Rising temperatures reduce global wheat production

Correlation of elongation factor 1A accumulation with photosynthetic pigment content and yield in winter wheat varieties under heat stress conditions

Heat stress is one of the most important environmental factors that influences wheat growth and development, leading to significant losses in grain yield and has become a significant detrimental factor for worldwide wheat production. In recent years, several studies suggested that eukaryotic elongation factor 1A (eEF1A), may contribute to heat tolerance in plants, therefore the aim of this study was: to investigate the accumulation of eEF1A in wheat under conditions of moderate and high air temperatures; to determine the amount of photosynthetic pigments and to determine the yield traits; and to examine whether there is a correlation between eEF1A accumulation, photosynthetic pigments, and yield in different wheat varieties. The results showed that heat stress induced accumulation of eEF1A significantly different among wheat varieties and showed that varieties with a higher accumulation of eEF1A under heat stress are characterized by a smaller decrease in the photosynthetic pigments. A correlation between higher accumulation of eEF1A under heat stress and yield traits was found. Analyzed parameters from two growing seasons, indicated that the higher accumulation of eEF1A and a smaller decrease in photosynthetic pigments distinguishes the varieties more resistant to heat stress. The analysis of the molecular mechanisms by immunoblot, under conditions of high and moderate air temperatures in two growing seasons, aims to develop agricultural strategy and develop wheat varieties tolerant to heat stress.

Effect of Flowering Time-Related Genes on Biomass, Harvest Index, and Grain Yield in CIMMYT Elite Spring Bread Wheat

Simple Summary

Allelic variants of vernalization (Vrn), photoperiod (Ppd), and earliness per se (Eps) genes in two panels of elite spring wheat were used to estimate their effects on the phenological stages, biomass (BM), harvest index (HI), and grain yield (YLD). Major spring alleles of Vrn-1 had the largest effect on shortening the time to anthesis, while the Ppd-insensitive allele Ppd-D1a had the most significant positive effect on YLD. Furthermore, alleles at recently identified loci TaTOE-B1 and TaFT3-B1 promoted between 3.8% and 7.6% higher YLD and 4.2% and 10.2% higher HI in the two panels. Further, when the possible effects of the TaTOE-B1 and TaFT3-B1 alleles on the sink and source traits were explored, the favorable allele at TaTOE-B1 showed positive effects on several sink traits related mainly to the grain number. Favorable alleles at TaFT3-B1 followed a different pattern, with positive effects on the traits related to grain weight. The results of this study expanded the wheat breeders’ toolbox in the quest to breed better-adapted and higher-yielding wheat cultivars.

Abstract

Grain yield (YLD) is a function of the total biomass (BM) and of partitioning the biomass by grains, i.e., the harvest index (HI). The most critical developmental stage for their determination is the flowering time, which mainly depends on the vernalization requirement (Vrn) and photoperiod sensitivity genes (Ppd) loci. Allelic variants at the Vrn, Ppd, and earliness per se (Eps) genes of elite spring wheat genotypes included in High Biomass Association Panel (HiBAP) I and II were used to estimate their effects on the phenological stages BM, HI, and YLD. Each panel was grown for two consecutive years in Northwest Mexico. Spring alleles at Vrn-1 had the largest effect on shortening the time to anthesis, and the Ppd-insensitive allele Ppd-D1a had the most significant positive effect on YLD in both panels. In addition, alleles at TaTOE-B1 and TaFT3-B1 promoted between 3.8% and 7.6% higher YLD and 4.2% and 10.2% higher HI in HiBAP I and II, respectively. When the possible effects of the TaTOE-B1 and TaFT3-B1 alleles on the sink and source traits were explored, the favorable allele at TaTOE-B1 showed positive effects on several sink traits mainly related to grain number. The favorable alleles at TaFT3-B1 followed a different pattern, with positive effects on the traits related to grain weight. The results of this study expanded the wheat breeders’ toolbox in the quest to breed better-adapted and higher-yielding wheat cultivars.

Increased ranking change in wheat breeding under climate change

The International Maize and Wheat Improvement Center develops and annually distributes elite wheat lines to public and private breeders worldwide. Trials have been created in multiple sites over many years to assess the lines' performance for use in breeding and release as varieties, and to provide iterative feedback on refining breeding strategies¹. The collaborator test sites are experiencing climate change, with new implications for how wheat genotypes are bred and selected². Using a standard quantitative genetic model to analyse four International Maize and Wheat Improvement Center global spring wheat trial datasets, we examine how genotype-environment interactions have changed over recent decades. Notably, crossover interactions-a critical indicator of changes in the ranking of cultivar performance in different environments-have increased over time. Climatic factors explained over 70% of the year-to-year variability in crossover interactions for yield. Yield responses of all lines in trial environments from 1980 to 2018 revealed that climate change has increased the ranking change in breeding targeted to favourable environments by ~15%, while it has maintained or reduced the ranking change in breeding targeted to heat and drought stress by up to 13%. Genetic improvement has generally increased crossover interactions, particularly for wheat targeted to high-yielding environments. However, the latest wheat germplasm developed under heat stress was better adapted and more stable, partly offsetting the increase in ranking changes under the warmer climate.

