Rising temperatures reduce global wheat production

Effectiveness of time of sowing and cultivar choice for managing climate change: wheat crop phenology and water use efficiency

Climate change (CC) presents a challenge for the sustainable development of wheat production systems in Australia. This study aimed to (1) quantify the impact of future CC on wheat grain yield for the period centred on 2030 from the perspectives of wheat phenology, water use and water use efficiency (WUE) and (2) evaluate the effectiveness of changing sowing times and cultivars in response to the expected impacts of future CC on wheat grain yield. The daily outputs of CSIRO Conformal-Cubic Atmospheric Model for baseline and future periods were used by a stochastic weather generator to derive changes in mean climate and in climate variability and to construct local climate scenarios, which were then coupled with a wheat crop model to achieve the two research aims. We considered three locations in New South Wales, Australia, six times of sowing (TOS) and three bread wheat (Triticum aestivum L.) cultivars in this study. Simulation results show that in 2030 (1) for impact analysis, wheat phenological events are expected to occur earlier and crop water use is expected to decrease across all cases (the combination of three locations, six TOS and three cultivars), wheat grain yield would increase or decrease depending on locations and TOS; and WUE would increase in most of the cases; (2) for adaptation considerations, the combination of TOS and cultivars with the highest yield varied across locations. Wheat growers at different locations will require different strategies in managing the negative impacts or taking the opportunities of future CC.

Domestication and Improvement in the Model C4 Grass, Setaria

Setaria viridis (green foxtail) and its domesticated relative S. italica (foxtail millet) are diploid C4 panicoid grasses that are being developed as model systems for studying grass genomics, genetics, development, and evolution. According to archeological evidence, foxtail millet was domesticated from green foxtail approximately 9,000 to 6,000 YBP in China. Under long-term human selection, domesticated foxtail millet developed many traits adapted to human cultivation and agricultural production. In comparison with its wild ancestor, foxtail millet has fewer vegetative branches, reduced grain shattering, delayed flowering time and less photoperiod sensitivity. Foxtail millet is the only present-day crop in the genus Setaria, although archeological records suggest that other species were domesticated and later abandoned in the last 10,000 years. We present an overview of domestication in foxtail millet, by reviewing recent studies on the genetic regulation of several domesticated traits in foxtail millet and discuss how the foxtail millet and green foxtail system could be further developed to both better understand its domestication history, and to provide more tools for future breeding efforts.

Northward shift of the agricultural climate zone under 21st-century global climate change

As agricultural regions are threatened by climate change, warming of high latitude regions and increasing food demands may lead to northward expansion of global agriculture. While socio-economic demands and edaphic conditions may govern the expansion, climate is a key limiting factor. Extant literature on future crop projections considers established agricultural regions and is mainly temperature based. We employed growing degree days (GDD), as the physiological link between temperature and crop growth, to assess the global northward shift of agricultural climate zones under 21^st-century climate change. Using ClimGen scenarios for seven global climate models (GCMs), based on greenhouse gas (GHG) emissions and transient GHGs, we delineated the future extent of GDD areas, feasible for small cereals, and assessed the projected changes in rainfall and potential evapotranspiration. By 2099, roughly 76% (55% to 89%) of the boreal region might reach crop feasible GDD conditions, compared to the current 32%. The leading edge of the feasible GDD will shift northwards up to 1200 km by 2099 while the altitudinal shift remains marginal. However, most of the newly gained areas are associated with highly seasonal and monthly variations in climatic water balances, a critical component of any future land-use and management decisions.

The electronic Rothamsted Archive (e-RA), an online resource for data from the Rothamsted long-term experiments

The electronic Rothamsted Archive, e-RA (www.era.rothamsted.ac.uk) provides a permanent managed database to both securely store and disseminate data from Rothamsted Research’s long-term field experiments (since 1843) and meteorological stations (since 1853). Both historical and contemporary data are made available via this online database which provides the scientific community with access to a unique continuous record of agricultural experiments and weather measured since the mid-19^th century. Qualitative information, such as treatment and management practices, plans and soil information, accompanies the data and are made available on the e-RA website. e-RA was released externally to the wider scientific community in 2013 and this paper describes its development, content, curation and the access process for data users. Case studies illustrate the diverse applications of the data, including its original intended purposes and recent unforeseen applications. Usage monitoring demonstrates the data are of increasing interest. Future developments, including adopting FAIR data principles, are proposed as the resource is increasingly recognised as a unique archive of data relevant to sustainable agriculture, agroecology and the environment.

Wheat pre-anthesis development as affected by photoperiod sensitivity genes (Ppd-1) under contrasting photoperiods

Fine tuning wheat phenology is of paramount importance for adaptation. A better understanding of how genetic constitution modulates the developmental responses during pre-anthesis phases would help to maintain or even increase yield potential as temperature increases due to climate change. The photoperiod-sensitive cultivar Paragon, and four near isogenic lines with different combinations of insensitivity alleles (Ppd-A1a, Ppd-B1a, Ppd-D1a or their triple stack) were evaluated under short (12h) and long (16h) photoperiods. Insensitivity alleles decreased time to anthesis and duration of the three pre-anthesis phases (vegetative, early reproductive and late reproductive), following the Ppd-D1a > Ppd-A1a > Ppd-B1a ranking of strength. Stacking them intensified the insensitivity, but had no additive effect over that of Ppd-D1a. The late reproductive phase was the most responsive, even exhibiting a qualitative response. Leaf plastochron was not affected but spikelet plastochron increased according to Ppd-1a ranking of strength. Earlier anthesis resulted from less leaves differentiated and a fine tuning effect of accelerated rate of leaf appearance. None of the alleles affected development exclusively during any particular pre-anthesis phase, which would be ideal for tailoring time to anthesis with specific partitioning of developmental time into particular phases. Other allelic variants should be further tested to this purpose.

Global QTL Analysis Identifies Genomic Regions on Chromosomes 4A and 4B Harboring Stable Loci for Yield-Related Traits Across Different Environments in Wheat (Triticum aestivum L.)

