Integrating Plant Science and Crop Modeling: Assessment of the Impact of Climate Change on Soybean and Maize Production

CSM-CROPGRO model to simulate safflower phenological development and yield

Crop simulation models are valuable tools for decision making regarding evaluation and crop improvement under different field conditions. CSM-CROPGRO model integrates genotype, environment and crop management portfolios to simulate growth, development and yield. Modeling the safflower response to varied climate regimes are needed to strengthen its productivity dynamics. The main objective of the study was to evaluate the performance of DSSAT-CSM-CROPGRO-Safflower (Version 4.8.2) under diverse climatic conditions. The model was calibrated using the field observations for phenology, biomass and safflower grain yield (SGY) of the year 2016-17. Estimation of genetic coefficients was performed using GLUE (Genetic Likelihood Uncertainty Estimation) program. Simulated results for days to flowering, maturity, biomass at flowering and maturity and SGY were predicted reasonably with good statistical indices. Model evaluation results elucidate phenological events with low root mean square error (6.32 and 6.52) and high d-index (0.95 and 0.96) for days to flowering and maturity respectively for all genotypes and climate conditions. Fair prediction of safflower biomass at flowering and maturity showed low RMSE (887.3 and 564.3 kg ha-1) and high d-index (0.67 and 0.93) for the studied genotypes across the environments. RMSE for validated safflower grain yield (101.8 kg ha-1) and d-index (0.95) depicted that model outperformed for all genotypes and growing conditions. Longer appropriate growing conditions at NARC-Islamabad took optimal duration to assimilate photosynthetic products lead to higher grain yield. Safflower resilience to different environments showed that it can be used as an alternate crop for different agroecological regions. Furthermore, CROPGRO-Safflower model can be used as tool to further evaluate inclusion of safflower in the existing cropping systems of studied regions.

Climate-based variability in the essential fatty acid composition of soybean oil

BACKGROUND

Soybean oil is a major dietary source of the essential fatty acids linoleic acid (LA) and α-linolenic acid (ALA); however, high-daytime temperatures during seed development reduce desaturase activity in soybeans. The resultant reduction in LA and ALA levels is a phenomenon well-known to soybean breeders, although the impact of this interaction between plants and environment on human nutrition is poorly understood.

OBJECTIVES

Using data from the literature, we developed a model for soybean essential fatty acid composition. Combining this model with contemporary agricultural and meteorological data sets, we determined whether insufficiency of essential fatty acids could result from geographic, intrayear, or interyear variability.

METHODS

We modeled this change using 233 data points from 16 studies that provided fatty acid composition data from plants grown under daytime high temperatures ranging from 15°C to 40°C.

RESULTS

As temperature increased, LA and ALA concentrations decreased from 55% to 30% and 13% to 3.5%, respectively. Application of the model to daytime high temperatures from 2 growth periods over 6 y showed significant regional, interyear, and intrayear variation in essential fatty acid content (P < 0.05). Using county yield data, we developed oil fatty acid models for the 3 top-producing regions of the United States. From this work, it was determined that soybean oil manufactured from soybeans in the southern United States may contain insufficient ALA to meet human nutritional needs because of high-daytime temperatures.

CONCLUSIONS

This work suggests that climate-based variation may result in many human populations not achieving an adequate daily intake of ALA.

MaxEnt model strategies to studying current and future potential land suitability dynamics of wheat, soybean and rice cultivation under climatic change scenarios in East Asia

