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https://www.readbyqxmd.com/read/28626887/using-numerical-plant-models-and-phenotypic-correlation-space-to-design-achievable-ideotypes
#1
Victor Picheny, Pierre Casadebaig, Ronan Trépos, Robert Faivre, David Da Silva, Patrick Vincourt, Evelyne Costes
Numerical plant models can predict the outcome of plant traits modifications resulting from genetic variations, on plant performance, by simulating physiological processes and their interaction with the environment. Optimization methods complement those models to design ideotypes, i.e. ideal values of a set of plant traits resulting in optimal adaptation for given combinations of environment and management, mainly through the maximization of a performance criteria (e.g. yield, light interception). As use of simulation models gains momentum in plant breeding, numerical experiments must be carefully engineered to provide accurate and attainable results, rooting them in biological reality...
June 18, 2017: Plant, Cell & Environment
https://www.readbyqxmd.com/read/28587758/epigenetics-for-plant-improvement-current-knowledge-and-modeling-avenues
#2
REVIEW
Philippe Gallusci, Zhanwu Dai, Michel Génard, Arnaud Gauffretau, Nathalie Leblanc-Fournier, Céline Richard-Molard, Denis Vile, Sophie Brunel-Muguet
Epigenetic variations are involved in the control of plant developmental processes and participate in shaping phenotypic plasticity to the environment. Intense breeding has eroded genetic diversity, and epigenetic diversity now emerge as a new source of phenotypic variations to improve adaptation to changing environments and ensure the yield and quality of crops. Here, we review how the characterization of the stability and heritability of epigenetic variations is required to drive breeding strategies, which can be assisted by process-based models...
June 3, 2017: Trends in Plant Science
https://www.readbyqxmd.com/read/28542198/optimization-of-black-box-models-with-uncertain-climatic-inputs-application-to-sunflower-ideotype-design
#3
Victor Picheny, Ronan Trépos, Pierre Casadebaig
Accounting for the interannual climatic variations is a well-known issue for simulation-based studies of environmental systems. It often requires intensive sampling (e.g., averaging the simulation outputs over many climatic series), which hinders many sequential processes, in particular optimization algorithms. We propose here an approach based on a subset selection in a large basis of climatic series, using an ad-hoc similarity function and clustering. A non-parametric reconstruction technique is introduced to estimate accurately the distribution of the output of interest using only the subset sampling...
2017: PloS One
https://www.readbyqxmd.com/read/28540573/optimization-of-multi-environment-trials-for-genomic-selection-based-on-crop-models
#4
R Rincent, E Kuhn, H Monod, F-X Oury, M Rousset, V Allard, J Le Gouis
We propose a statistical criterion to optimize multi-environment trials to predict genotype × environment interactions more efficiently, by combining crop growth models and genomic selection models. Genotype × environment interactions (GEI) are common in plant multi-environment trials (METs). In this context, models developed for genomic selection (GS) that refers to the use of genome-wide information for predicting breeding values of selection candidates need to be adapted. One promising way to increase prediction accuracy in various environments is to combine ecophysiological and genetic modelling thanks to crop growth models (CGM) incorporating genetic parameters...
May 24, 2017: TAG. Theoretical and Applied Genetics. Theoretische und Angewandte Genetik
https://www.readbyqxmd.com/read/28536708/performance-of-sorghum-varieties-under-variable-rainfall-in-central-tanzania
#5
Barnabas M Msongaleli, S D Tumbo, N I Kihupi, Filbert B Rwehumbiza
Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties...
2017: International Scholarly Research Notices
https://www.readbyqxmd.com/read/28536585/exploring-niches-for-short-season-grain-legumes-in-semi-arid-eastern-kenya-coping-with-the-impacts-of-climate-variability
#6
Anne Sennhenn, Donald M G Njarui, Brigitte L Maass, Anthony M Whitbread
Climate variability is the major risk to agricultural production in semi-arid agroecosystems and the key challenge to sustain farm livelihoods for the 500 million people who inhabit these areas worldwide. Short-season grain legumes have great potential to address this challenge and help to design more resilient and productive farming systems. However, grain legumes display a great diversity and differ widely in growth, development, and resource use efficiency. Three contrasting short season grain legumes common bean (Phaseolus vulgaris L...