Progress in Research on the Mechanisms Underlying Chloroplast-Involved Heat Tolerance in Plants

Global warming is a serious challenge plant production has to face. Heat stress not only affects plant growth and development but also reduces crop yield and quality. Studying the response mechanisms of plants to heat stress will help humans use these mechanisms to improve the heat tolerance of plants, thereby reducing the harm of global warming to plant production. Research on plant heat tolerance has gradually become a hotspot in plant molecular biology research in recent years. In view of the special role of chloroplasts in the response to heat stress in plants, this review is focusing on three perspectives related to chloroplasts and their function in the response of heat stress in plants: the role of chloroplasts in sensing high temperatures, the transmission of heat signals, and the improvement of heat tolerance in plants. We also present our views on the future direction of research on chloroplast related heat tolerance in plants.

Assessment of the performance of CORDEX regional climate models in simulating rainfall and air temperature over southwest Ethiopia

This study analyzed the performance of four (REgional MOdel (REMO2009), High-Resolution Hamburg Climate Model 5 (HIRAM5), Climate Limited-Area Modeling Community (CCLM4-8) and Rossby Centre Regional Atmospheric Model (RCA4)) Regional Climate Models (RCMs) simulations from Coordinated Regional Climate Downscaling Experiment (CORDEX) Africa program. The simulation period of 1985–2005 was evaluated considering how each RCM simulated the observed rainfall and air temperature over southwest Ethiopia. It was found that all the RCMs simulated the seasonal rainfall, but not the peak rainfall, with all models including their ensemble underestimating the peak rainfall. However, the ensemble was better than the individual RCMs in simulating both rainfall and air temperature. All models were slightly biased around a warm climate zone in simulating maximum air temperature when compared to the simulation of air minimum temperature. Of the four RCMs, REMO2009 performed well in simulating the maximum and minimum air temperatures. The interseasonal variation in rainfall was greater than the seasonal variation in air temperature. In terms of cumulative distribution, the HIRAM5 captured more extreme rainfall events and overestimated the return period. Overall, the differences in performance among the RCMs provided strong evidence for the use of regional-scale data at the local scale in climate impact assessments being controversial. In relation to the spatial pattern of the rainfall, most of the models simulated the observed minimum rainfall in the north and northeast, medium rainfall in the central region, and maximum rainfall in the south and southwest of the study area. The overall results indicate that choosing a reliable RCM is fundamentally necessary to delivering a strong basis for any climate-change impact study.

Warm temperature triggers JOX and ST2A-mediated jasmonate catabolism to promote plant growth

Plants respond to warm temperature by increased elongation growth of organs to enhance cooling capacity. Phytohormones, such as auxin and brassinosteroids, regulate this growth process. However, our view on the players involved in warm temperature-mediated growth remains fragmentary. Here, we show that warm temperature leads to an increased expression of JOXs and ST2A, genes controlling jasmonate catabolism. This leads to an elevated 12HSO₄-JA level and consequently to a reduced level of bioactive jasmonates. Ultimately this results in more JAZ proteins, which facilitates plant growth under warm temperature conditions. Taken together, understanding the conserved role of jasmonate signalling during thermomorphogenesis contributes to ensuring food security under a changing climate.

Plants undergo morphological changes to enhance cooling at warm temperatures. Here Zhu et al. show that JOXs and ST2A enzymes, which mediate jasmonate catabolism, contribute to this process by reducing the level of bioactive jasmonate facilitating growth responses.

Cereal Yield Forecasting with Satellite Drought-Based Indices, Weather Data and Regional Climate Indices Using Machine Learning in Morocco

Accurate seasonal forecasting of cereal yields is an important decision support tool for countries, such as Morocco, that are not self-sufficient in order to predict, as early as possible, importation needs. This study aims to develop an early forecasting model of cereal yields (soft wheat, barley and durum wheat) at the scale of the agricultural province considering the 15 most productive over 2000–2017 (i.e., 15 × 18 = 270 yields values). To this objective, we built on previous works that showed a tight linkage between cereal yields and various datasets including weather data (rainfall and air temperature), regional climate indices (North Atlantic Oscillation in particular), and drought indices derived from satellite observations in different wavelengths. The combination of the latter three data sets is assessed to predict cereal yields using linear (Multiple Linear Regression, MLR) and non-linear (Support Vector Machine, SVM; Random Forest, RF, and eXtreme Gradient Boost, XGBoost) machine learning algorithms. The calibration of the algorithmic parameters of the different approaches are carried out using a 5-fold cross validation technique and a leave-one-out method is implemented for model validation. The statistical metrics of the models are first analyzed as a function of the input datasets that are used, and as a function of the lead times, from 4 months to 2 months before harvest. The results show that combining data from multiple sources outperformed models based on one dataset only. In addition, the satellite drought indices are a major source of information for cereal prediction when the forecasting is carried out close to harvest (2 months before), while weather data and, to a lesser extent, climate indices, are key variables for earlier predictions. The best models can accurately predict yield in January (4 months before harvest) with an R2 = 0.88 and RMSE around 0.22 t. ha−1. The XGBoost method exhibited the best metrics. Finally, training a specific model separately for each group of provinces, instead of one global model, improved the prediction performance by reducing the RMSE by 10% to 35% depending on the provinces. In conclusion, the results of this study pointed out that combining remote sensing drought indices with climate and weather variables using a machine learning technique is a promising approach for cereal yield forecasting.