Climate change and variability are projected to alter the geographic suitability of lands for crops cultivation. Accurately predicting changes in the potential current and future land suitability distribution dynamics of wheat (Triticum aestivum), soybean (Glycine max) and rice (Oryza sativa) crops due to climate change scenarios is critical to adapting and mitigating the impacts of bioclimatic changes, and plays a significant role in securing food security in East Asia region. This study compiled large datasets of wheat, soybean and rice occurrence locations from GBIF and 19 bioclimatic variables obtained from the WorldClim database that affect crops growth. We recognized potential future suitable distribution regions for crops under the one socioeconomic pathway, (SSP585) for 2021-2040 and 2041-2060, using the MaxEnt model. The accuracy of the MaxEnt was highly significant with mean AUC values ranging from 0.833 to 0.882 for all models evaluated. The jackknife test revealed that for wheat, Bio4 and Bio12 contributed 17.6% and 12.6%, for soybean Bio10 and Bio12 contributed 15.6% and 49.5%, while for rice Bio12 and Bio14 contributed 12.9% and 36.0% to the MaxEnt model. In addition, cultivation aptitude for wheat, soybean, and rice increased in southeast China, North Korea, South Korea, and Japan, while decreasing in Mongolia and northwest China. Climate change is expected to increase the high land suitability for wheat, soybean, and rice in East Asia. Simulation results indicate an average decrease of unsuitable areas of -98.5%, -41.2% and -36.3% for wheat, soybean and rice from 2060 than that of current land suitability. In contrast, the high land suitable for wheat, soybean and rice cultivation is projected to increase by 75.1%, 68.5% and 81.9% from 2060 as compared with current. The findings of this study are of utmost importance in the East Asia region as they present an opportunity for policy makers to develop appropriate adaptation and mitigation strategies required to sustain crops distribution under future climates. Although the risks of wheat, soybean and rice cultivation may be significantly higher in the future because of high temperatures, heat waves, and droughts caused by climate change.

Climate trends and soybean production since 1970 in Mississippi: Empirical evidence from ARDL model

Studying historical response of crops to weather conditions at a finer scale is essential for devising agricultural strategies tailored to expected climate changes. However, determining the relationship between crop and climate in Mississippi (MS) remains elusive. Therefore, this research attempted to i) estimate climate trends between 1970 and 2020 in MS during the soybean growing season (SGS) using the Mann-Kendall and Sen slope method, ii) calculate the impact of climate change on soybean yield using an auto-regressive distributive lag (ARDL) econometric model, and iii) identify the most critical months from a crop-climate perspective by generating a correlation between the detrended yield and the monthly average for each climatic variable. Specific variables considered were maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), precipitation (PT), carbon dioxide emissions (CO2), and relative humidity (RH). All required diagnostic-tests i.e., pre-analysis, post-analysis, model-sensitivity, and assessing the models' goodness-of-fit were performed and statistical standards were met. A positive trend in Tmin (+0.25 °C/decade), and a negative trend in DTR (-0.18 °C/decade) was found. Although Tmax, PT, and RH showed non-significant trends, numerical changes were noted as +0.11 °C/decade, +3.03 mm/decade, and -0.06 %/decade, respectively. Furthermore, soybean yield was positively correlated with Tmin (in June and September), PT (in July and August), and RH (in July), but negatively correlated with Tmax (in July and August) and DTR (in June, July, and August). Soybean yield was observed to be significantly reduced by 18.11 % over the long-term and by 5.51 % over the short-term for every 1 °C increase in Tmax. With every unit increase in Tmin and CO2 emissions, the yield of soybeans increased significantly by 7.76 % and 3.04 %, respectively. Altogether, soybeans in MS exhibited variable sensitivity to short- and long-terms climatic changes. The results highlight the importance of testing climate-resilient agronomic practices and cultivars that encompass asymmetric sensitivities in response to climatic conditions of MS.