2017: Frontiers in Plant Science
https://www.readbyqxmd.com/read/28418069/genetic-control-of-plasticity-of-oil-yield-for-combined-abiotic-stresses-using-a-joint-approach-of-crop-modeling-and-genome-wide-association
#7
Brigitte Mangin, Pierre Casadebaig, Eléna Cadic, Nicolas Blanchet, Marie-Claude Boniface, Sébastien Carrère, Jérôme Gouzy, Ludovic Legrand, Baptiste Mayjonade, Nicolas Pouilly, Thierry André, Marie Coque, Joël Piquemal, Marion Laporte, Patrick Vincourt, Stéphane Muños, Nicolas B Langlade
Understanding the genetic basis of phenotypic plasticity is crucial for predicting and managing climate change effects on wild plants and crops. Here, we combined crop modeling and quantitative genetics to study the genetic control of oil yield plasticity for multiple abiotic stresses in sunflower. First we developed stress indicators to characterize 14 environments for three abiotic stresses (cold, drought and nitrogen) using the SUNFLO crop model and phenotypic variations of three commercial varieties. The computed plant stress indicators better explain yield variation than descriptors at the climatic or crop levels...
April 18, 2017: Plant, Cell & Environment
https://www.readbyqxmd.com/read/28389147/contribution-of-crop-models-to-adaptation-in-wheat
#8
REVIEW
Karine Chenu, John Roy Porter, Pierre Martre, Bruno Basso, Scott Cameron Chapman, Frank Ewert, Marco Bindi, Senthold Asseng
With world population growing quickly, agriculture needs to produce more with fewer inputs while being environmentally friendly. In a context of changing environments, crop models are useful tools to simulate crop yields. Wheat (Triticum spp.) crop models have been evolving since the 1960s to translate processes related to crop growth and development into mathematical equations. These have been used over decades for agronomic purposes, and have more recently incorporated advances in the modeling of environmental footprints, biotic constraints, trait and gene effects, climate change impact, and the upscaling of global change impacts...
June 2017: Trends in Plant Science
https://www.readbyqxmd.com/read/28386178/support-vector-machine-based-open-crop-model-sbocm-case-of-rice-production-in-china
#9
Ying-Xue Su, Huan Xu, Li-Jiao Yan
Existing crop models produce unsatisfactory simulation results and are operationally complicated. The present study, however, demonstrated the unique advantages of statistical crop models for large-scale simulation. Using rice as the research crop, a support vector machine-based open crop model (SBOCM) was developed by integrating developmental stage and yield prediction models. Basic geographical information obtained by surface weather observation stations in China and the 1:1000000 soil database published by the Chinese Academy of Sciences were used...
March 2017: Saudi Journal of Biological Sciences
https://www.readbyqxmd.com/read/28384568/combination-of-a-crop-model-and-a-geochemical-model-as-a-new-approach-to-evaluate-the-sustainability-of-an-intensive-agriculture-system
#10
Gihan Mohammed, Fabienne Trolard, Marina Gillon, Anne-Laure Cognard-Plancq, André Chanzy, Guilhem Bourrié
By combining a crop model (STICS) and a geochemical model (PHREEQC), a new approach to assess the sustainability of agrosystems is proposed. It is based upon aqueous geochemistry and the stepwise modifications of soil solution during its transfer from the surface till aquifer. Meadows of Crau (SE France), irrigated since the 16th century, were field monitored (2012-2015) and modelled. Except for N, the mineral requirements of hay are largely covered by dissolved elements brought by irrigation water with only slight deficits in K and P, which are compensated by P-K fertilizers and the winter pasture by sheep...