Screening for Higher Grain Yield and Biomass among Sixty Bread Wheat Genotypes Grown under Elevated CO2 and High-Temperature Conditions

Global warming will inevitably affect crop development and productivity, increasing uncertainty regarding food production. The exploitation of genotypic variability can be a promising approach for selecting improved crop varieties that can counteract the adverse effects of future climate change. We investigated the natural variation in yield performance under combined elevated CO₂ and high-temperature conditions in a set of 60 bread wheat genotypes (59 of the 8TH HTWSN CIMMYT collection and Gazul). Plant height, biomass production, yield components and phenological traits were assessed. Large variations in the selected traits were observed across genotypes. The CIMMYT genotypes showed higher biomass and grain yield when compared to Gazul, indicating that the former performed better than the latter under the studied environmental conditions. Principal component and hierarchical clustering analyses revealed that the 60 wheat genotypes employed different strategies to achieve final grain yield, highlighting that the genotypes that can preferentially increase grain and ear numbers per plant will display better yield responses under combined elevated levels of CO₂ and temperature. This study demonstrates the success of the breeding programs under warmer temperatures and the plants' capacity to respond to the concurrence of certain environmental factors, opening new opportunities for the selection of widely adapted climate-resilient wheat genotypes.

Large potential for crop production adaptation depends on available future varieties

Climate change affects global agricultural production and threatens food security. Faster phenological development of crops due to climate warming is one of the main drivers for potential future yield reductions. To counter the effect of faster maturity, adapted varieties would require more heat units to regain the previous growing period length. In this study, we investigate the effects of variety adaptation on global caloric production under four different future climate change scenarios for maize, rice, soybean, and wheat. Thereby, we empirically identify areas that could require new varieties and areas where variety adaptation could be achieved by shifting existing varieties into new regions. The study uses an ensemble of seven global gridded crop models and five CMIP6 climate models. We found that 39% (SSP5-8.5) of global cropland could require new crop varieties to avoid yield loss from climate change by the end of the century. At low levels of warming (SSP1-2.6), 85% of currently cultivated land can draw from existing varieties to shift within an agro-ecological zone for adaptation. The assumptions on available varieties for adaptation have major impacts on the effectiveness of variety adaptation, which could more than half in SSP5-8.5. The results highlight that region-specific breeding efforts are required to allow for a successful adaptation to climate change.

Intervessel pit membrane thickness best explains variation in embolism resistance amongst stems of Arabidopsis thaliana accessions

BACKGROUND AND AIMS

The ability to avoid drought-induced embolisms in the xylem is one of the essential traits for plants to survive periods of water shortage. Over the past three decades, hydraulic studies have been focusing on trees, which limits our ability to understand how herbs tolerate drought. Here we investigate the embolism resistance in inflorescence stems of four Arabidopsis thaliana accessions that differ in growth form and drought response. We assess functional traits underlying the variation in embolism resistance amongst the accessions studied using detailed anatomical observations.

METHODS

Vulnerability to xylem embolism was evaluated via vulnerability curves using the centrifuge technique and linked with detailed anatomical observations in stems using light microscopy and transmission electron microscopy.

KEY RESULTS

The data show significant differences in stem P50, varying 2-fold from -1.58 MPa in the Cape Verde Island accession to -3.07 MPa in the woody soc1 ful double mutant. Out of all the anatomical traits measured, intervessel pit membrane thickness (TPM) best explains the differences in P50, as well as P12 and P88. The association between embolism resistance and TPM can be functionally explained by the air-seeding hypothesis. There is no evidence that the correlation between increased woodiness and increased embolism resistance is directly related to functional aspects. However, we found that increased woodiness is strongly linked to other lignification characters, explaining why mechanical stem reinforcement is indirectly related to increased embolism resistance.

CONCLUSIONS

The woodier or more lignified accessions are more resistant to embolism than the herbaceous accessions, confirming the link between increased stem lignification and increased embolism resistance, as also observed in other lineages. Intervessel pit membrane thickness and, to a lesser extent, theoretical vessel implosion resistance and vessel wall thickness are the missing functional links between stem lignification and embolism resistance.

Discovery of miRNAs and Development of Heat-Responsive miRNA-SSR Markers for Characterization of Wheat Germplasm for Terminal Heat Tolerance Breeding

A large proportion of the Asian population fulfills their energy requirements from wheat (Triticum aestivum L.). Wheat quality and yield are critically affected by the terminal heat stress across the globe. It affects approximately 40% of the wheat-cultivating regions of the world. Therefore, there is a critical need to develop improved terminal heat-tolerant wheat varieties. Marker-assisted breeding with genic simple sequence repeats (SSR) markers have been used for developing terminal heat-tolerant wheat varieties; however, only few studies involved the use of microRNA (miRNA)-based SSR markers (miRNA-SSRs) in wheat, which were found as key players in various abiotic stresses. In the present study, we identified 104 heat-stress-responsive miRNAs reported in various crops. Out of these, 70 miRNA-SSR markers have been validated on a set of 20 terminal heat-tolerant and heat-susceptible wheat genotypes. Among these, only 19 miRNA-SSR markers were found to be polymorphic, which were further used to study the genetic diversity and population structure. The polymorphic miRNA-SSRs amplified 61 SSR loci with an average of 2.9 alleles per locus. The polymorphic information content (PIC) value of polymorphic miRNA-SSRs ranged from 0.10 to 0.87 with a mean value of 0.48. The dendrogram constructed using unweighted neighbor-joining method and population structure analysis clustered these 20 wheat genotypes into 3 clusters. The target genes of these miRNAs are involved either directly or indirectly in providing tolerance to heat stress. Furthermore, two polymorphic markers miR159c and miR165b were declared as very promising diagnostic markers, since these markers showed specific alleles and discriminated terminal heat-tolerant genotypes from the susceptible genotypes. Thus, these identified miRNA-SSR markers will prove useful in the characterization of wheat germplasm through the study of genetic diversity and population structural analysis and in wheat molecular breeding programs aimed at terminal heat tolerance of wheat varieties.

