) environmental impact of RAS water and (ii) resource input in plant production. Longer term RAS trials should be conducted to determine the maximum nutrient concentrations achievable during fish production with diets including BSFM as the main protein source. [ABSTRACT FROM AUTHOR]

Published
2024
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15. Plant nutritional value of aquaculture water produced by feeding Nile tilapia (Oreochromis niloticus) alternative protein diets: A lettuce and basil case study

Author

Jones, Jeffrey J., Shaw, Christopher, Chen, Tsu-Wei, Staß, Christopher Martin, Ulrichs, Christian, Riewe, David, Kloas, Werner, Geilfus, Christoph-Martin, Jones, Jeffrey J., Shaw, Christopher, Chen, Tsu-Wei, Staß, Christopher Martin, Ulrichs, Christian, Riewe, David, Kloas, Werner, and Geilfus, Christoph-Martin

Abstract

Societal Impact Statement Refining circular multitrophic food production methods, which integrate plant, fish, and insect outputs, is imperative for environmental sustainability. Our findings suggest that the right protein choices in fish feed, like black soldier fly meal and poultry meal, can notably enhance the nutrient profile of fish waste water. This, in turn, is conducive for hydroponic cultivation, enhancing the nutritional attributes of plants like basil and lettuce. As we reduce environmental impact and optimize resource use, it is evident that our food ecosystems are deeply intertwined. Harnessing these synergies could redefine our approach to food production, paving the way for a more sustainable global future. Summary - Optimization of nutrient use efficiencies in circular multitrophic food production systems (i.e., plant, fish, and insect production) is crucial for sustainability. This study tested how protein ingredient choice in fish feed influences the plant nutritional value of the fish waste water when used for hydroponic crop production. - Waste water samples were obtained from recirculating aquaculture systems (RAS) in which Nile tilapia (Oreochromis niloticus) were fed different single protein source diets—black soldier fly meal (BSFM), poultry by-product meal (PM), poultry blood meal (PBM), and fish meal. Water was analyzed for plant nutrients and used for lettuce and basil cultivation to evaluate their suitability for hydroponic crop production—viz. yield, mineral nutrient, and selected secondary metabolite levels. - BSFM RAS water had the highest concentrations of K, Mg, and micronutrients (Cu, Mn, Mo, Zn) of the RAS waters, whereas PM RAS water contained the highest P concentration and had a mean pH of 6.5 closer to the optimum pH for hydroponic plants. These RAS waters consequently lead to the highest yields in basil and lettuce indicating the importance of the aforementioned factors. - From a plant production perspective, BSFM appears prom, Bundesminesterium für Bildung und Forschung, Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) http://dx.doi.org/10.13039/501100001659, Open Access Publication Fund of Humboldt Universität zu Berlin, Peer Reviewed

Published
2023

16. Optimal coordination between photosynthetic acclimation strategy and canopy architecture in two contrasting cucumber cultivars

Author

Pao, Yi-Chen, Stützel, Hartmut, Chen, Tsu-Wei, Pao, Yi-Chen, Stützel, Hartmut, and Chen, Tsu-Wei

Abstract

Crop varieties differing in architectural characteristics (AC) vary in their intra-canopy light distribution. To optimize canopy photosynthesis, we hypothesize that varieties with contrasting AC possess different photosynthetic acclimation strategy (PAS) with respect to photosynthetic nitrogen (Np) partitioning. We firstly used in silico experiments to test this hypothesis and suggested a trade-off in Np partitioning between carboxylation and light harvesting to achieve optimal coordination between PAS, AC and growing light environment. Then, two cucumber (Cucumis sativus L.) cultivars, Aramon and SC-50, which were bred under greenhouse vertical single-stem and field creeping multi-branch canopy, were selected for studying their differences in AC and PAS using greenhouse and growth chamber experiments, respectively. In the greenhouse, more horizontal leaves of SC-50 resulted in steeper intra-canopy light gradient and a higher degree of self-shading, especially in the upper canopy layer. In growth chamber experiments, Aramon invested more leaf nitrogen into photosynthesis than SC-50, and the proportion (pNp) increased as light was reduced. In contrast, pNp of SC-50 did not respond to light but SC-50 partitioned its limited Np between carboxylation and light harvesting functions more effectively, showing a strategy particularly advantageous for canopies with a high degree of self-shading. This is further confirmed by additional in silico experiments showing that Np partitioning of SC-50 coped better with the impact of strong light competition caused by low light and by leaf clumping under high planting density. These findings provide a comprehensive perspective of genotypic variation in PAS, canopy architectures and their optimal coordination., Peer Reviewed