Major advances in wheat production are needed to address global food insecurity under future climate conditions, such as high temperatures. The grain yield of bread wheat (Triticum aestivum L.) is a quantitatively inherited complex trait that is strongly influenced by interacting genetic and environmental factors. Here, we conducted global QTL analysis for five yield-related traits, including spike yield, yield components and plant height (PH), in the Nongda3338/Jingdong6 doubled haploid (DH) population using a high-density SNP and SSR-based genetic map. A total of 12 major genomic regions with stable QTL controlling yield-related traits were detected on chromosomes 1B, 2A, 2B, 2D, 3A, 4A, 4B, 4D, 5A, 6A, and 7A across 12 different field trials with timely sown (normal) and late sown (heat stress) conditions. Co-location of yield components revealed significant tradeoffs between thousand grain weight (TGW) and grain number per spike (GNS) on chromosome 4A. Dissection of a "QTL-hotspot" region for grain weight on chromosome 4B was helpful in marker-assisted selection (MAS) breeding. Moreover, this study identified a novel QTL for heat susceptibility index of thousand grain weight (HSITGW) on chromosome 4BL that explains approximately 10% of phenotypic variation. QPh.cau-4B.2, QPh.cau-4D.1 and QPh.cau-2D.3 were coincident with the dwarfing genes Rht1, Rht2, and Rht8, and haplotype analysis revealed their pleiotropic architecture with yield components. Overall, our findings will be useful for elucidating the genetic architecture of yield-related traits and developing new wheat varieties with high and stable yield.

Decreased photosynthetic rate under high temperature in wheat is due to lipid desaturation, oxidation, acylation, and damage of organelles

BACKGROUND

High temperature is a major abiotic stress that limits wheat (Triticum aestivum L.) productivity. Variation in levels of a wide range of lipids, including stress-related molecular species, oxidative damage, cellular organization and ultrastructural changes were analyzed to provide an integrated view of the factors that underlie decreased photosynthetic rate under high temperature stress. Wheat plants of cultivar Chinese Spring were grown at optimum temperatures (25/15 °C, maximum/minimum) until the onset of the booting stage. Thereafter, plants were exposed to high temperature (35/25 °C) for 16 d.

RESULTS

Compared with optimum temperature, a lower photosynthetic rate was observed at high temperature which is an interplay between thylakoid membrane damage, thylakoid membrane lipid composition, oxidative damage of cell organelle, and stomatal and non-stomatal limitations. Triacylglycerol levels were higher under high temperature stress. Polar lipid fatty acyl unsaturation was lower at high temperature, while triacylglycerol unsaturation was the same at high temperature and optimum temperature. The changes in lipid species indicates increases in activities of desaturating, oxidizing, glycosylating and acylating enzymes under high temperature stress. Cumulative effect of high temperature stress led to generation of reactive oxygen species, cell organelle and membrane damage, and reduced antioxidant enzyme activity, and imbalance between reactive oxygen species and antioxidant defense system.

CONCLUSIONS

Taken together with recent findings demonstrating that reactive oxygen species are formed from and are removed by thylakoid lipids, the data suggest that reactive oxygen species production, reactive oxygen species removal, and changes in lipid metabolism contribute to decreased photosynthetic rate under high temperature stress.

Underestimation of N2 O emissions in a comparison of the DayCent, DNDC, and EPIC models

Process-based models are increasingly used to study agroecosystem interactions and N₂ O emissions from agricultural fields. The widespread use of these models to conduct research and inform policy benefits from periodic model comparisons that assess the state of agroecosystem modeling and indicate areas for model improvement. This work provides an evaluation of simulated N₂ O flux from three process-based models: DayCent, DNDC, and EPIC. The models were calibrated and validated using data collected from two research sites over five years that represent cropping systems and nitrogen fertilizer management strategies common to dairy cropping systems. We also evaluated the use of a multi-model ensemble strategy, which inconsistently outperformed individual model estimations. Regression analysis indicated a cross-model bias to underestimate high magnitude daily and cumulative N₂ O flux. Model estimations of observed soil temperature and water content did not sufficiently explain model underestimations, and we found significant variation in model estimates of heterotrophic respiration, denitrification, soil NH₄⁺ , and soil NO₃^- , which may indicate that additional types of observed data are required to evaluate model performance and possible biases. Our results suggest a bias in the model estimation of N₂ O flux from agroecosystems that limits the extension of models beyond calibration and as instruments of policy development. This highlights a growing need for the modeling and measurement communities to collaborate in the collection and analysis of the data necessary to improve models and coordinate future development.

Climate Change and the Neglected Tropical Diseases

Climate change is expected to impact across every domain of society, including health. The majority of the world's population is susceptible to pathological, infectious disease whose life cycles are sensitive to environmental factors across different physical phases including air, water and soil. Nearly all so-called neglected tropical diseases (NTDs) fall into this category, meaning that future geographic patterns of transmission of dozens of infections are likely to be affected by climate change over the short (seasonal), medium (annual) and long (decadal) term. This review offers an introduction into the terms and processes deployed in modelling climate change and reviews the state of the art in terms of research into how climate change may affect future transmission of NTDs. The 34 infections included in this chapter are drawn from the WHO NTD list and the WHO blueprint list of priority diseases. For the majority of infections, some evidence is available of which environmental factors contribute to the population biology of parasites, vectors and zoonotic hosts. There is a general paucity of published research on the potential effects of decadal climate change, with some exceptions, mainly in vector-borne diseases.

Impact of Crop Husbandry Practices and Environmental Conditions on Wheat Composition and Quality: A Review

The increasing interest in the production of bread wheat ( Triticum aestivum L.) with specific quality traits requires a shift from the current breeding goal, being yield, to improved compositional and, consequently, functional traits. Since wheat is a key food crop, this must be attained while maintaining or even further increasing yield. Furthermore, as compositional requirements for specific applications are not well-defined, both protein and gluten content as well as the enzymatic activity remain most important. Given that these traits are majorly impacted by both genotype and environment, it is very complex to predict and ultimately control them. Different strategies, such as applying optimized agronomic practices, can temper these uncontrollable determinants which are equally important to steer wheat quality. As current research on their contribution to specific traits is highly fragmented, this report provides a comprehensive review of the influence of crop husbandry and environmental conditions on wheat yield and composition.