A Framework for Addressing the Twin Challenges of COVID-19 and Climate Change for Sustainable Agriculture and Food Security in South Asia

Climate change has begun to ravage agriculture and threaten food security in many parts of the world. The novel coronavirus pandemic (COVID-19) has further disrupted agricultural activities and supply chains and has become a serious threat for public health. Like in many developing countries, South Asian farmers are now facing the double challenge of addressing the impacts of a changing climate and managing the disruptions caused by COVID-19. Despite growing concern, there is limited understanding of how climate change, public health, and COVID-19 interact, and of the possible pathways to achieving a climate-friendly recovery from COVID-19 to achieve food and nutrition security. In view of this, this paper explores the multifaceted challenges that farmers are now facing in South Asia due to climate change and the disruption caused by COVID-19 from the agricultural and food security lens. The analysis reveals that the complex interactions of COVID-19 and climate change have impacted all dimensions of food security. These interlinkages demand an integrated approach in dealing with food, public health, and climate change to harness synergies and minimize trade-offs between food production, public health, and climate mitigation. I present a framework to address the immediate challenge of COVID-19 and the longer-term challenge of anthropogenic climate change. Key elements of the framework include the strengthening health sector response capacities, strengthening of local and regional food systems, making agriculture resilient to pandemics, adopting flexible and smart approaches—including the implementation of climate-smart agricultural interventions on different scales, promotion of appropriate research and innovation, and the integration of short-term support to address the challenges of COVID-19 to build long-term productivity, and resilience of food systems by investing on natural capital. This framework would enable policy makers to choose the appropriate policy responses at different scales, to address these twin challenges of COVID-19 and climate change.

Expansion of Agriculture in Northern Cold-Climate Regions: A Cross-Sectoral Perspective on Opportunities and Challenges

Agriculture in the boreal and Arctic regions is perceived as marginal, low intensity and inadequate to satisfy the needs of local communities, but another perspective is that northern agriculture has untapped potential to increase the local supply of food and even contribute to the global food system. Policies across northern jurisdictions target the expansion and intensification of agriculture, contextualized for the diverse social settings and market foci in the north. However, the rapid pace of climate change means that traditional methods of adapting cropping systems and developing infrastructure and regulations for this region cannot keep up with climate change impacts. Moreover, the anticipated conversion of northern cold-climate natural lands to agriculture risks a loss of up to 76% of the carbon stored in vegetation and soils, leading to further environmental impacts. The sustainable development of northern agriculture requires local solutions supported by locally relevant policies. There is an obvious need for the rapid development of a transdisciplinary, cross-jurisdictional, long-term knowledge development, and dissemination program to best serve food needs and an agricultural economy in the boreal and Arctic regions while minimizing the risks to global climate, northern ecosystems and communities.

Bottlenecks and opportunities in field-based high-throughput phenotyping for heat and drought stress

Flowering and grain-filling stages are highly sensitive to heat and drought stress exposure, leading to significant loss in crop yields. Therefore, phenotyping to enhance resilience to these abiotic stresses is critical for sustaining genetic gains in crop improvement programs. However, traditional methods for screening traits related to these stresses are slow, laborious, and often expensive. Remote sensing provides opportunities to introduce low-cost, less biased, high-throughput phenotyping methods to capture large genetic diversity to facilitate enhancement of stress resilience in crops. This review focuses on four key physiological traits and processes that are critical in understanding crop responses to drought and heat stress during reproductive and grain-filling periods. Specifically, these traits include: (i) time of day of flowering, to escape these stresses during flowering; (ii) optimizing photosynthetic efficiency; (iii) storage and translocation of water-soluble carbohydrates; and (iv) yield and yield components to provide in-season yield estimates. Moreover, we provide an overview of current advances in remote sensing in capturing these traits, and discuss the limitations with existing technology as well as future direction of research to develop high-throughput phenotyping approaches. In the future, phenotyping these complex traits will require sensor advancement, high-quality imagery combined with machine learning methods, and efforts in transdisciplinary science to foster integration across disciplines.

The optimization of wheat yield through adaptive crop management in a changing climate: evidence from China

BACKGROUND

Adaptive crop management is critical to food security in a changing climate, but the respective contributions of climate change and crop management to yields remain unclear. Thus, we distinguished and quantified the respective contribution of climate change and crop management on wheat yield between 1981 and 2018 in China, using first-difference multivariate regression model.