Published
2023

22. How does structure matter? Comparison of canopy photosynthesis using one- And three-dimensional light models: A case study using greenhouse cucumber canopies

Author

Pao, Yi-Chen, Kahlen, Katrin, Chen, Tsu-Wei, Wiechers, Dirk, Stützel, Hartmut, Pao, Yi-Chen, Kahlen, Katrin, Chen, Tsu-Wei, Wiechers, Dirk, and Stützel, Hartmut

Abstract

One-dimensional light models using the Beer-Lambert equation (BL) with the light extinction coefficient k are simple and robust tools for estimating light interception of homogeneous canopies. Functional-structural plant models (FSPMs) are powerful to capture light-plant interactions in heterogeneous canopies, but they are also more complex due to explicit descriptions of three-dimensional plant architecture and light models. For choosing an appropriate modelling approach, the trade-offs between simplicity and accuracy need to be considered when canopies with spatial heterogeneity are concerned. We compared two light modelling approaches, one following BL and another using ray tracing (RT), based on a framework of a dynamic FSPM of greenhouse cucumber. Resolutions of hourly step (HS) and daily step (DS) were applied to simulate light interception, leaf-level photosynthetic acclimation and plant-level dry matter production over growth periods of 2-5 weeks. Results showed that BL-HS was comparable to RT-HS in predicting shoot dry matter and photosynthetic parameters. The k used in the BL approach was simulated using an empirical relationship between k and leaf area index established with the assistance of RT, which showed variation up to 0.2 in k depending on canopy geometry under the same plant density. When a constant k value was used instead, a difference of 0.2 in k resulted in up to 27 % loss in accuracy for shoot dry matter. These results suggested that, with the assistance of RT in k estimation, the simple approach BL-HS provided efficient estimation for long-term processes.

Published
2021

28. Data: Breeding improves wheat productivity under contrasting agrochemical input levels

Author

Voss-Fels, Kai, Stahl, Andreas, Wittkop, Benjamin, Lichthardt, Carolin, Nagler, Sabrina, Rose, Till, Chen, Tsu-Wei, Zetzsche, Holger, Seddig, Sylvia, Baig, Mirza Majid, Ballvora, Agim, Ordon, Frank, Léon, Jens, Kage, Henning, Friedt, Wolfgang, Stützel, Hartmut, and Snowdon, Rod J.

Subjects
climate change, wheat, breeding history, food security, agriculture
Abstract

This is the experimental data set of Voss-Fels, et. al. (2019. Nature Plants). The first table (NP2019_MainExperiment_adjMeans.csv) presents the adjusted mean trait data of the full panel of 191 elite winter wheat cultivars in the main experiment. Data for each trait were considered independently for each of three cropping intensities. High, medium and low intensities represent HiN/HiF, HiN/NoF and LoN/NoF, respectively. Details are described in the supplementary Figure 2.The second table (NP2019_ValidationExperiment_adjMeans.csv) presents the adjusted mean yield of 52 elite winter wheat cultivars in the validation experiment., Contact: Dr. Tsu-Wei Chen (ORCID: 0000-0001-6698-563X), Leibniz Universität Hannover.