Climate change effect on wheat phenology depends on cultivar change

Changing crop phenology is considered an important bio-indicator of climate change, with the recent warming trend causing an advancement in crop phenology. Little is known about the contributions of changes in sowing dates and cultivars to long-term trends in crop phenology, particularly for winter crops such as winter wheat. Here, we analyze a long-term (1952–2013) dataset of phenological observations across western Germany and observations from a two-year field experiment to directly compare the phenologies of winter wheat cultivars released between 1950 and 2006. We found a 14–18% decline in the temperature sum required from emergence to flowering for the modern cultivars of winter wheat compared with the cultivars grown in the 1950s and 1960s. The trends in the flowering day obtained from a phenology model parameterized with the field observations showed that changes in the mean temperature and cultivar properties contributed similarly to the trends in the flowering day, whereas the effects of changes in the sowing day were negligible. We conclude that the single-cultivar concept commonly used in climate change impact assessments results in an overestimation of winter wheat sensitivity to increasing temperature, which suggests that studies on climate change effects should consider changes in cultivars.

Combined effects of elevated temperature and CO2 enhance threat from low temperature hazard to winter wheat growth in North China

We examined the growth and yield of winter wheat (Triticum aestivum) in response to the predicted elevated CO2 concentration and temperature to determine the mechanism of the combined impacts in North China Plain. An elevated treatment (CO2: 600 μmol mol-1, temperature: +2.5~3.0 °C, ECTI) and a control treatment (ambient CO2 and temperature, CK) were conducted in open-top chambers from October 2013 to June 2016. Post-winter growth stages of winter wheat largely advanced and shifted to a cooler period of nature season under combined impact of elevated CO2 and temperature during the entire growing season. The mean temperature and accumulated photosynthetic active radiations (PAR) over the post-winter growing period in ECTI decreased by 0.8-1.5 °C and 10-13%, respectively compared with that in CK, negatively impacted winter wheat growth. As a result, winter wheat in ECTI suffered from low temperature hazards during critical period of floret development and anthesis and grain number per ear was reduced by 10-31% in the three years. Although 1000-kernel weight in ECTI increased by 8-9% mainly due to elevated CO2, increasing CO2 concentration from 400 to 600 μmol mol-1 throughout the growth stage was not able to offset the adverse effect of warming on winter wheat growth and yield.

Physiological and molecular characterisation for high temperature stress in Lens culinaris

In the present study, 11 lentil (Lens culinaris Medik) genotypes including heat tolerant and heat sensitive genotypes identified after a screening of 334 accessions of lentil for traits imparting heat tolerance, were characterised based on physiological traits and molecular markers. Results showed a higher reduction in pollen viability among sensitive genotypes (up to 52.3%) compared with tolerant genotypes (up to 32.4%) at 43°C. Higher photosynthetic electron transport rate was observed among heat tolerant genotypes and two heat tolerant lentil genotypes, IG 4258 (0.43) and IG 3330 (0.38) were having highest Fv/Fm values. However, membrane stability was significantly higher in only one heat tolerant genotype, ILL 10712, indicating that different mechanisms are involved to control heat tolerance in lentil. The molecular characterisation of lentil genotypes with 70 polymorphic SSR and genic markers resulted into distinct clusters in accordance with their heat stress tolerance. A functional marker ISM11257 (intron spanning marker) amplifying an allele of 205bp in size was present only among heat tolerant genotypes, and could be further used in a breeding program to identify heat tolerant lentil genotypes. The findings of this study will contribute to the development of heat tolerant lentil cultivars.

Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments

Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple-ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple-ensemble probabilistic assessment, the median of simulated yield change was -4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981-2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple-ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources.

Impacts and Uncertainties of +2°C of Climate Change and Soil Degradation on European Crop Calorie Supply

Even if global warming is kept below +2°C, European agriculture will be significantly impacted. Soil degradation may amplify these impacts substantially and thus hamper crop production further. We quantify biophysical consequences and bracket uncertainty of +2°C warming on calories supply from 10 major crops and vulnerability to soil degradation in Europe using crop modeling. The Environmental Policy Integrated Climate (EPIC) model together with regional climate projections from the European branch of the Coordinated Regional Downscaling Experiment (EURO-CORDEX) was used for this purpose. A robustly positive calorie yield change was estimated for the EU Member States except for some regions in Southern and South-Eastern Europe. The mean impacts range from +30 Gcal ha-1 in the north, through +25 and +20 Gcal ha-1 in Western and Eastern Europe, respectively, to +10 Gcal ha-1 in the south if soil degradation and heat impacts are not accounted for. Elevated CO2 and increased temperature are the dominant drivers of the simulated yield changes in high-input agricultural systems. The growth stimulus due to elevated CO2 may offset potentially negative yield impacts of temperature increase by +2°C in most of Europe. Soil degradation causes a calorie vulnerability ranging from 0 to 50 Gcal ha-1 due to insufficient compensation for nutrient depletion and this might undermine climate benefits in many regions, if not prevented by adaptation measures, especially in Eastern and North-Eastern Europe. Uncertainties due to future potentials for crop intensification are about 2-50 times higher than climate change impacts.