RESULTS

Wheat production in China has increased over the past four decades. Under the sole impact of climate change, wheat yield generally decreased (-5.45 to +1.09% decade^-1 ). Crop management increased the wheat yield from 7.11 to 19.94% decade^-1 . Sensitivities of wheat yield to climatic variables (average temperature, accumulated sunshine hours, accumulated precipitation) were spatially heterogeneous; notably, in spring-wheat planting areas, wheat yield was more susceptible to the negative impact of warming. In terms of relative contribution, the contribution of climate change to spring wheat yield was -24.08% to -5.41%, and the contribution to winter wheat was -4.98% to +34.69%. Crop management had a positive contribution to all wheat-growing areas (65.31-96.84%).

CONCLUSION

Crop management had a greater effect on wheat yield than climate change did. Among the three climatic variables investigated, average temperature had the dominant effect on wheat yield change; the impact of precipitation was minimal but mostly negative. The results provide insight regarding the contribution of climate change and crop management to wheat yield; adaptation measures may be more effective in planting areas where crop management contributes more, which will help stakeholders optimize crop management and adaptation strategies. © 2020 Society of Chemical Industry.

Meta-analysis of genome-wide association studies reveal common loci controlling agronomic and quality traits in a wide range of normal and heat stressed environments

Several stable QTL were detected using metaGWAS analysis for different agronomic and quality traits under 26 normal and heat stressed environments. Heat stress, exacerbated by global warming, has a negative influence on wheat production worldwide and climate resilient cultivars can help mitigate these impacts. Selection decisions should therefore depend on multi-environment experiments representing a range of temperatures at critical stages of development. Here, we applied a meta-genome wide association analysis (metaGWAS) approach to detect stable QTL with significant effects across multiple environments. The metaGWAS was applied to 11 traits scored in 26 trials that were sown at optimal or late times of sowing (TOS1 and TOS2, respectively) at five locations. A total of 2571 unique wheat genotypes (13,959 genotypes across all environments) were included and the analysis conducted on TOS1, TOS2 and both times of sowing combined (TOS1&2). The germplasm was genotyped using a 90 k Infinium chip and imputed to exome sequence level, resulting in 341,195 single nucleotide polymorphisms (SNPs). The average accuracy across all imputed SNPs was high (92.4%). The three metaGWAS analyses revealed 107 QTL for the 11 traits, of which 16 were detected in all three analyses and 23 were detected in TOS1&2 only. The remaining QTL were detected in either TOS1 or TOS2 with or without TOS1&2, reflecting the complex interactions between the environments and the detected QTL. Eight QTL were associated with grain yield and seven with multiple traits. The identified QTL provide an important resource for gene enrichment and fine mapping to further understand the mechanisms of gene × environment interaction under both heat stressed and unstressed conditions.

Wheat morpho-physiological traits and radiation use efficiency under interactive effects of warming and tillage management

Understanding the interactive effects of different warming levels and tillage managements on crop morphological and physiological traits and radiation use efficiency (RUE) is essential for breeding climate-resilient cultivars. Here, we conducted temperature free-air controlled enhancement (T-FACE) experiments on winter wheat during two growth seasons in the North China Plain. The experiments consisted of three warming treatments and two tillage treatments (CT: conventional tillage and NT: no-tillage). In the normal season, warming had significant positive effects on major morphological and physiological traits and increased significantly RUE of yield (RUE_Y ) and biomass (RUE_DM ) by 13.3 and 11.3%, 19.3 and 12.4%, 42.3 and 43.7%, respectively, under the treatments of CTT1, CTT2 and NTT1 relative to the control (CTN, NTN). By contrast, in the warmer season, warming had negative effects on leaf width, light extinction coefficient, light-saturated net photosynthetic rate, aboveground, stems and spike biomass and RUE from anthesis to maturity, and consequently grain yield under conventional tillage, but positive effects under no-tillage. Our findings bring new insights into the mechanisms on the interactive effects of warming and tillage treatments on wheat growth and productivity; provide valuable information on crop ideotypic traits for breeding climate-resilient crop cultivars.

The Heat is On: How Crop Growth, Development and Yield Respond to High Temperature

Plants are exposed to a wide range of temperatures during their life cycle and need to continuously adapt. These adaptations need to deal with temperature changes on a daily and seasonal level and with temperatures affected by climate change. Increasing global temperatures negatively impact crop performance, and several physiological, biochemical, morphological and developmental responses to increased temperature have been described that allow plants to mitigate this. In this review, we assess various growth, development, and yield-related responses of crops to extreme and moderate high temperature, focusing on knowledge gained from both monocot (e.g. wheat, barley, maize, rice) and dicot crops (e.g. soybean and tomato) and incorporating information from model plants (e.g. Arabidopsis and Brachypodium). This revealed common and different responses between dicot and monocot crops, and defined different temperature thresholds depending on the species, growth stage and organ.