Building soil to reduce climate change impacts on global crop yield

Improving soil health and resilience is fundamental for sustainable food production, however the role of soil in maintaining or improving global crop productivity under climate warming is not well identified and quantified. Here, we examined the impact of soil on yield response to climate warming for four major crops (i.e., maize, wheat, rice and soybean), using global-scale datasets and random forest method. We found that each °C of warming reduced global yields of maize by 3.4%, wheat by 2.4%, rice by 0.3% and soybean by 5.0%, which were spatially heterogeneous with possible positive impacts. The random forest modeling analyses further showed that soil organic carbon (SOC), as an indicator of soil quality, dominantly explained the spatial heterogeneity of yield responses to warming and would regulate the negative warming responses. Improving SOC under the medium SOC sequestration scenario would reduce the warming-induced yield loss of maize, wheat, rice and soybean to 0.1% °C-1, 2.7% °C-1, 3.4% °C-1 and - 0.6% °C-1, respectively, avoiding an average of 3%-5% °C-1 of global yield loss. These yield benefits would occur on 53.2%, 67.8%, 51.8% and 71.6% of maize, wheat, rice and soybean planting areas, respectively, with particularly pronounced benefits in the regions with negative warming responses. With improved soil carbon, food systems are predicted to provide additional 20 to over 130 million tonnes of food that would otherwise lose due to future warming. Our findings highlight the critical role of soil in alleviating negative warming impacts on food security, especially for developing regions, given that sustainable actions on soil improvement could be taken broadly.

Crop/Plant Modeling Supports Plant Breeding: I. Optimization of Environmental Factors in Accelerating Crop Growth and Development for Speed Breeding

The environmental conditions in customered speed breeding practice are, to some extent, empirical and, thus, can be further optimized. Crop and plant models have been developed as powerful tools in predicting growth and development under various environments for extensive crop species. To improve speed breeding, crop models can be used to predict the phenotypes resulted from genotype by environment by management at the population level, while plant models can be used to examine 3-dimensional plant architectural development by microenvironments at the organ level. By justifying the simulations via numerous virtual trials using models in testing genotype × environment × management, an optimized combination of environmental factors in achieving desired plant phenotypes can be quickly determined. Artificial intelligence in assisting for optimization is also discussed. We admit that the appropriate modifications on modeling algorithms or adding new modules may be necessary in optimizing speed breeding for specific uses. Overall, this review demonstrates that crop and plant models are promising tools in providing the optimized combinations of environment factors in advancing crop growth and development for speed breeding.

The impact of climate change on maize chemical defenses

Climate change is increasingly affecting agriculture, both at the levels of crops themselves, and by altering the distribution and damage caused by insect or microbial pests. As global food security depends on the reliable production of major crops such as maize (Zea mays), it is vital that appropriate steps are taken to mitigate these negative impacts. To do this a clear understanding of what the impacts are and how they occur is needed. This review focuses on the impact of climate change on the production and effectiveness of maize chemical defenses, including volatile organic compounds, terpenoid phytoalexins, benzoxazinoids, phenolics, and flavonoids. Drought, flooding, heat stress, and elevated concentrations of atmospheric carbon dioxide, all impact the production of maize chemical defenses, in a compound and tissue-specific manner. Furthermore, changes in stomatal conductance and altered soil conditions caused by climate change can impact environmental dispersal and effectiveness certain chemicals. This can alter both defensive barrier formation and multitrophic interactions. The production of defense chemicals is controlled by stress signaling networks. The use of similar networks to co-ordinate the response to abiotic and biotic stress can lead to complex integration of these networks in response to the combinatorial stresses that are likely to occur in a changing climate. The impact of multiple stressors on maize chemical defenses can therefore be different from the sum of the responses to individual stressors and challenging to predict. Much work remains to effectively leverage these protective chemicals in climate-resilient maize.

Prolonged low temperature exposure de-sensitises ABA-induced stomatal closure in soybean, involving an ethylene-dependent process

Chilling can decrease stomatal sensitivity to abscisic acid (ABA) in some legumes, although hormonal mechanisms involved are unclear. After evaluating leaf gas exchange of 16 European soybean genotypes at 14°C, 6 genotypes representing the range of response were selected. Further experiments combined low (L, 14°C) and high (H, 24°C) temperature exposure from sowing until the unifoliate leaf was visible and L or H temperature until full leaf expansion, to impose four temperature treatments: LL, LH, HL, and HH. Prolonged chilling (LL) substantially decreased leaf water content but increased leaf ethylene evolution and foliar concentrations of the ethylene precursor 1-aminocyclopropane-1-carboxylic acid, indole-3-acetic acid, ABA and jasmonic acid. Across genotypes, photosynthesis linearly increased with stomatal conductance (Gs), with photosynthesis of HH plants threefold higher than LL plants at the same Gs. In all treatments except LL, Gs declined with foliar ABA accumulation. Foliar ABA sprays substantially decreased Gs of HH plants, but did not significantly affect LL plants. Thus low temperature compromised stomatal sensitivity to endogenous and exogenous ABA. Applying the ethylene antagonist 1 methyl-cyclopropene partially reverted excessive stomatal opening of LL plants. Thus, chilling-induced ethylene accumulation may mediate stomatal insensitivity to ABA, offering chemical opportunities for improving seedling survival in cold environments.