Agroclimatology and Wheat Production: Coping with Climate Change

Cereal production around the world is critical to the food supply for the human population. Crop productivity is primarily determined by a combination of temperature and precipitation because temperatures have to be in the range for plant growth and precipitation has to supply crop water requirements for a given environment. The question is often asked about the changes in productivity and what we can expect in the future and we evaluated the causes for variation in historical annual statewide wheat grain yields in Oklahoma, Kansas, and North Dakota across the Great Plains of United States. Wheat (Triticum aestivum L.) is adapted to this area and we focused on production in these states from 1950 to 2016. This analysis used a framework for annual yields using yield gaps between attainable and actual yields and found the primary cause of the variation among years were attributable to inadequate precipitation during the grain-filling period. In Oklahoma, wheat yields were reduced when April and May precipitation was limited (r2 = 0.70), while in Kansas, May precipitation was the dominant factor (r2 = 0.78), and in North Dakota June-July precipitation was the factor explaining yield variation (r2 = 0.65). Temperature varied among seasons and at the statewide level did not explain a significant portion of the yield variation. The pattern of increased variation in precipitation will cause further variation in wheat production across the Great Plains. Reducing yield variation among years will require adaptation practices that increase water availability to the crop coupled with the positive impact derived from other management practices, e.g., cultivars, fertilizer management, etc.

Saline soil properties, quality and productivity of wheat grown with bagasse ash and thiourea in different climatic zones

Soil salinity and atmosphere temperature change have negative impacts on crop productivity and its quality and can pose a significant risk to soil properties in semi-arid regions. We conducted two field experiments in North (first zone) and South (second zone) of Egypt to investigate the effects of soil bagasse ash (10 ton ha^-1), foliar thiourea (240 g ha^-1) and their combination in comparison to the control treatment on saline soil properties and productivity and quality traits of wheat. All studied treatments were received the recommended rate of N, P and K fertilizations. Combination of soil bagasse ash and foliar thiourea application resulted in a significant improvement of most studied soil properties (i.e. EC, compaction, hydraulic conductivity, OM and available P, K, N contents) after harvest in comparison to other treatments in both of zones. Also, it enhanced growth and grain yield of wheat in terms of photosynthesis related attributes and yield components. Moreover, combination of soil bagasse ash and foliar thiourea application resulted in superior grain quality traits in terms of carbohydrate, fibre, protein and ash contents than separated application of soil bagasse ash, foliar thiourea or even control treatment. In conclusion, combination of soil bagasse ash and foliar thiourea application can be used as suitable option to enhance plant nutrition, wheat productivity and improve wheat grain quality and soil traits in saline soil as well as can alleviate heat stress.

Geographical patterns in climate and agricultural technology drive soybean productivity in Brazil

The impacts of global climate change have been a worldwide concern for several research areas, including those dealing with resources essential to human well being, such as agriculture, which directly impact economic activities and food security. Here we evaluate the relative effect of climate (as indicated by the Ecological Niche Model-ENM) and agricultural technology on actual soybean productivity in Brazilian municipalities and estimate the future geographic distribution of soybeans using a novel statistical approach allowing the evaluation of partial coefficients in a non-stationary (Geographically Weighted Regression; GWR) model. We found that technology was more important than climate in explaining soybean productivity in Brazil. However, some municipalities are more dependent on environmental suitability (mainly in Southern Brazil). The future environmental suitability for soybean cultivation tends to decrease by up 50% in the central region of Brazil. Meanwhile, southern-most Brazil will have more favourable conditions, with an increase of ca. 25% in environmental suitability. Considering that opening new areas for cultivation can degrade environmental quality, we suggest that, in the face of climate change impacts on soybean cultivation, the Brazilian government and producers must invest in breeding programmes and more general ecosystem-based strategies for adaptation to climate change, including the development of varieties tolerant to climate stress, and strategies to increase productivity and reduce costs (social and environmental).

Biophysical and economic implications for agriculture of +1.5° and +2.0°C global warming using AgMIP Coordinated Global and Regional Assessments

This study presents results of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Global and Regional Assessments (CGRA) of +1.5° and +2.0°C global warming above pre-industrial conditions. This first CGRA application provides multi-discipline, multi-scale, and multi-model perspectives to elucidate major challenges for the agricultural sector caused by direct biophysical impacts of climate changes as well as ramifications of associated mitigation strategies. Agriculture in both target climate stabilizations is characterized by differential impacts across regions and farming systems, with tropical maize Zea mays experiencing the largest losses, while soy Glycine max mostly benefits. The result is upward pressure on prices and area expansion for maize and wheat Triticum aestivum, while soy prices and area decline (results for rice Oryza sativa are mixed). An example global mitigation strategy encouraging bioenergy expansion is more disruptive to land use and crop prices than the climate change impacts alone, even in the +2.0°C scenario which has a larger climate signal and lower mitigation requirement than the +1.5°C scenario. Coordinated assessments reveal that direct biophysical and economic impacts can be substantially larger for regional farming systems than global production changes. Regional farmers can buffer negative effects or take advantage of new opportunities via mitigation incentives and farm management technologies. Primary uncertainties in the CGRA framework include the extent of CO₂ benefits for diverse agricultural systems in crop models, as simulations without CO₂ benefits show widespread production losses that raise prices and expand agricultural area.

Decadal analysis of impact of future climate on wheat production in dry Mediterranean environment: A case of Jordan

Different aspects of climate change, such as increased temperature, changed rainfall and higher atmospheric CO₂ concentration, all have different effects on crop yields. Process-based crop models are the most widely used tools for estimating future crop yield responses to climate change. We applied APSIM crop simulation model in a dry Mediterranean climate with Jordan as sentinel site to assess impact of climate change on wheat production at decadal level considering two climate change scenarios of representative concentration pathways (RCP) viz., RCP4.5 and RCP8.5. Impact of climatic variables alone was negative on grain yield but this adverse effect was negated when elevated atmospheric CO₂ concentrations were also considered in the simulations. Crop cycle of wheat was reduced by a fortnight for RCP4.5 scenario and by a month for RCP8.5 scenario at the approach of end of the century. On an average, a grain yield increase of 5 to 11% in near future i.e., 2010s-2030s decades, 12 to 16% in mid future i.e., 2040s-2060s decades and 9 to 16% in end of century period can be expected for moderate climate change scenario (RCP4.5) and 6 to 15% in near future, 13 to 19% in mid future and 7 to 20% increase in end of century period for a drastic climate change scenario (RCP8.5) based on different soils. Positive impact of elevated CO₂ is more pronounced in soils with lower water holding capacity with moderate increase in temperatures. Elevated CO₂ had greater positive effect on transpiration use efficiency (TUE) than negative effect of elevated mean temperatures. The change in TUE was in near perfect direct relationship with elevated CO₂ levels (R²>0.99) and every 100-ppm atmospheric CO₂ increase resulted in TUE increase by 2kgha^-1mm^-1. Thereby, in this environment yield gains are expected in future and farmers can benefit from growing wheat.