Short-Term Implications of Climate Shocks on Wheat-Based Nutrient Flows: A Global "Nutrition at Risk" Analysis through a Stochastic CGE Model

Food security analyses of international trade largely overlook the importance of substantial heterogeneity and complexity of nutrient content in food products. This paper quantifies the extent to which wheat-based nutrient supplies, including energy, protein, iron, zinc, and magnesium, are exposed to the risks of realistic productivity and trade shocks. By employing a static and stochastic world trade computable general equilibrium (CGE) model, we find that productivity shocks may result in losses in households’ nutrient consumption of up to 18% for protein, 33.1% for zinc, and 37.4% for magnesium. Significant losses are observed in countries mostly in the Middle East, North Africa, and Central Asia. Since the main centers of wheat exports have recently been shifting to former Soviet Union countries, we also simulated the nutritional risks of export restrictions imposed by the Russian Federation, Ukraine, and Kazakhstan, which have resorted to this policy instrument in recent years. We find that partial export restrictions increase the probability of nutrient shocks by five times or more in most countries that we studied. Increased nutrient deficiencies have a range of public health implications in the affected countries, which could be mitigated and/or avoided by adjusting production and trade policies and by targeting high nutritional risk groups, such as women and children. Since the potential implications of supply shocks are diffused across countries through international trade, the stricter regulation of export restrictions to enhance the predictably and reliability of global food supplies is also needed.

Decreased wheat production in the USA from climate change driven by yield losses rather than crop abandonment

An increase in global average surface temperature over the 21st century will affect food production. There is still uncertainty if the source of the production losses caused by climate change could be driven either by lower yield or reduced area harvested. We use county-level production data on winter wheat coupled with fine-scale weather outcomes between 1981-2007 to examine the impact of climate change on winter wheat production in Kansas. We decompose the total impact of weather variables through both the yield and harvested acreage channels. We find that an insignificant portion-both in terms of magnitude and statistical significance-of the production losses are due to reduced harvested acres (i.e., crop abandonment). The proportion harvested only account for 14.88% and 21.71% of the total damages under RCPs 4.5 and 8.5 and neither effect is statistically significant. An implication of this result implies that studies that only examine climate impacts on harvested yields are not significantly underestimating the climate change impacts on production.

Differential responses of anthers of stress tolerant and sensitive wheat cultivars to high temperature stress

Transcriptomic analyses identified anther-expressed genes in wheat likely to contribute to heat tolerance and hence provide useful genetic markers. The genes included those involved in hormone biosynthesis, signal transduction, the heat shock response and anther development. Pollen development is particularly sensitive to high temperature heat stress. In wheat, heat-tolerant and heat-sensitive cultivars have been identified, although the underlying genetic causes for these differences are largely unknown. The effects of heat stress on the developing anthers of two heat-tolerant and two heat-sensitive wheat cultivars were examined in this study. Heat stress (35 °C) was found to disrupt pollen development in the two heat-sensitive wheat cultivars but had no visible effect on pollen or anther development in the two heat-tolerant cultivars. The sensitive anthers exhibited a range of developmental abnormalities including an increase in unfilled and clumped pollen grains, abnormal pollen walls and a decrease in pollen viability. This subsequently led to a greater reduction in grain yield in the sensitive cultivars following heat stress. Transcriptomic analyses of heat-stressed developing wheat anthers of the four cultivars identified a number of key genes which may contribute to heat stress tolerance during pollen development. Orthologs of some of these genes in Arabidopsis and rice are involved in regulation of the heat stress response and the synthesis of auxin, ethylene and gibberellin. These genes constitute candidate molecular markers for the breeding of heat-tolerant wheat lines.

Importance of the description of light interception in crop growth models

Canopy light interception determines the amount of energy captured by a crop, and is thus critical to modeling crop growth and yield, and may substantially contribute to the prediction uncertainty of crop growth models (CGMs). We thus analyzed the canopy light interception models of the 26 wheat (Triticum aestivum) CGMs used by the Agricultural Model Intercomparison and Improvement Project (AgMIP). Twenty-one CGMs assume that the light extinction coefficient (K) is constant, varying from 0.37 to 0.80 depending on the model. The other models take into account the illumination conditions and assume either that all green surfaces in the canopy have the same inclination angle (θ) or that θ distribution follows a spherical distribution. These assumptions have not yet been evaluated due to a lack of experimental data. Therefore, we conducted a field experiment with five cultivars with contrasting leaf stature sown at normal and double row spacing, and analyzed θ distribution in the canopies from three-dimensional canopy reconstructions. In all the canopies, θ distribution was well represented by an ellipsoidal distribution. We thus carried out an intercomparison between the light interception models of the AgMIP-Wheat CGMs ensemble and a physically based K model with ellipsoidal leaf angle distribution and canopy clumping (KellC). Results showed that the KellC model outperformed current approaches under most illumination conditions and that the uncertainty in simulated wheat growth and final grain yield due to light models could be as high as 45%. Therefore, our results call for an overhaul of light interception models in CGMs.

The Potential of Using Chitosan on Cereal Crops in the Face of Climate Change

This review presents the main findings from measurements carried out on cereals using chitosan, its derivatives, and nanoparticles. Research into the use of chitosan in agriculture is growing in popularity. Since 2000, 188 original scientific articles indexed in Web of Science, Scopus, and Google Scholar databases have been published on this topic. These have focused mainly on wheat (34.3%), maize (26.3%), and rice (24.2%). It was shown that research on other cereals such as millets and sorghum is scarce and should be expanded to better understand the impact of chitosan use. This review demonstrates that this chitosan is highly effective against the most dangerous diseases and pathogens for cereals. Furthermore, it also contributes to improving yield and chlorophyll content, as well as some plant growth parameters. Additionally, it induces excellent resistance to drought, salt, and low temperature stress and reduces their negative impact on cereals. However, further studies are needed to demonstrate the full field efficacy of chitosan.