Published
2019
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29. Co-Evolution of Sink and Source in the Recent Breeding History of Winter Wheat in Germany

Author

Lichthardt, Carolin, Chen, Tsu-Wei, Stahl, Andreas, Stützel, Hartmut, Lichthardt, Carolin, Chen, Tsu-Wei, Stahl, Andreas, and Stützel, Hartmut

Abstract

Optimizing the interplay between sinks and sources is of crucial importance for breeding progress in winter wheat. However, the physiological limitations of yield from source (e.g. green canopy duration, GCD) and sink (e.g. grain number) are still unclear. Furthermore, there is little information on how the source traits have been modified during the breeding history of winter wheat. This study analyzed the breeding progress of sink and source components and their relationships to yield components. Field trials were conducted over three years with 220 cultivars representing the German breeding history of the past five decades. In addition, genetic associations of QTL for the traits were assessed with genome-wide association studies. Breeding progress mainly resulted from an increase in grain numbers per spike, a sink component, whose variations were largely explained by the photosynthetic activity around anthesis, a source component. Surprisingly, despite significant breeding progress in GCD and other source components, they showed no direct influence on thousand grain weights, indicating that grain filling was not limited by the source strength. Our results suggest that, 1) the potential longevity of the green canopy is predetermined at the time point that the number of grains is fixed; 2) a co-evolution of source and sink strength during the breeding history contribute to the yield formation of the modern cultivars. For future breeding we suggest to choose parental lines with high grain numbers per spike on the sink side, and high photosynthetic activity around anthesis and canopy duration on the source side, and to place emphasis on these traits throughout selection.

Published
2020

30. Crop adaptation to climate change as a consequence of long-term breeding

Author

Snowdon, Rod, Wittkop, Benjamin, Chen, Tsu-Wei, Stahl, Andreas, Snowdon, Rod, Wittkop, Benjamin, Chen, Tsu-Wei, and Stahl, Andreas

Abstract

Major global crops in high-yielding, temperate cropping regions are facing increasing threats from the impact of climate change, particularly from drought and heat at critical developmental timepoints during the crop lifecycle. Research to address this concern is frequently focused on attempts to identify exotic genetic diversity showing pronounced stress tolerance or avoidance, to elucidate and introgress the responsible genetic factors or to discover underlying genes as a basis for targeted genetic modification. Although such approaches are occasionally successful in imparting a positive effect on performance in specific stress environments, for example through modulation of root depth, major-gene modifications of plant architecture or function tend to be highly context-dependent. In contrast, long-term genetic gain through conventional breeding has incrementally increased yields of modern crops through accumulation of beneficial, small-effect variants which also confer yield stability via stress adaptation. Here we reflect on retrospective breeding progress in major crops and the impact of long-term, conventional breeding on climate adaptation and yield stability under abiotic stress constraints. Looking forward, we outline how new approaches might complement conventional breeding to maintain and accelerate breeding progress, despite the challenges of climate change, as a prerequisite to sustainable future crop productivity., Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347, Justus-Liebig-Universität Gießen (3114), Peer Reviewed

Published
2020

31. Phenomenal: An automatic open source library for 3D shoot architecture reconstruction and analysis for image-based plant phenotyping

Author

Artzet, Simon, Chen, Tsu Wei, Chopard, Jérôme, Brichet, Nicolas, Mielewczik, Michael, Cohen-Boulakia, Sarah, Cabrera Bosquet, Llorenç, Tardieu, Francois, Fournier, Christian, and Pradal, Christophe

Subjects
plateforme de phénotypage, Traitement des images, Vegetal Biology, Open source, Automatic pipeline, Image analysis, Scientific workflow, 3D reconstruction, libre accès, Image Processing, modèle 3d, analyse d'image, Biologie végétale, architecture de la plante, topologie
Abstract

In the era of high-throughput visual plant phenotyping, it is crucial to design fully automated and flexible workflows able to derive quantitative traits from plant images. Over the last years, several software supports the extraction of architectural features of shoot systems. Yet currently no end-to-end systems are able to extract both 3D shoot topology and geometry of plants automatically from images on large datasets and a large range of species. In particular, these software essentially deal with dicotyledons, whose architecture is comparatively easier to analyze than monocotyledons. To tackle these challenges, we designed the Phenomenal software featured with: (i) a completely automatic workflow system including data import, reconstruction of 3D plant architecture for a range of species and quantitative measurements on the reconstructed plants; (ii) an open source library for the development and comparison of new algorithms to perform 3D shoot reconstruction and (iii) an integration framework to couple workflow outputs with existing models towards model-assisted phenotyping. Phenomenal analyzes a large variety of data sets and species from images of high-throughput phenotyping platform experiments to published data obtained in different conditions and provided in a different format. Phenomenal has been validated both on manual measurements and synthetic data simulated by 3D models. It has been also tested on other published datasets to reproduce a published semi-automatic reconstruction workflow in an automatic way. Phenomenal is available as an open-source software on a public repository.