Improving the use of crop models for risk assessment and climate change adaptation

Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Our analysis drew on the other papers in this special issue, and on our experience in the UK Climate Change Risk Assessment 2017 and the MACSUR, AgMIP and ISIMIP projects. The criteria were used to assess how improvements could be made to the framing of climate change risks, and to outline the good practice and new developments that are needed to improve risk assessment. Key areas of good practice include: i. the development, running and documentation of crop models, with attention given to issues of spatial scale and complexity; ii. the methods used to form crop-climate ensembles, which can be based on model skill and/or spread; iii. the methods used to assess adaptation, which need broadening to account for technological development and to reflect the full range options available. The analysis highlights the limitations of focussing only on projections of future impacts and adaptation options using pre-determined time slices. Whilst this long-standing approach may remain an essential component of risk assessments, we identify three further key components: 1.Working with stakeholders to identify the timing of risks. What are the key vulnerabilities of food systems and what does crop-climate modelling tell us about when those systems are at risk?2.Use of multiple methods that critically assess the use of climate model output and avoid any presumption that analyses should begin and end with gridded output.3.Increasing transparency and inter-comparability in risk assessments. Whilst studies frequently produce ranges that quantify uncertainty, the assumptions underlying these ranges are not always clear. We suggest that the contingency of results upon assumptions is made explicit via a common uncertainty reporting format; and/or that studies are assessed against a set of criteria, such as those presented in this paper.

Unlocking new alleles for leaf rust resistance in the Vavilov wheat collection

Thirteen potentially new leaf rust resistance loci were identified in a Vavilov wheat diversity panel. We demonstrated the potential of allele stacking to strengthen resistance against this important pathogen. Leaf rust (LR) caused by Puccinia triticina is an important disease of wheat (Triticum aestivum L.), and the deployment of genetically resistant cultivars is the most viable strategy to minimise yield losses. In this study, we evaluated a diversity panel of 295 bread wheat accessions from the N. I. Vavilov Institute of Plant Genetic Resources (St Petersburg, Russia) for LR resistance and performed genome-wide association studies (GWAS) using 10,748 polymorphic DArT-seq markers. The diversity panel was evaluated at seedling and adult plant growth stages using three P. triticina pathotypes prevalent in Australia. GWAS was applied to 11 phenotypic data sets which identified a total of 52 significant marker-trait associations representing 31 quantitative trait loci (QTL). Among them, 29 QTL were associated with adult plant resistance (APR). Of the 31 QTL, 13 were considered potentially new loci, whereas 4 co-located with previously catalogued Lr genes and 14 aligned to regions reported in other GWAS and genomic prediction studies. One seedling LR resistance QTL located on chromosome 3A showed pronounced levels of linkage disequilibrium among markers (r ² = 0.7), suggested a high allelic fixation. Subsequent haplotype analysis for this region found seven haplotype variants, of which two were strongly associated with LR resistance at seedling stage. Similarly, analysis of an APR QTL on chromosome 7B revealed 22 variants, of which 4 were associated with resistance at the adult plant stage. Furthermore, most of the tested lines in the diversity panel carried 10 or more combined resistance-associated marker alleles, highlighting the potential of allele stacking for long-lasting resistance.

Evidence for a weakening strength of temperature-corn yield relation in the United States during 1980-2010

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 (R_{GST_CY}) has declined in the United States between 1980 and 2010 with a loss in the statistical significance. The regression slope which represents the anomalies in corn yield that occur in association with 1 degree temperature anomaly has decreased significantly from -6.9%/K of the first half period to -2.4%/K--3.5%/K of the second half period. This implies that projected corn yield reduction will be overestimated by a fact of 2 in a given warming scenario, if the corn-temperature relation is derived from the earlier historical period. Changes in R_{GST_CY} are mainly observed in Midwest Corn Belt and central High Plains, but are partly reproduced by 11 process-based crop models. In Midwest rain-fed systems, the decrease of negative temperature effects coincides with an increase in water availability by precipitation. In irrigated areas where water stress is minimized, the decline of beneficial temperature effects is significantly related to the increase in extreme hot days. The results indicate that an extrapolation of historical yield response to temperature may bias the assessment of agriculture vulnerability to climate change. Efforts to reduce climate impacts on agriculture should pay attention not only to climate change, but also to changes in climate-crop yield relations. There are some caveats that should be acknowledged as the analysis is restricted to the changes in the linear relation between growing season mean temperature and corn yield for the specific study period.

An AgMIP framework for improved agricultural representation in IAMs

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agricultural Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications.

Increasing temperature cuts back crop yields in Hungary over the last 90 years

The transformation of climatic regime has an undeniable impact on plant production, but we rarely have long enough date series to examine the unfolding of such effects. The clarification of the relationship between crop plants and climate has a near-immediate importance due to the impending human-made global change. This study investigated the relationship between temperature, precipitation, drought intensity and the yields of four major cereals in Hungary between 1921 and 2010. The analysis of 30-year segments indicated a monotonously increasing negative impact of temperature on crop yields. A 1°C temperature increase reduced the yield of the four main cereals by 9.6%-14.8% in 1981-2010, which revealed the vulnerability of Eastern European crop farming to recent climate change. Climate accounted for 17%-39% of yield variability over the past 90 years, but this figure reached 33%-67% between 1981 and 2010. Our analysis supports the claim that the mid-20th century green revolution improved yields "at the mercy of the weather": during this period, the impact of increasing fertilization and mechanisation coincided with climatic conditions that were more favourable than today. Crop yields in Eastern Europe have been stagnating or decreasing since the mid-1980s. Although usually attributed to the large socio-economic changes sweeping the region, our analysis indicates that a warming climate is at least partially responsible for this trend. Such a robust impact of increasing temperatures on crop yields also constitutes an obvious warning for this core grain-growing region of the world.