October 1, 2017: Science of the Total Environment
https://www.readbyqxmd.com/read/28379522/can-increased-leaf-photosynthesis-be-converted-into-higher-crop-mass-production-a-simulation-study-for-rice-using-the-crop-model-gecros
#11
Xinyou Yin, Paul C Struik
Various genetic engineering routes to enhance C3 leaf photosynthesis have been proposed to improve crop productivity. However, their potential contribution to crop productivity needs to be assessed under realistic field conditions. Using 31 year weather data, we ran the crop model GECROS for rice in tropical, subtropical, and temperate environments, to evaluate the following routes: (1) improving mesophyll conductance (gm); (2) improving Rubisco specificity (Sc/o); (3) improving both gm and Sc/o; (4) introducing C4 biochemistry; (5) introducing C4 Kranz anatomy that effectively minimizes CO2 leakage; (6) engineering the complete C4 mechanism; (7) engineering cyanobacterial bicarbonate transporters; (8) engineering a more elaborate cyanobacterial CO2-concentrating mechanism (CCM) with the carboxysome in the chloroplast; and (9) a mechanism that combines the low ATP cost of the cyanobacterial CCM and the high photosynthetic capacity per unit leaf nitrogen...
April 1, 2017: Journal of Experimental Botany
https://www.readbyqxmd.com/read/28377779/bioenergy-sorghum-crop-model-predicts-vpd-limited-transpiration-traits-enhance-biomass-yield-in-water-limited-environments
#12
Sandra K Truong, Ryan F McCormick, John E Mullet
Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes...
2017: Frontiers in Plant Science
https://www.readbyqxmd.com/read/28184227/using-ceres-maize-and-enso-as-decision-support-tools-to-evaluate-climate-sensitive-farm-management-practices-for-maize-production-in-the-northern-regions-of-ghana
#13
Dilys S MacCarthy, Samuel G K Adiku, Bright S Freduah, Francis Gbefo, Alpha Y Kamara
Maize (Zea mays) has traditionally been a major cereal staple in southern Ghana. Through breeding and other crop improvement efforts, the zone of cultivation of maize has now extended to the northern regions of Ghana which, hitherto, were the home to sorghum and millet as the major cereals. Maize yield in the northern Ghana is hampered by three major biophysical constraints, namely, poor soil fertility, low soil water storage capacity and climate variability. In this study we used the DSSAT crop model to assess integrated water and soil management strategies that combined the pre-season El-Niño-Southern Oscillation (ENSO)-based weather forecasting in selecting optimal planting time, at four locations in the northern regions of Ghana...
2017: Frontiers in Plant Science
https://www.readbyqxmd.com/read/28158204/atmospheric-co2-concentration-effects-on-rice-water-use-and-biomass-production
#14
Uttam Kumar, William Paul Quick, Marilou Barrios, Pompe C Sta Cruz, Michael Dingkuhn
Numerous studies have addressed effects of rising atmospheric CO2 concentration on rice biomass production and yield but effects on crop water use are less well understood. Irrigated rice evapotranspiration (ET) is composed of floodwater evaporation and canopy transpiration. Crop coefficient Kc (ET over potential ET, or ETo) is crop specific according to FAO, but may decrease as CO2 concentration rises. A sunlit growth chamber experiment was conducted in the Philippines, exposing 1.44-m2 canopies of IR72 rice to four constant CO2 levels (195, 390, 780 and 1560 ppmv)...
2017: PloS One
https://www.readbyqxmd.com/read/28134461/responses-to-atmospheric-co2-concentrations-in-crop-simulation-models-a-review-of-current-simple-and-semicomplex-representations-and-options-for-model-development
#15
REVIEW
Eline Vanuytrecht, Peter J Thorburn
Elevated atmospheric CO2 concentrations ([CO2 ]) cause direct changes in crop physiological processes (e.g. photosynthesis and stomatal conductance). To represent these CO2 responses, commonly used crop simulation models have been amended, using simple and semicomplex representations of the processes involved. Yet, there is no standard approach to and often poor documentation of these developments. This study used a bottom-up approach (starting with the APSIM framework as case study) to evaluate modelled responses in a consortium of commonly used crop models and illuminate whether variation in responses reflects true uncertainty in our understanding compared to arbitrary choices of model developers...