Maintenance of grafting reducing cadmium accumulation in soybean (Glycinemax) is mediated by DNA methylation

Cadmium (Cd) pollution in farmland soil increases the probability of wastage of land resources and compromised food safety. Grafting can change the absorption rates of elements in crops; however, there are few studies on grafting in bulk grain and cash crops. In this study, Glycine max was used as a scion and Luffa aegyptiaca as a rootstock for grafting experiments. The changes in total sulfur and Cd content in the leaves and grains of grafted species were determined for three consecutive generations, and the gene expression and DNA methylation status of the leaves were analyzed. The results show that grafting significantly reduced the total sulfur and Cd content in soybean leaves and grains; the Cd content in soybean leaves and grains decreased by >50 %. The plant's primary sulfur metabolism pathway was not significantly affected. Glucosinolates and DNA methylation may play important roles in reducing total sulfur and Cd accumulation. Notably, low sulfur and low Cd traits can be maintained over two generations. Our study establishes that grafting can reduce the total sulfur and Cd content in soybean, and these traits can be inherited. In summary, grafting technology can be used to prevent soybean from accumulating Cd in farmland soil. This provides a theoretical basis for grafting to cultivate crops with low Cd accumulation.

Distribution characteristics of climate potential productivity of soybean in frigid region and its response to climate change

The scope of this study is to analyze the climatic potential productivity of soybean [Glycine max (L.) Merr.] and explore the impact of climate change on soybean in the frigid region in China by using daily climatic variables from 144 meteorological stations for the period 1971‒2019. The gradually descending model is used to estimate photosynthesis, light-temperature, and climatic potential productivity of soybean. The results show that climate potential productivity of soybean in the frigid region ranges from large to small: Liaoning > Jilin > Heilongjiang > East Four Leagues (four cities in eastern Inner Mongolia), with Heilongjiang and East Four Leagues showing a significant upward trend. Spatially, the climate potential productivity is larger on plains than that on mountains. The Northeast Plain and Sanjiang Plain are areas with high climate potential productivity. Changes in climatic factors have different impacts on the climate potential productivity of soybean. The influence of temperature changes on the climate potential productivity shows a positive effect, and climate warming compensates for the lack of heat in the frigid region. Furthermore, radiation and precipitation are the main climatic factors leading to spatial differences in the climate potential productivity of soybean in the frigid region. Radiation changes have a positive effect on soybean climate potential productivity in plain areas and a negative effect on the mountains. However, precipitation reduction negatively affects most of the frigid region, while it has a positive effect on the two plains of Heilongjiang. Precipitation responses the needs of soybean growth. Our findings recommend that a transition of soybean planting from the mountainous region to plain, that is, from low potential productivity areas to high potential productivity areas, could be an effective strategy for regional optimization for planting structure and rational utilization of irrigation technology.