Responsive Proteins in Wheat Cultivars with Contrasting Nitrogen Efficiencies under the Combined Stress of High Temperature and Low Nitrogen

Productivity of wheat (Triticumaestivum) is markedly affected by high temperature and nitrogen deficiency. Identifying the functional proteins produced in response to these multiple stresses acting in a coordinated manner can help in developing tolerance in the crop. In this study, two wheat cultivars with contrasting nitrogen efficiencies (N-efficient VL616 and N-inefficient UP2382) were grown in control conditions, and under a combined stress of high temperature (32 °C) and low nitrogen (4 mM), and their leaf proteins were analysed in order to identify the responsive proteins. Two-dimensional electrophoresis unravelled sixty-one proteins, which varied in their expression in wheat, and were homologous to known functional proteins involved in biosynthesis, carbohydrate metabolism, energy metabolism, photosynthesis, protein folding, transcription, signalling, oxidative stress, water stress, lipid metabolism, heat stress tolerance, nitrogen metabolism, and protein synthesis. When exposed to high temperature in combination with low nitrogen, wheat plants altered their protein expression as an adaptive means to maintain growth. This response varied with cultivars. Nitrogen-efficient cultivars showed a higher potential of redox homeostasis, protein stability, osmoprotection, and regulation of nitrogen levels. The identified stress-responsive proteins can pave the way for enhancing the multiple-stress tolerance in wheat and developing a better understanding of its mechanism.

Putative Microsatellite DNA Marker-Based Wheat Genomic Resource for Varietal Improvement and Management

Wheat fulfills 20% of global caloric requirement. World needs 60% more wheat for 9 billion population by 2050 but climate change with increasing temperature is projected to affect wheat productivity adversely. Trait improvement and management of wheat germplasm requires genomic resource. Simple Sequence Repeats (SSRs) being highly polymorphic and ubiquitously distributed in the genome, can be a marker of choice but there is no structured marker database with options to generate primer pairs for genotyping on desired chromosome/physical location. Previously associated markers with different wheat trait are also not available in any database. Limitations of in vitro SSR discovery can be overcome by genome-wide in silico mining of SSR. Triticum aestivum SSR database (TaSSRDb) is an integrated online database with three-tier architecture, developed using PHP and MySQL and accessible at http://webtom.cabgrid.res.in/wheatssr/. For genotyping, Primer3 standalone code computes primers on user request. Chromosome-wise SSR calling for all the three sub genomes along with choice of motif types is provided in addition to the primer generation for desired marker. We report here a database of highest number of SSRs (476,169) from complex, hexaploid wheat genome (~17 GB) along with previously reported 268 SSR markers associated with 11 traits. Highest (116.93 SSRs/Mb) and lowest (74.57 SSRs/Mb) SSR densities were found on 2D and 3A chromosome, respectively. To obtain homozygous locus, e-PCR was done. Such 30 loci were randomly selected for PCR validation in panel of 18 wheat Advance Varietal Trial (AVT) lines. TaSSRDb can be a valuable genomic resource tool for linkage mapping, gene/QTL (Quantitative trait locus) discovery, diversity analysis, traceability and variety identification. Varietal specific profiling and differentiation can supplement DUS (Distinctiveness, Uniformity, and Stability) testing, EDV (Essentially Derived Variety)/IV (Initial Variety) disputes, seed purity and hybrid wheat testing. All these are required in germplasm management as well as also in the endeavor of wheat productivity.

New science of climate change impacts on agriculture implies higher social cost of carbon

Despite substantial advances in climate change impact research in recent years, the scientific basis for damage functions in economic models used to calculate the social cost of carbon (SCC) is either undocumented, difficult to trace, or based on a small number of dated studies. Here we present new damage functions based on the current scientific literature and introduce these into an integrated assessment model (IAM) in order to estimate a new SCC. We focus on the agricultural sector, use two methods for determining the yield impacts of warming, and the GTAP CGE model to calculate the economic consequences of yield shocks. These new damage functions reveal far more adverse agricultural impacts than currently represented in IAMs. Impacts in the agriculture increase from net benefits of $2.7 ton⁻¹ CO₂ to net costs of $8.5 ton⁻¹, leading the total SCC to more than double.

Climate change impacts in models used to calculate the social cost of carbon (SCC) are either poorly documented or based on a small number of dated studies. Here, the authors estimate new damages for the agricultural sector and find that updating this sector alone causes the SCC to increase substantially.

Strategies for feeding the world more sustainably with organic agriculture

Organic agriculture is proposed as a promising approach to achieving sustainable food systems, but its feasibility is also contested. We use a food systems model that addresses agronomic characteristics of organic agriculture to analyze the role that organic agriculture could play in sustainable food systems. Here we show that a 100% conversion to organic agriculture needs more land than conventional agriculture but reduces N-surplus and pesticide use. However, in combination with reductions of food wastage and food-competing feed from arable land, with correspondingly reduced production and consumption of animal products, land use under organic agriculture remains below the reference scenario. Other indicators such as greenhouse gas emissions also improve, but adequate nitrogen supply is challenging. Besides focusing on production, sustainable food systems need to address waste, crop-grass-livestock interdependencies and human consumption. None of the corresponding strategies needs full implementation and their combined partial implementation delivers a more sustainable food future.

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

Increasing global CO2 emissions have profound consequences for plant biology, not least because of direct influences on carbon gain. However, much remains uncertain regarding how our major crops will respond to a future high CO2 world. Crop model inter-comparison studies have identified large uncertainties and biases associated with climate change. The need to quantify uncertainty has drawn the fields of plant molecular physiology, crop breeding and biology, and climate change modeling closer together. Comparing data from different models that have been used to assess the potential climate change impacts on soybean and maize production, future yield losses have been predicted for both major crops. When CO2 fertilization effects are taken into account significant yield gains are predicted for soybean, together with a shift in global production from the Southern to the Northern hemisphere. Maize production is also forecast to shift northwards. However, unless plant breeders are able to produce new hybrids with improved traits, the forecasted yield losses for maize will only be mitigated by agro-management adaptations. In addition, the increasing demands of a growing world population will require larger areas of marginal land to be used for maize and soybean production. We summarize the outputs of crop models, together with mitigation options for decreasing the negative impacts of climate on the global maize and soybean production, providing an overview of projected land-use change as a major determining factor for future global crop production.