Published
2019

34. Phenomenal: An automatic open source library for 3D shoot architecture reconstruction and analysis for image-based plant phenotyping

Author

Artzet, Simon, primary, Chen, Tsu-Wei, additional, Chopard, Jérôme, additional, Brichet, Nicolas, additional, Mielewczik, Michael, additional, Cohen-Boulakia, Sarah, additional, Cabrera-Bosquet, Llorenç, additional, Tardieu, François, additional, Fournier, Christian, additional, and Pradal, Christophe, additional

Published
2019
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36. Changes in the vertical distribution of leaf area enhanced light interception efficiency in maize over generations of maize selection

Author

Perez, Raphaël, Fournier, Christian, Cabrera-Bosquet, Llorenç, Artzet, Simon, Pradal, Christophe, Brichet, Nicolas, Chen, Tsu-Wei, Chapuis, Romain, Welcker, Claude, Tardieu, François, Perez, Raphaël, Fournier, Christian, Cabrera-Bosquet, Llorenç, Artzet, Simon, Pradal, Christophe, Brichet, Nicolas, Chen, Tsu-Wei, Chapuis, Romain, Welcker, Claude, and Tardieu, François

Abstract

Breeders select for yield, thereby indirectly selecting for traits that contribute to it. We tested if breeding has affected a range of traits involved in plant architecture and light interception, via the analysis of a panel of 60 maize hybrids released from 1950‐2015. This was based on novel traits calculated from reconstructions derived from a phenotyping platform. The contribution of these traits to light interception was assessed in virtual field canopies composed of 3D plant reconstructions, with a model tested in a real field. Two categories of traits had different contributions to genetic progress. (i) The vertical distribution of leaf area had a high heritability and showed a marked trend over generations of selection. Leaf area tended to be located at lower positions in the canopy, thereby improving light penetration and distribution in the canopy. This potentially increased the carbon availability to ears, via the amount of light absorbed by the intermediate canopy layer, (ii) Neither the horizontal distribution of leaves in the relation to plant rows nor the response of light interception to plant density showed appreciable trends with generations. Hence, among many architectural traits, the vertical distribution of leaf area was the main indirect target of selection.

Published
2019

38. 47-3: High Efficiency and High PPI AMOLED with Cavity Tuned by Inkjet Printed Hole Injection Layer

Author

Lee, Meng-Ting, primary, Lu, Kun-Ta, additional, Chen, Yi-Hong, additional, Lin, Kuan-Heng, additional, Chen, Wen-Pin, additional, Chen, Tsu-Wei, additional, Chen, Kuo-Kuang, additional, Lu, Hsueh-Hsing, additional, Lin, Yu-Hsin, additional, Walker, Daniel, additional, Creally, Matthew, additional, Béalle, Gaëlle, additional, Wang, Hsing-Ju, additional, Tseng, Hsin-Rong, additional, Goulding, Mark, additional, Boehm, Edgar, additional, and Buchholz, Herwig, additional

Published
2018
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39. Environmental triggers for photosynthetic protein turnover determine the optimal nitrogen distribution and partitioning in the canopy

Author

Pao, Yi-Chen, Chen, Tsu-Wei, Moualeu-Ngangue, Dany Pascal, Stütze, Hartmut, Pao, Yi-Chen, Chen, Tsu-Wei, Moualeu-Ngangue, Dany Pascal, and Stütze, Hartmut