The Modification of Circadian Clock Components in Soybean During Domestication and Improvement

Agricultural production is greatly dependent on daylength, which is determined by latitude. Living organisms align their physiology to daylength through the circadian clock, which is made up of input sensors, core and peripheral clock components, and output. The light/dark cycle is the major input signal, moderated by temperature fluctuations and metabolic changes. The core clock in plants functions mainly through a number of transcription feedback loops. It is known that the circadian clock is not essential for survival. However, alterations in the clock components can lead to substantial changes in physiology. Thus, these clock components have become the de facto targets of artificial selection for crop improvement during domestication. Soybean was domesticated around 5,000 years ago. Although the circadian clock itself is not of particular interest to soybean breeders, specific alleles of the circadian clock components that affect agronomic traits, such as plant architecture, sensitivity to light/dark cycle, flowering time, maturation time, and yield, are. Consequently, compared to their wild relatives, cultivated soybeans have been bred to be more adaptive and productive at different latitudes and habitats for acreage expansion, even though the selection processes were made without any prior knowledge of the circadian clock. Now with the advances in comparative genomics, known modifications in the circadian clock component genes in cultivated soybean have been found, supporting the hypothesis that modifications of the clock are important for crop improvement. In this review, we will summarize the known modifications in soybean circadian clock components as a result of domestication and improvement. In addition to the well-studied effects on developmental timing, we will also discuss the potential of circadian clock modifications for improving other aspects of soybean productivity.

Life-Course Monitoring of Endogenous Phytohormone Levels under Field Conditions Reveals Diversity of Physiological States among Barley Accessions

Agronomically important traits often develop during the later stages of crop growth as consequences of various plant-environment interactions. Therefore, the temporal physiological states that change and accumulate during the crop's life course can significantly affect the eventual phenotypic differences in agronomic traits among crop varieties. Thus, to improve productivity, it is important to elucidate the associations between temporal physiological responses during the growth of different crop varieties and their agronomic traits. However, data representing the dynamics and diversity of physiological states in plants grown under field conditions are sparse. In this study, we quantified the endogenous levels of five phytohormones - auxin, cytokinins (CKs), ABA, jasmonate and salicylic acid - in the leaves of eight diverse barley (Hordeum vulgare) accessions grown under field conditions sampled weekly over their life course to assess the ongoing fluctuations in hormone levels in the different accessions under field growth conditions. Notably, we observed enormous changes over time in the development-related plant hormones, such as auxin and CKs. Using 3' RNA-seq-based transcriptome data from the same samples, we investigated the expression of barley genes orthologous to known hormone-related genes of Arabidopsis throughout the life course. These data illustrated the dynamics and diversity of the physiological states of these field-grown barley accessions. Together, our findings provide new insights into plant-environment interactions, highlighting that there is cultivar diversity in physiological responses during growth under field conditions.

Flowering time control in rice by introducing Arabidopsis clock-associated PSEUDO-RESPONSE REGULATOR 5

Plants flower under appropriate day-length conditions by integrating temporal information provided by the circadian clock with light and dark information from the environment. A sub-group of plant specific circadian clock-associated PSEUDO-RESPONSE REGULATOR (PRR) genes (PRR7/PRR3 sub-group) controls flowering time both in long-day and short-day plants; however, flowering control by the other two PRR gene sub-groups has been reported only in Arabidopsis thaliana (Arabidopsis), a model long-day plant. Here, we show that an Arabidopsis PRR9/PRR5 sub-group gene can control flowering time (heading date) in rice, a short-day plant. Although PRR5 promotes flowering in Arabidopsis, transgenic rice overexpressing Arabidopsis PRR5 caused late flowering. Such transgenic rice plants produced significantly higher biomass, but not grain yield, due to the late flowering. Concomitantly, expression of Hd3a, a rice florigen gene, was reduced in the transgenic rice.Abbreviations: CCT: CONSTANS, CONSTANS-LIKE, and TOC1; HD: HEADING DATE; LHY: LATE ELONGATED HYPOCOTYL; Ppd: photoperiod; PR: pseudo-receiver; PRR: PSEUDO-RESPONSE REGULATOR; TOC1: TIMING OF CAB EXPRESSION 1; ZTL: ZEITLUPE.