Future soil moisture and temperature extremes imply expanding suitability for rainfed agriculture in temperate drylands

The distribution of rainfed agriculture, which accounts for approximately ¾ of global croplands, is expected to respond to climate change and human population growth and these responses may be especially pronounced in water limited areas. Because the environmental conditions that support rainfed agriculture are determined by climate, weather, and soil conditions that affect overall and transient water availability, predicting this response has proven difficult, especially in temperate regions that support much of the world’s agriculture. Here, we show that suitability to support rainfed agriculture in temperate dryland climates can be effectively represented by just two daily environmental variables: moist soils with warm conditions increase suitability while extreme high temperatures decrease suitability. 21^st century projections based on daily ecohydrological modeling of downscaled climate forecasts indicate overall increases in the area suitable for rainfed agriculture in temperate dryland regions, especially at high latitudes. The regional exception to this trend was Europe, where suitability in temperate dryland portions will decline substantially. These results clarify how rising temperatures interact with other key drivers of moisture availability to determine the sustainability of rainfed agriculture and help policymakers, resource managers, and the agriculture industry anticipate shifts in areas suitable for rainfed cultivation.

Genome-wide association study for agronomic and physiological traits in spring wheat evaluated in a range of heat prone environments

We identified 27 stable loci associated with agronomic traits in spring wheat using genome-wide association analysis, some of which confirmed previously reported studies. GWAS peaks identified in regions where no QTL for grain yield per se has been mapped to date, provide new opportunities for gene discovery and creation of new cultivars with desirable alleles for improving yield and yield stability in wheat. We undertook large-scale genetic analysis to determine marker-trait associations (MTAs) underlying agronomic and physiological performance in spring wheat using genome-wide association studies (GWAS). Field trials were conducted at seven sites in three countries (Sudan, Egypt, and Syria) over 2-3 years in each country. Twenty-five agronomic and physiological traits were measured on 188 wheat genotypes. After correcting for population structure and relatedness, a total of 245 MTAs distributed over 66 loci were associated with agronomic traits in individual and mean performance across environments respectively; some of which confirmed previously reported loci. Of these, 27 loci were significantly associated with days to heading, thousand kernel weight, grain yield, spike length, and leaf rolling for mean performance across environments. Despite strong QTL by environment interactions, eight of the loci on chromosomes 1A, 1D, 5A, 5D, 6B, 7A, and 7B had pleiotropic effects on days to heading and yield components (TKW, SM^-2, and SNS). The winter-type alleles at the homoeologous VRN1 loci significantly increased days to heading and grain yield in optimal environments, but decreased grain yield in heat prone environments. Top 20 high-yielding genotypes, ranked by additive main effects and multiplicative interaction (AMMI), had low kinship relationship and possessed 4-5 favorable alleles for GY MTAs except two genotypes, Shadi-4 and Qafzah-11/Bashiq-1-2. This indicated different yield stability mechanisms due to potentially favorable rare alleles that are uncharacterized. Our results will enable wheat breeders to effectively introgress several desirable alleles into locally adapted germplasm in developing wheat varieties with high yield stability and enhanced heat tolerance.

Short periods of high temperature during meiosis prevent normal meiotic progression and reduce grain number in hexaploid wheat (Triticum aestivum L.)

Exposure of wheat to high temperatures during male meiosis prevents normal meiotic progression and reduces grain number. We define a temperature-sensitive period and link heat tolerance to chromosome 5D. This study assesses the effects of heat on meiotic progression and grain number in hexaploid wheat (Triticum aestivum L. var. Chinese Spring), defines a heat-sensitive stage and evaluates the role of chromosome 5D in heat tolerance. Plants were exposed to high temperatures (30 or 35 °C) in a controlled environment room for 20-h periods during meiosis and the premeiotic interphase just prior to meiosis. Examination of pollen mother cells (PMCs) from immature anthers immediately before and after heat treatment enabled precise identification of the developmental phases being exposed to heat. A temperature-sensitive period was defined, lasting from premeiotic interphase to late leptotene, during which heat can prevent PMCs from progressing through meiosis. PMCs exposed to 35 °C were less likely to progress than those exposed to 30 °C. Grain number per spike was reduced at 30 °C, and reduced even further at 35 °C. Chinese Spring nullisomic 5D-tetrasomic 5B (N5DT5B) plants, which lack chromosome 5D, were more susceptible to heat during premeiosis-leptotene than Chinese Spring plants with the normal (euploid) chromosome complement. The proportion of plants with PMCs progressing through meiosis after heat treatment was lower for N5DT5B plants than for euploids, but the difference was not significant. However, following exposure to 30 °C, in euploid plants grain number was reduced (though not significantly), whereas in N5DT5B plants the reduction was highly significant. After exposure to 35 °C, the reduction in grain number was highly significant for both genotypes. Implications of these findings for the breeding of thermotolerant wheat are discussed.

Temperature increase reduces global yields of major crops in four independent estimates

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.

Responses of crop yield growth to global temperature and socioeconomic changes

Although biophysical yield responses to local warming have been studied, we know little about how crop yield growth-a function of climate and technology-responds to global temperature and socioeconomic changes. Here, we present the yield growth of major crops under warming conditions from preindustrial levels as simulated by a global gridded crop model. The results revealed that global mean yields of maize and soybean will stagnate with warming even when agronomic adjustments are considered. This trend is consistent across socioeconomic assumptions. Low-income countries located at low latitudes will benefit from intensive mitigation and from associated limited warming trends (1.8 °C), thus preventing maize, soybean and wheat yield stagnation. Rice yields in these countries can improve under more aggressive warming trends. The yield growth of maize and soybean crops in high-income countries located at mid and high latitudes will stagnate, whereas that of rice and wheat will not. Our findings underpin the importance of ambitious climate mitigation targets for sustaining yield growth worldwide.