Abstract

Plants continually adjust the photosynthetic functions in their leaves to fluctuating light, thereby optimizing the use of photosynthetic nitrogen (Nph) at the canopy level. To investigate the complex interplay between external signals during the acclimation processes, a mechanistic model based on the concept of protein turnover (synthesis and degradation) was proposed and parameterized using cucumber grown under nine combinations of nitrogen and light in growth chambers. Integrating this dynamic model into a multi-layer canopy model provided accurate predictions of photosynthetic acclimation of greenhouse cucumber canopies grown under high and low nitrogen supply in combination with day-to-day fluctuations in light at two different levels. This allowed us to quantify the degree of optimality in canopy nitrogen use for maximizing canopy carbon assimilation, which was influenced by Nph distribution along canopy depth or Nph partitioning between functional pools. Our analyses suggest that Nph distribution is close to optimum and Nph reallocation is more important under low nitrogen. Nph partitioning is only optimal under a light level similar to the average light intensity during acclimation, meaning that day-to-day light fluctuations inevitably result in suboptimal Nph partitioning. Our results provide insights into photoacclimation and can be applied to crop model improvement.

Published
2018

40. A new method to estimate photosynthetic parameters through net assimilation rate-intercellular space CO2 concentration (A-C-i) curve and chlorophyll fluorescence measurements

Author

Moualeu-Ngangue, Dany P., Chen, Tsu Wei, Stuetzel, Hartmut, Institute for Horticultural Production Systems, Vegetable Systems Modelling Section, Faculty of Natural Sciences, Gottfried Wilhelm Leibniz University of Hanover, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
fitting method, conductance epidermique, taux d'assimilation nette, chlorophyll fluorescence, estimation, cucumis sativus, photosynthèse foliaire, fluorescence chlorophyllienne, mesophyll conductance, photosynthetic parameters, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, A-Ci curves
Abstract

Gas exchange (GE) and chlorophyll fluorescence (CF) measurements are widely used to noninvasively study photosynthetic parameters, for example the rates of maximum Rubisco carboxylation (V-cmax), electron transport rate (J), daytime respiration (R-d) and mesophyll conductance (g(m)). Existing methods for fitting GE data (net assimilation rate-intercellular space CO2 concentration (A-C-i) curve) are based on two assumptions: g(m) is unvaried with CO2 concentration in the intercellular space (C-i); and light absorption () and the proportion of quanta absorbed by photosystem II () are constant in the data set. These may result in significant bias in estimating photosynthetic parameters. To avoid the above-mentioned hypotheses, we present a new method for fitting A-C-i curves and CF data simultaneously. This method was applied to a data set obtained from cucumber (Cucumis sativus) leaves of various leaf ages and grown under eight different light conditions. The new method had significantly lower root mean square error and a lower rate of failures compared with previously published methods (6.72% versus 24.1%, respectively) and the effect of light conditions on V-cmax and J was better observed. Furthermore, the new method allows the estimation of a new parameter, the fraction of incoming irradiance harvested by photosystem II, and the dependence of g(m) on C-i.

Published
2017
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41. A genome-wide approach combining field and platform phenotyping to investigate plant responses to drought and high temperatures

Author

Welcker, Claude, Millet, Emilie, Alvarez Prado, Santiago, Coupel-Ledru, Aude, Chen, Tsu Wei, Cabrera Bosquet, Llorenç, Tardieu, Francois, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
changement climatique, Vegetal Biology, scénario climatique, maïs, qtl, variabilité génétique, maize, ressource génétique, plateforme de phénotypage, genetic resources, genetic variability, région génomique, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, global change, Biologie végétale
Abstract

Natural genetic resources need to be fully explored for designing novel genotypes able to cope with climate change, with special emphasis on identification of traits and allelic sources of adaptation to drought and high temperature. We base our approach on a combination of methods involving genetic analyses in phenotyping platforms and in the field. The rationale is that a given trait or allele confers advantages for yield in specific scenarios of water deficit or high temperature, but most often not in all of these scenarios. We have explored, in a network of field experiments, a series of environmental scenarios for identifying the scenarios where a given allele has positive, negative or no effect on yield. We have then dissected these effects into responses to specific environmental conditions and their genetic variability. The latter step involves phenotyping in an automated phenotyping platform, allowing one to infer traits that are impossible to measure in the field, such as radiation use efficiency, sensitivity of growth to water deficit or stomatal control. We have applied this strategy to a panel of 250 maize hybrids allowing a multi- scale multi environment whole-genome association study. Resulting pattern of QTL effects expressed as function of environmental variables and traits can be used for assessing the performance of genotypes and the contribution of genomic regions under current and future stress situations, and for accelerating the breeding for drought-prone environments.