Heat stress effects on source-sink relationships and metabolome dynamics in wheat

Crops such as wheat (Triticum spp.) are predicted to face more frequent exposures to heat stress as a result of climate change. Increasing the yield and sustainability of yield under such stressful conditions has long been a major target of wheat breeding, and this goal is becoming increasingly urgent as the global population increases. Exposure of wheat plants in their reproductive or grain-filling stage to high temperature affects the duration and rate of grain filling, and hence has a negative impact on wheat productivity. Therefore, understanding the plasticity of the response to heat stress that exists between wheat genotypes, especially in source-sink relationships at the reproductive and grain-filling stages, is critical for the selection of germplasm that can maintain high yields under heat stress. A broad understanding of metabolic dynamics and the relationships between metabolism and heat tolerance is required in order to achieve this goal. Here, we review the current literature concerning the effects of heat stress on sink-source relationships in a wide range of wheat genotypes, and highlight the current metabolomic approaches that are used to investigate high temperature responses in wheat.

Response of maize biomass and soil water fluxes on elevated CO2 and drought-From field experiments to process-based simulations

The rising concentration of atmospheric carbon dioxide (CO₂ ) is known to increase the total aboveground biomass of several C3 crops, whereas C4 crops are reported to be hardly affected when water supply is sufficient. However, a free-air carbon enrichment (FACE) experiment in Braunschweig, Germany, in 2007 and 2008 resulted in a 25% increased biomass of the C4 crop maize under restricted water conditions and elevated CO₂ (550 ppm). To project future yields of maize under climate change, an accurate representation of the effects of eCO₂ and drought on biomass and soil water conditions is essential. Current crop growth models reveal limitations in simulations of maize biomass under eCO₂ and limited water supply. We use the coupled process-based hydrological-plant growth model Catchment Modeling Framework-Plant growth Modeling Framework to overcome this limitation. We apply the coupled model to the maize-based FACE experiment in Braunschweig that provides robust data for the investigation of combined CO₂ and drought effects. We approve hypothesis I that CO₂ enrichment has a small direct-fertilizing effect with regard to the total aboveground biomass of maize and hypothesis II that CO₂ enrichment decreases water stress and leads to higher yields of maize under restricted water conditions. Hypothesis III could partly be approved showing that CO₂ enrichment decreases the transpiration of maize, but does not raise soil moisture, while increasing evaporation. We emphasize the importance of plant-specific CO₂ response factors derived by use of comprehensive FACE data. By now, only one FACE experiment on maize is accomplished applying different water levels. For the rigorous testing of plant growth models and their applicability in climate change studies, we call for datasets that go beyond single criteria (only yield response) and single effects (only elevated CO₂ ).

Characterization of Two Growth Period QTLs Reveals Modification of PRR3 Genes During Soybean Domestication

Soybean yield is largely dependent on growth period. We characterized two growth period quantitative trait loci, Gp11 and Gp12, from a recombinant inbred population generated from a cross of wild (W05) and cultivated (C08) soybean. Lines carrying Gp11C08 and Gp12C08 tend to have a shorter growth period and higher expression of GmFT2a and GmFT5a. Furthermore, multiple interval mapping suggests that Gp11 and Gp12 may be genetically interacting with the E2 locus. This is consistent with the observation that GmFT2a and GmFT5a are activated by Gp11C08 and Gp12C08 at ZT4 in the recessive e2 but not the dominant E2 background. Gp11 and Gp12 are duplicated genomic regions each containing a copy of the soybean ortholog of PSEUDO RESPONSE REGULATOR 3 (GmPRR3A and GmPRR3B). GmPRR3A and GmPRR3B from C08 carry mutations that delete the CCT domain in the encoded proteins. These mutations were selected during soybean improvement and they alter the subcellular localization of GmPRR3A and GmPRR3B. Furthermore, GmPRR3A and GmPRR3B can interact with TOPLESS-related transcription factors, suggesting that they function in a transcription repressor complex. This study addresses previously unexplored components of the genetic network that probably controls the growth period of soybean and puts these loci into context with the well-characterized growth period-regulating E loci.