May 2017: Global Change Biology
https://www.readbyqxmd.com/read/28124255/the-primary-root-of-sorghum-bicolor-l-moench-as-a-model-system-to-study-brassinosteroid-signaling-in-crops
#16
David Blasco-Escámez, Fidel Lozano-Elena, Norma Fàbregas, Ana I Caño-Delgado
Roots anchor plants to the soil and are essential for a successful plant growth and adaptation to the environment. Research on the primary root in the plant model system Arabidopsis thaliana has yielded important advances in the molecular and cellular understanding of root growth and development. Several studies have uncovered how the hormones brassinosteroids (BRs) control cell cycle and differentiation programs through different cell-specific signaling pathways that are key for root growth and development...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28102202/consistent-negative-response-of-us-crops-to-high-temperatures-in-observations-and-crop-models
#17
Bernhard Schauberger, Sotirios Archontoulis, Almut Arneth, Juraj Balkovic, Philippe Ciais, Delphine Deryng, Joshua Elliott, Christian Folberth, Nikolay Khabarov, Christoph Müller, Thomas A M Pugh, Susanne Rolinski, Sibyll Schaphoff, Erwin Schmid, Xuhui Wang, Wolfram Schlenker, Katja Frieler
High temperatures are detrimental to crop yields and could lead to global warming-driven reductions in agricultural productivity. To assess future threats, the majority of studies used process-based crop models, but their ability to represent effects of high temperature has been questioned. Here we show that an ensemble of nine crop models reproduces the observed average temperature responses of US maize, soybean and wheat yields. Each day >30 °C diminishes maize and soybean yields by up to 6% under rainfed conditions...
January 19, 2017: Nature Communications
https://www.readbyqxmd.com/read/27991912/plausible-rice-yield-losses-under-future-climate-warming
#18
Chuang Zhao, Shilong Piao, Xuhui Wang, Yao Huang, Philippe Ciais, Joshua Elliott, Mengtian Huang, Ivan A Janssens, Tao Li, Xu Lian, Yongwen Liu, Christoph Müller, Shushi Peng, Tao Wang, Zhenzhong Zeng, Josep Peñuelas
Rice is the staple food for more than 50% of the world's population(1-3). Reliable prediction of changes in rice yield is thus central for maintaining global food security. This is an extraordinary challenge. Here, we compare the sensitivity of rice yield to temperature increase derived from field warming experiments and three modelling approaches: statistical models, local crop models and global gridded crop models. Field warming experiments produce a substantial rice yield loss under warming, with an average temperature sensitivity of -5...
December 19, 2016: Nature Plants
https://www.readbyqxmd.com/read/27891133/modeling-long-term-corn-yield-response-to-nitrogen-rate-and-crop-rotation
#19
Laila A Puntel, John E Sawyer, Daniel W Barker, Ranae Dietzel, Hanna Poffenbarger, Michael J Castellano, Kenneth J Moore, Peter Thorburn, Sotirios V Archontoulis
Improved prediction of optimal N fertilizer rates for corn (Zea mays L.) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean (Glycine max L.) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha(-1)) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N...
2016: Frontiers in Plant Science
https://www.readbyqxmd.com/read/27864754/tips-and-tricks-for-exogenous-application-of-synthetic-post-translationally-modified-peptides-to-plants
#20
Nathan Czyzewicz, Elisabeth Stes, Ive De Smet
The first signaling peptide discovered and purified was insulin in 1921. However, it was not until 1991 that the first peptide signal, systemin, was discovered in plants. Since the discovery of systemin, peptides have emerged as a potent and diverse class of signaling molecules in plant systems. Peptides consist of small amino acid sequences, which often act as ligands of receptor kinases. However, not all peptides are created equal, and signaling peptides are grouped into several subgroups dependent on the type of post-translational processing they undergo...
2017: Methods in Molecular Biology
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