High-resolution spectral information enables phenotyping of leaf epicuticular wax in wheat

BACKGROUND

Epicuticular wax (EW) is the first line of defense in plants for protection against biotic and abiotic factors in the environment. In wheat, EW is associated with resilience to heat and drought stress, however, the current limitations on phenotyping EW restrict the integration of this secondary trait into wheat breeding pipelines. In this study we evaluated the use of light reflectance as a proxy for EW load and developed an efficient indirect method for the selection of genotypes with high EW density.

RESULTS

Cuticular waxes affect the light that is reflected, absorbed and transmitted by plants. The narrow spectral regions statistically associated with EW overlap with bands linked to photosynthetic radiation (500 nm), carotenoid absorbance (400 nm) and water content (~ 900 nm) in plants. The narrow spectral indices developed predicted 65% (EWI-13) and 44% (EWI-1) of the variation in this trait utilizing single-leaf reflectance. However, the normalized difference indices EWI-4 and EWI-9 improved the phenotyping efficiency with canopy reflectance across all field experimental trials. Indirect selection for EW with EWI-4 and EWI-9 led to a selection efficiency of 70% compared to phenotyping with the chemical method. The regression model EWM-7 integrated eight narrow wavelengths and accurately predicted 71% of the variation in the EW load (mg·dm-2) with leaf reflectance, but under field conditions, a single-wavelength model consistently estimated EW with an average RMSE of 1.24 mg·dm-2 utilizing ground and aerial canopy reflectance.

CONCLUSIONS

Overall, the indices EWI-1, EWI-13 and the model EWM-7 are reliable tools for indirect selection for EW based on leaf reflectance, and the indices EWI-4, EWI-9 and the model EWM-1 are reliable for selection based on canopy reflectance. However, further research is needed to define how the background effects and geometry of the canopy impact the accuracy of these phenotyping methods.

Water Quality Threats, Perceptions of Climate Change and Behavioral Responses among Farmers in the Ethiopian Rift Valley

This work aims to assess water quality for irrigated agriculture, alongside perceptions and adaptations of farmers to climate change in the Main Ethiopian Rift (MER). Climate change is expected to cause a rise in temperature and variability in rainfall in the region, reducing surface water availability and raising dependence on groundwater. The study data come from surveys with 147 farmers living in the Ziway–Shala basin and water quality assessments of 162 samples from groundwater wells and surface water. Most groundwater samples were found to be unsuitable for long term agricultural use due to their high salinity and sodium adsorption ratio, which has implications for soil permeability, as well as elevated bicarbonate, boron and residual sodium carbonate concentrations. The survey data indicate that water sufficiency is a major concern for farmers that leads to frequent crop failures, especially due to erratic and insufficient rainfall. An important adaptation mechanism for farmers is the use of improved crop varieties, but major barriers to adaptation include a lack of access to irrigation water, credit or savings, appropriate seeds, and knowledge or information on weather and climate conditions. Local (development) agents are identified as vital to enhancing farmers’ knowledge of risks and solutions, and extension programs must therefore continue to promote resilience and adaptation in the area. Unfortunately, much of the MER groundwater that could be used to cope with declining viability of rainfed agriculture and surface water availability, is poor in quality. The use of saline groundwater could jeopardize the agricultural sector, and most notably commercial horticulture and floriculture activities. This study highlights the complex nexus of water quality and sufficiency challenges facing the agriculture sector in the region, and should help decision-makers to design feasible strategies for enhancing adaptation and food security.

The Occurrence of Mycotoxins in Raw Materials and Fish Feeds in Europe and the Potential Effects of Deoxynivalenol (DON) on the Health and Growth of Farmed Fish Species-A Review

The first part of this study evaluates the occurrence of mycotoxin patterns in feedstuffs and fish feeds. Results were extrapolated from a large data pool derived from wheat (n = 857), corn (n = 725), soybean meal (n = 139) and fish feed (n = 44) samples in European countries and based on sample analyses by liquid chromatography/tandem mass spectrometry (LC-MS/MS) in the period between 2012-2019. Deoxynivalenol (DON) was readily present in corn (in 47% of the samples) > wheat (41%) > soybean meal (11%), and in aquafeeds (48%). Co-occurrence of mycotoxins was frequently observed in feedstuffs and aquafeed samples. For example, in corn, multi-mycotoxin occurrence was investigated by Spearman's correlations and odd ratios, and both showed co-occurrence of DON with its acetylated forms (3-AcDON, 15-AcDON) as well as with zearalenone (ZEN). The second part of this study summarizes the existing knowledge on the effects of DON on farmed fish species and evaluates the risk of DON exposure in fish, based on data from in vivo studies. A meta-analytical approach aimed to estimate to which extent DON affects feed intake and growth performance in fish. Corn was identified as the ingredient with the highest risk of contamination with DON and its acetylated forms, which often cannot be detected by commonly used rapid detection methods in feed mills. Periodical state-of-the-art mycotoxin analyses are essential to detect the full spectrum of mycotoxins in fish feeds aimed to prevent detrimental effects on farmed fish and subsequent economic losses for fish farmers. Because levels below the stated regulatory limits can reduce feed intake and growth performance, our results show that the risk of DON contamination is underestimated in the aquaculture industry.