Starch Trek: The Search for Yield

Starch is a plant storage polyglucan that accumulates in plastids. It is composed of two polymers, amylose and amylopectin, with different structures and plays several roles in helping to determine plant yield. In leaves, it acts as a buffer for night time carbon starvation. Genetically altered plants that cannot synthesize or degrade starch efficiently often grow poorly. There have been a number of successful approaches to manipulate leaf starch metabolism that has resulted in increased growth and yield. Its degradation is also a source of sugars that can help alleviate abiotic stress. In edible parts of plants, starch often makes up the majority of the dry weight constituting much of the calorific value of food and feed. Increasing starch in these organs can increase this as well as increasing yield. Enzymes involved in starch metabolism are well known, and there has been much research analyzing their functions in starch synthesis and degradation, as well as genetic and posttranslational regulatory mechanisms affecting them. In this mini review, we examine work on this topic and discuss future directions that could be used to manipulate this metabolite for improved yield.

Modelling predicts that soybean is poised to dominate crop production across Africa

The superior agronomic and human nutritional properties of grain legumes (pulses) make them an ideal foundation for future sustainable agriculture. Legume-based farming is particularly important in Africa, where small-scale agricultural systems dominate the food production landscape. Legumes provide an inexpensive source of protein and nutrients to African households as well as natural fertilization for the soil. Although the consumption of traditionally grown legumes has started to decline, the production of soybeans (Glycine max Merr.) is spreading fast, especially across southern Africa. Predictions of future land-use allocation and production show that the soybean is poised to dominate future production across Africa. Land use models project an expansion of harvest area, whereas crop models project possible yield increases. Moreover, a seed change in farming strategy is underway. This is being driven largely by the combined cash crop value of products such as oils and the high nutritional benefits of soybean as an animal feed. Intensification of soybean production has the potential to reduce the dependence of Africa on soybean imports. However, a successful "soybean bonanza" across Africa necessitates an intensive research, development, extension, and policy agenda to ensure that soybean genetic improvements and production technology meet future demands for sustainable production.

Role of Modelling in International Crop Research: Overview and Some Case Studies

Crop modelling has the potential to contribute to global food and nutrition security. This paper briefly examines the history of crop modelling by international crop research centres of the CGIAR (formerly Consultative Group on International Agricultural Research but now known simply as CGIAR), whose primary focus is on less developed countries. Basic principles of crop modelling building up to a Genotype × Environment × Management × Socioeconomic (G × E × M × S) paradigm, are explained. Modelling has contributed to better understanding of crop performance and yield gaps, better prediction of pest and insect outbreaks, and improving the efficiency of crop management including irrigation systems and optimization of planting dates. New developments include, for example, use of remote sensed data and mobile phone technology linked to crop management decision support models, data sharing in the new era of big data, and the use of genomic selection and crop simulation models linked to environmental data to help make crop breeding decisions. Socio-economic applications include foresight analysis of agricultural systems under global change scenarios, and the consequences of potential food system shocks are also described. These approaches are discussed in this paper which also calls for closer collaboration among disciplines in order to better serve the crop research and development communities by providing model based recommendations ranging from policy development at the level of governmental agencies to direct crop management support for resource poor farmers.

Physiology Based Approaches for Breeding of Next-Generation Food Legumes

Plant breeders and agricultural scientists of the 21st century are challenged to increase the yield potentials of crops to feed the growing world population. Climate change, the resultant stresses and increasing nutrient deficiencies are factors that are to be considered in designing modern plant breeding pipelines. Underutilized food legumes have the potential to address these issues and ensure food security in developing nations of the world. Food legumes in the past have drawn limited research funding and technological attention when compared to cereal crops. Physiological breeding strategies that were proven to be successful in cereals are to be adapted to legume crop improvement to realize their potential. The gap between breeders and physiologists should be narrowed by collaborative approaches to understand complex traits in legumes. This review discusses the potential of physiology based approaches in food legume breeding and how they impact yield gains and abiotic stress tolerance in these crops. The influence of roots and root system architectures in food legumes' breeding is also discussed. Molecular breeding to map the relevant physiological traits and the potentials of gene editing those traits are detailed. It is imperative to unlock the potentials of these underutilized crops to attain sustainable environmental and nutritional food security.