Published
2017

42. Image workflows for high throughput phenotyping platforms

Author

Artzet, Simon, Brichet, Nicolas, Cabrera, Llorenc, Chen, Tsu-Wei, Chopard, Jerome, Mielewczik, Michael, Fournier, Christian, Pradal, Christophe, Modeling plant morphogenesis at different scales, from genes to phenotype (VIRTUAL PLANTS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA)-Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), 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), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Godin, Christophe, Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), and Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)

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

International audience; Plant high-throughput phenotyping aims at capturing the genetic variability of plant responses to environmental factor for thousands of plants, hence identifying heritable traits for genomic selection and predicting the genetic values of allelic combinations in different environment. This first implies the automation of the measurement of a large number of traits, to characterize plant growth, plant development and plant functioning. It also requires a fluent and versatile interaction between data and continuously evolving plant response models, that are essential in the analysis of the marker x environment interaction and in the integration of processes for predicting crop performance. In the frame of the Phenome high throughput phenotyping infrastructure, we develop Phenomenal, a software collection dedicated to the analysis of high throughput phenotyping data and with models. It is based on the OpenAlea platform that provides methods and softwares for the modelling of plants, together with a user-friendly interface for the design and execution of scientific workflows. OpenAlea is also part of the InfraPhenoGrid infrastructure that allows high throughput computation and recording of provenance during the execution. Phenomenal currently consists of 2D image analysis workflows build with standard image libraries (OpenCV, Scikit Image), algorithms for 3D reconstruction, segmentation and tracking of plant organs for maize (under development), and workflows for estimation of light interception by plants during their growth. 3D models of maize architectural development (ADEL) are used to help segmenting 3D plants and automate the mapping between topological objects detected during 3D image segmentation and plant organs defined in the model. Plant models are combined with meteorological data to feed a light distribution model (RATP) and estimate light use efficiency. In the future, we plan to scale the approach to the analysis of more complex plants (wheat) and more complex images acquired in the field. We also want to automatize the connection between plant response models and the data extracted from images, to get directly an estimation of the crop performance in a large range of context.

Published
2016

43. Optimal photosynthetic nitrogen partitioning in cucumber leaves for maximizing canopy photosynthesis

Author

Pao, Y. C., Chen, Tsu Wei, Stützel, Hartmut, Leibniz University Hannover, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research, Leibniz Association (ZALF). DEU.

Subjects
Vegetal Biology, concombre, activité photosynthétique, transport d'électron, photosynthétat, teneur en azote, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, culture hydroponique, modèle de simulation, Biologie végétale, intensité lumineuse
Published
2016

44. Genetic variability in light-related parameters of maize models revealed by linking 3D-reconstruction of plant architecture with light model and phenotyping platform

Author

Chen, Tsu-Wei, Fournier, Christian, Artzet, Simon, Brichet, Nicolas, Chopard, Jérôme, Pradal, Christophe, Alvarez Prado, Santiago, Cabrera-Bosquet, Llorenç, Welcker, Claude, Tardieu, Francois, Godin, Christophe, Leibniz Universität Hannover [Hannover] (LUH), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Modeling plant morphogenesis at different scales, from genes to phenotype (VIRTUAL PLANTS), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national 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), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA)-Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Leibniz Universität Hannover=Leibniz University Hannover, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
3d reconstruction, U10 - Méthodes mathématiques et statistiques, Phenotyping, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Radiation use efficiency, F50 - Anatomie et morphologie des plantes, F30 - Génétique et amélioration des plantes, F62 - Physiologie végétale : croissance et développement
Abstract