Projective analysis of staple food crop productivity in adaptation to future climate change in China

Climate change continually affects our capabilities to feed the increasing population. Rising temperatures have the potential to shorten the crop growth duration and therefore reduce crop yields. In the past decades, China has successfully improved crop cultivars to stabilize, and even lengthen, the crop growth duration to make use of increasing heat resources. However, because of the complex cropping systems in the different regions of China, the possibility and the effectiveness of regulating crop growth duration to reduce the negative impacts of future climate change remain questionable. Here, we performed a projective analysis of the staple food crop productivity in double-rice, wheat-rice, wheat-maize, single-rice, and single-maize cropping systems in China using modeling approaches. The results indicated that from the present to the 2040s, the warming climate would shorten the growth duration of the current rice, wheat, and maize cultivars by 2-24, 11-13, and 9-29 days, respectively. The most significant shortening of the crop growth duration would be in Northeast China, where single-rice and single-maize cropping dominates the croplands. The shortened crop growth duration would consequently reduce crop productivity. The most significant decreases would be 27-31, 6-20, and 7-22% for the late crop in the double-rice rotation, wheat in the winter wheat-rice rotation, and single maize, respectively. However, our projection analysis also showed that the negative effects of the warming climate could be compensated for by stabilizing the growth duration of the crops via improvement in crop cultivars. In this case, the productivity of rice, wheat, and maize in the 2040s would increase by 4-16, 31-38, and 11-12%, respectively. Our modeling results implied that the possibility of securing future food production exists by adopting proper adaptation options in China.

The uncertainty of crop yield projections is reduced by improved temperature response functions

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.

Crop Production under Drought and Heat Stress: Plant Responses and Management Options

Abiotic stresses are one of the major constraints to crop production and food security worldwide. The situation has aggravated due to the drastic and rapid changes in global climate. Heat and drought are undoubtedly the two most important stresses having huge impact on growth and productivity of the crops. It is very important to understand the physiological, biochemical, and ecological interventions related to these stresses for better management. A wide range of plant responses to these stresses could be generalized into morphological, physiological, and biochemical responses. Interestingly, this review provides a detailed account of plant responses to heat and drought stresses with special focus on highlighting the commonalities and differences. Crop growth and yields are negatively affected by sub-optimal water supply and abnormal temperatures due to physical damages, physiological disruptions, and biochemical changes. Both these stresses have multi-lateral impacts and therefore, complex in mechanistic action. A better understanding of plant responses to these stresses has pragmatic implication for remedies and management. A comprehensive account of conventional as well as modern approaches to deal with heat and drought stresses have also been presented here. A side-by-side critical discussion on salient responses and management strategies for these two important abiotic stresses provides a unique insight into the phenomena. A holistic approach taking into account the different management options to deal with heat and drought stress simultaneously could be a win-win approach in future.

Survey of High Throughput RNA-Seq Data Reveals Potential Roles for lncRNAs during Development and Stress Response in Bread Wheat

Long non-coding RNAs (lncRNAs) are a family of regulatory RNAs that play essential role in the various developmental processes and stress responses. Recent advances in sequencing technology and computational methods enabled identification and characterization of lncRNAs in certain plant species, but they are less known in Triticum aestivum (bread wheat). Herein, we analyzed 52 RNA seq data (>30 billion reads) and identified 44,698 lncRNAs in T. aestivum genome, which were characterized in comparison to the coding sequences (mRNAs). Similar to the mRNAs, lncRNAs were also derived from each sub-genome and chromosome, and showed tissue developmental stage specific and differential expression, as well. The modulated expression of lncRNAs during abiotic stresses like heat, drought, and salt indicated their putative role in stress response. The co-expression of lncRNAs with vital mRNAs including various transcription factors and enzymes involved in Abscisic acid (ABA) biosynthesis, and gene ontology mapping inferred their regulatory roles in numerous biological processes. A few lncRNAs were predicted as precursor (19 lncRNAs), while some as target mimics (1,047 lncRNAs) of known miRNAs involved in various regulatory functions. The results suggested numerous functions of lncRNAs in T. aestivum, and unfolded the opportunities for functional characterization of individual lncRNA in future studies.

Understanding the weather signal in national crop-yield variability

Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the US. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.

Contribution of Crop Models to Adaptation in Wheat

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. This review outlines the potential and limitations of modern wheat crop models in assisting agronomists, breeders, and policymakers to address the current and future challenges facing agriculture.

Hot spots of wheat yield decline with rising temperatures

Many of the irrigated spring wheat regions in the world are also regions with high poverty. The impacts of temperature increase on wheat yield in regions of high poverty are uncertain. A grain yield-temperature response function combined with a quantification of model uncertainty was constructed using a multimodel ensemble from two key irrigated spring wheat areas (India and Sudan) and applied to all irrigated spring wheat regions in the world. Southern Indian and southern Pakistani wheat-growing regions with large yield reductions from increasing temperatures coincided with high poverty headcounts, indicating these areas as future food security 'hot spots'. The multimodel simulations produced a linear absolute decline of yields with increasing temperature, with uncertainty varying with reference temperature at a location. As a consequence of the linear absolute yield decline, the relative yield reductions are larger in low-yielding environments (e.g., high reference temperature areas in southern India, southern Pakistan and all Sudan wheat-growing regions) and farmers in these regions will be hit hardest by increasing temperatures. However, as absolute yield declines are about the same in low- and high-yielding regions, the contributed deficit to national production caused by increasing temperatures is higher in high-yielding environments (e.g., northern India) because these environments contribute more to national wheat production. Although Sudan could potentially grow more wheat if irrigation is available, grain yields would be low due to high reference temperatures, with future increases in temperature further limiting production.