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https://www.readbyqxmd.com/read/28714956/the-uncertainty-of-crop-yield-projections-is-reduced-by-improved-temperature-response-functions
#1
Enli Wang, Pierre Martre, Zhigan Zhao, Frank Ewert, Andrea Maiorano, Reimund P Rötter, Bruce A Kimball, Michael J Ottman, Gerard W Wall, Jeffrey W White, Matthew P Reynolds, Phillip D Alderman, Pramod K Aggarwal, Jakarat Anothai, Bruno Basso, Christian Biernath, Davide Cammarano, Andrew J Challinor, Giacomo De Sanctis, Jordi Doltra, Elias Fereres, Margarita Garcia-Vila, Sebastian Gayler, Gerrit Hoogenboom, Leslie A Hunt, Roberto C Izaurralde, Mohamed Jabloun, Curtis D Jones, Kurt C Kersebaum, Ann-Kristin Koehler, Leilei Liu, Christoph Müller, Soora Naresh Kumar, Claas Nendel, Garry O'Leary, Jørgen E Olesen, Taru Palosuo, Eckart Priesack, Ehsan Eyshi Rezaei, Dominique Ripoche, Alex C Ruane, Mikhail A Semenov, Iurii Shcherbak, Claudio Stöckle, Pierre Stratonovitch, Thilo Streck, Iwan Supit, Fulu Tao, Peter Thorburn, Katharina Waha, Daniel Wallach, Zhimin Wang, Joost Wolf, Yan Zhu, Senthold Asseng
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...
July 17, 2017: Nature Plants
https://www.readbyqxmd.com/read/28710999/recent-changes-in-county-level-corn-yield-variability-in-the-united-states-from-observations-and-crop-models
#2
Guoyong Leng
The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions...
July 11, 2017: Science of the Total Environment
https://www.readbyqxmd.com/read/28702039/ceres-maize-model-for-determining-the-optimum-planting-dates-of-early-maturing-maize-varieties-in-northern-nigeria
#3
Adnan A Adnan, Jibrin M Jibrin, Alpha Y Kamara, Bassam L Abdulrahman, Abdulwahab S Shaibu, Ismail I Garba
Field trials were carried out in the Sudan Savannah of Nigeria to assess the usefulness of CERES-maize crop model as a decision support tool for optimizing maize production through manipulation of plant dates. The calibration experiments comprised of 20 maize varieties planted during the dry and rainy seasons of 2014 and 2015 at Bayero University Kano and Audu Bako College of Agriculture Dambatta. The trials for model evaluation were conducted in 16 different farmer fields across the Sudan (Bunkure and Garun-Mallam) and Northern Guinea (Tudun-Wada and Lere) Savannas using two of the calibrated varieties under four different sowing dates...
2017: Frontiers in Plant Science
https://www.readbyqxmd.com/read/28701815/next-generation-crop-models-a-modular-approach-to-model-early-vegetative-and-reproductive-development-of-the-common-bean-phaseolus-vulgaris-l
#4
C Hwang, M J Correll, S A Gezan, L Zhang, M S Bhakta, C E Vallejos, K J Boote, J A Clavijo-Michelangeli, J W Jones
The next generation of gene-based crop models offers the potential of predicting crop vegetative and reproductive development based on genotype and weather data as inputs. Here, we illustrate an approach for developing a dynamic modular gene-based model to simulate changes in main stem node numbers, time to first anthesis, and final node number on the main stem of common bean (Phaseolus vulgaris L.). In the modules, these crop characteristics are functions of relevant genes (quantitative trait loci (QTL)), the environment (E), and QTL × E interactions...
July 2017: Agricultural Systems
https://www.readbyqxmd.com/read/28701814/modelling-the-impacts-of-pests-and-diseases-on-agricultural-systems
#5
M Donatelli, R D Magarey, S Bregaglio, L Willocquet, J P M Whish, S Savary
The improvement and application of pest and disease models to analyse and predict yield losses including those due to climate change is still a challenge for the scientific community. Applied modelling of crop diseases and pests has mostly targeted the development of support capabilities to schedule scouting or pesticide applications. There is a need for research to both broaden the scope and evaluate the capabilities of pest and disease models. Key research questions not only involve the assessment of the potential effects of climate change on known pathosystems, but also on new pathogens which could alter the (still incompletely documented) impacts of pests and diseases on agricultural systems...
July 2017: Agricultural Systems
https://www.readbyqxmd.com/read/28672243/evidence-for-a-weakening-strength-of-temperature-corn-yield-relation-in-the-united-states-during-1980-2010
#6
Guoyong Leng
Temperature is known to be correlated with crop yields, causing reduction of crop yield with climate warming without adaptations or CO2 fertilization effects. The historical temperature-crop yield relation has often been used for informing future changes. This relationship, however, may change over time following alternations in other environmental factors. Results show that the strength of the relationship between the interannual variability of growing season temperature and corn yield (RGST_CY) has declined in the United States between 1980 and 2010 with a loss in the statistical significance...
June 30, 2017: Science of the Total Environment
https://www.readbyqxmd.com/read/28659583/trait-based-model-development-to-support-breeding-programs-a-case-study-for-salt-tolerance-and-rice
#7
Livia Paleari, Ermes Movedi, Roberto Confalonieri
Eco-physiological models are increasingly used to analyze G × E × M interactions to support breeding programs via the design of ideotypes for specific contexts. However, available crop models are only partly suitable for this purpose, since they often lack clear relationships between parameters and traits breeders are working on. Taking salt stress tolerance and rice as a case study, we propose a paradigm shift towards the building of ideotyping-specific models explicitly around traits involved in breeding programs...
June 28, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28626887/using-numerical-plant-models-and-phenotypic-correlation-space-to-design-achievable-ideotypes
#8
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
#9
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...
July 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
#10
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
#11
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...
August 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
#12
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
#13
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
#14
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
#15
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
#16
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
#17
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
#18
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
#19
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
#20
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
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