International audience; Radiation interception efficiency (RIE) and radiation use efficiency (RUE) are the main driving forces of dry mass accumulation, so parameters related to RIE and RUE, e.g. light extinction coefficient (k) and photosynthetic parameters, have strong impacts on yields. Since these parameters are strongly related to the canopy structure, architectural traits of plants are important for characterization of the genetic variability of these parameters, a critical work for modelling the interactions between yield and environmental conditions and predicting future genetic gain. In this work, we propose a new method to estimate the RIE- and RUE-related parameters of maize for the crop models by a high-throughput phenotyping platform, PHENOARCH (https://goo.gl /x3C6oN). In autumn 2014, 330 maize lines were grown under non-stressed condition with five repetitions. For each plant, one top image and 12 side images of the plant were taken every 2-3 days. These images were used to reconstruct the 3D-architecture of the plants. To estimate RIE of a maize line on day t, the 3D plants of this line were used for constructing a virtual canopy consisting of 15 plants in three rows. Based on the architecture of this virtual canopy, RIE was calculated by the RATP light model and leaf area index (LAI) was estimated by the images analyses and the reconstructed 3D-architecture. k was obtained by computing the slope between natural logarithm of light transmittance through the canopy and LAI. Relationship between RIE and plant developmental stage was fitted to a sigmoidal function with three parameters: maximum RIE (RIEmax), maximum change of RIE (smax) and time taken to reach smax (ts). Maize lines were genotyped with 354K polymorphic SNPs and genome wide association analysis (GWAS) was performed over model parameters. Between genotypes, significant differences in k, RIEmax, smax and ts were found, ranging from 0.31-0.75 (unitless), 0.43-0.98 (unitless), 0.12-0.27 (d-1) and 18.3-39.5 (d), respectively. GWAS revealed 16 QTL for k, 77 for RIEmax, 1 for smax and 7 for ts. This study is an example of model-assisted phenotyping and we conclude that using the 3D architecture of plants reconstructed by phenotyping platform has strong potential to discover the genetic variability of light-related traits. Further possibilities include the estimation of radiation use efficiency and relative canopy photosynthetic capacity.

Published
2016

45. High-throughput phenotyping platform reveals genetic variability and quantitative trait loci of light-related parameters in maize models

Author

Chen, Tsu-Wei, Fournier, Christian, Artzet, Simon, Brichet, Nicolas, Chopard, Jérôme, Christophe Pradal, Alvarez-Prado, Santiago, Cabrera-Bosquet, Llorenç, Welcker, C., and Tardieu, François

Abstract

Radiation interception efficiency (RIE) and radiation use efficiency (RUE) are the main driving forces of dry mass accumulation in many crop models, so parameters related to RIE and RUE, e.g. light extinction coefficient (k) and photosynthetic parameters, have strong influences on the results of simulations. In this work, we propose a new method to estimate the RIE- and RUE-related parameters in maize models by a high-throughput phenotyping platform, PHENOARCH (https://goo.gl /x3C6oN), where images of 330 maize lines were taken and used to reconstruct the 3D-structure of the plants. The 3D plants were used to construct a virtual canopy to calculate RIE based on the RATP light model. Leaf area index (LAI) was estimated by the reconstructed 3D-structure and k was calculated from RIE and LAI. Relationship between RIE and plant developmental stage was fitted to a sigmoidal function with three parameters: maximum RIE (RIEmax), maximum change of RIE (smax) and time taken to reach smax (ts). Between genotypes, significant differences in k, RIEmax, smax and ts were found and genome wide association analysis revealed 16 QTL for k, 77 for RIEmax, 1 for smax and 7 for ts. Further parameters including RUE and relative canopy photosynthetic capacity can be also estimated by our method. We conclude that 3Dstructure of plants reconstructed in a phenotyping platform can be used to discover the genetic variability of lightrelated parameters for crop models.

Published
2016

46. A Modeling Approach to Quantify the Effects of Stomatal Behavior and Mesophyll Conductance on Leaf Water Use Efficiency

Author

Moualeu-Ngangue, Dany P., Chen, Tsu-Wei, Stützel, Hartmut, Leibniz University Hannover, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
stomatal behavior, Water use efficiency (WUE), Vegetal Biology, water use efficiency, conduction stomatique, fungi, mesophyll conductance, Plant Science, mésophylle, Light regulation, ddc:580, concombre, sap flow dynamics, lumière naturelle, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, ddc:500, efficience d'utilisation de l'eau, stress hydrique, photosynthèse, ensoleillement, modèle dynamique, Biologie végétale
Abstract

International audience; Water use efficiency (WUE) is considered as a determinant of yield under stress and a component of crop drought resistance. Stomatal behavior regulates both transpiration rate and net assimilation and has been suggested to be crucial for improving crop WUE. In this work, a dynamic model was used to examine the impact of dynamic properties of stomata on WUE. The model includes sub-models of stomatal conductance dynamics, solute accumulation in the mesophyll, mesophyll water content, and water flow to the mesophyll. Using the instantaneous value of stomatal conductance, photosynthesis, and transpiration rate were simulated using a biochemical model and Penman-Monteith equation, respectively. The model was parameterized for a cucumber leaf and model outputs were evaluated using climatic data. Our simulations revealed that WUE was higher on a cloudy than a sunny day. Fast stomata' reaction to light decreased WUE during the period of increasing light (e.g., in the morning) by up to 10.2% and increased WUE during the period of decreasing light (afternoon) by up to 6.25%. Sensitivity of daily WUE to stomata' parameters and mesophyll conductance to 002 was tested for sunny and cloudy days. Increasing mesophyll conductance to CO2 was more likely to increase WUE for all climatic conditions (up to 5.5% on the sunny day) than modifications of stomatal reaction speed to light and maximum stomatal conductance.

Published
2016
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48. Architectural and non-architectural effects of salinity on canopy structure, light interception and dry mass production on greenhouse cucumber and tomato

Author

Chen, Tsu-Wei

Subjects
photosynthesis, quantitative Limitierungsanalyse, Cucumber, Dewey Decimal Classification::600 | Technik::630 | Landwirtschaft, Veterinärmedizin, functional-structural plant model, Lichtnutzungseffizient, tomato, light interception, Tomate, quantitative limitation analysis, ddc:630, Gurke, light use efficiency, Lichtaufnahme, Salzstress, Photosynthese, salinity stress, funktionell-strukturelles Pflanzenmodell
Abstract

[no abstract]

Published
2015
Full Text
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49. A Modeling Approach to Quantify the Effects of Stomatal Behavior and Mesophyll Conductance on Leaf Water Use Efficiency

Author

Moualeu-Ngangue, Dany Pascal, Chen, Tsu-Wei, Stützel, Hartmut, Moualeu-Ngangue, Dany Pascal, Chen, Tsu-Wei, and Stützel, Hartmut

Abstract

Water use efficiency (WUE) is considered as a determinant of yield under stress and a component of crop drought resistance. Stomatal behavior regulates both transpiration rate and net assimilation and has been suggested to be crucial for improving crop WUE. In this work, a dynamic model was used to examine the impact of dynamic properties of stomata on WUE. The model includes sub-models of stomatal conductance dynamics, solute accumulation in the mesophyll, mesophyll water content, and water flow to the mesophyll. Using the instantaneous value of stomatal conductance, photosynthesis, and transpiration rate were simulated using a biochemical model and Penman-Monteith equation, respectively. The model was parameterized for a cucumber leaf and model outputs were evaluated using climatic data. Our simulations revealed that WUE was higher on a cloudy than a sunny day. Fast stomatal reaction to light decreased WUE during the period of increasing light (e.g., in the morning) by up to 10.2% and increased WUE during the period of decreasing light (afternoon) by up to 6.25%. Sensitivity of daily WUE to stomatal parameters and mesophyll conductance to CO2 was tested for sunny and cloudy days. Increasing mesophyll conductance to CO2 was more likely to increase WUE for all climatic conditions (up to 5.5% on the sunny day) than modifications of stomatal reaction speed to light and maximum stomatal conductance.

Published
2016

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