Wheat root systems as a breeding target for climate resilience

In the coming decades, larger genetic gains in yield will be necessary to meet projected demand, and this must be achieved despite the destabilizing impacts of climate change on crop production. The root systems of crops capture the water and nutrients needed to support crop growth, and improved root systems tailored to the challenges of specific agricultural environments could improve climate resiliency. Each component of root initiation, growth and development is controlled genetically and responds to the environment, which translates to a complex quantitative system to navigate for the breeder, but also a world of opportunity given the right tools. In this review, we argue that it is important to know more about the 'hidden half' of crop plants and hypothesize that crop improvement could be further enhanced using approaches that directly target selection for root system architecture. To explore these issues, we focus predominantly on bread wheat (Triticum aestivum L.), a staple crop that plays a major role in underpinning global food security. We review the tools available for root phenotyping under controlled and field conditions and the use of these platforms alongside modern genetics and genomics resources to dissect the genetic architecture controlling the wheat root system. To contextualize these advances for applied wheat breeding, we explore questions surrounding which root system architectures should be selected for, which agricultural environments and genetic trait configurations of breeding populations are these best suited to, and how might direct selection for these root ideotypes be implemented in practice.

The impact of weather and increased atmospheric CO2 from 1892 to 2016 on simulated yields of UK wheat

Climate change effects on UK winter wheat grain yield are complex: warmer temperature, negative; greater carbon dioxide (CO2) concentration, positive; but other environmental variables and their timing also affect yield. In the absence of long-term experiments where temperature and CO2 concentration were manipulated separately, we applied the crop simulation model Sirius with long-term daily meteorological data (1892-2016) for Rothamsted, Hertfordshire, UK (2007-2016 mean growing season temperature 1.03°C warmer than 1892-1991), and CO2 concentration over this period, to investigate the separate effects of historic CO2 and weather on simulated grain yield in three wheat cultivars of the modern era. We show a slight decline in simulated yield over the period 1892-2016 from the effect of weather (daily temperature, rainfall and sunshine hours) at fixed CO2 (294.50 ppm, 1892 reference value), but a maximum 9.4% increase when accounting for increasing atmospheric CO2 (from 294.50 to 404.21 ppm), differing slightly among cultivars. Notwithstanding considerable inter-annual variation, the slight yield decline at 294.50 ppm CO2 over this 125-year period from the historic weather simulations for Rothamsted agrees with the expected decline from temperature increase alone, but the positive yield trend with actual CO2 values does not match the recent stagnation in UK wheat yield.

Cloning, expression analysis and In silico characterization of HSP101: a potential player conferring heat stress in Aegilops speltoides (Tausch) Gren

Heat shock protein (HSP101) function as molecular chaperones and confer thermotolerance to plants. In the present investigation, identification, comprehensive expression analysis, phylogeny and protein modelling of HSP101 gene has been done in Aegilops speltoides accession Pau3583. In the present study, we cloned and in silico characterized a HSP101C gene designated as AsHSP101C-Pau3583. AsHSP101C-Pau3583 is 4180 bp long with seven exons and six introns and encoded a polypeptide of 910 amino acids predicted by FGENESH. We have identified 58 SNPs between the AsHSP101C-Pau3583 and reference gene sequence extracted from Ae. speltoides TGAC assembly. Real-time RT-PCR analysis of expression levels of HSP101 gene in two wheat genotypes under heat stress revealed that gene namely HSP101C was up-regulated in Aegilops speltoides acc. Pau3583 by > fourfold in comparison to Triticum aestivum cv. PBW343 under heat stress signifies that it plays a role in conferring heat tolerance. Sequence comparison and phylogenetic analysis of AsHSP101C-Pau3583 with seven wheat homologs Triticum aestivum, Aegilops speltoides (TGAC), Triticum durum cv Cappelli, Triticum durum cv Strongfield, Triticum monococcum, Aegilops tauschii and Triticum urartu showed significant similarities with highly conserved coding regions and functional domains (AAA, AAA + 2, ClpB domains), suggesting the conserved function of HSP101C in different species. The illustration of the protein models of HSP101C in homologs provided information for the ATP-binding motifs within the nucleotide binding domains (NBD), specific for the chaperone activity. These findings are important and identified SNPs could be used for designing markers for ensuring the transfer of AsHSP101C-Pau3583 gene into hexaploid wheat and its role in heat tolerance.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01005-2.

Hotter, drier, CRISPR: the latest edit on climate change

Integrating CRISPR/Cas9 genome editing into modern breeding programs for crop improvement in cereals. Global climate trends in many agricultural regions have been rapidly changing over the past decades, and major advances in global food systems are required to ensure food security in the face of these emerging challenges. With increasing climate instability due to warmer temperatures and rising CO₂ levels, the productivity of global agriculture will continue to be negatively impacted. To combat these growing concerns, creative approaches will be required, utilising all the tools available to produce more robust and tolerant crops with increased quality and yields under more extreme conditions. The integration of genome editing and transgenics into current breeding strategies is one promising solution to accelerate genetic gains through targeted genetic modifications, producing crops that can overcome the shifting climate realities. This review focuses on how revolutionary genome editing tools can be directly implemented into breeding programs for cereal crop improvement to rapidly counteract many of the issues affecting agriculture production in the years to come.

Gaining Acceptance of Novel Plant Breeding Technologies

Ensuring the sustainability of agriculture under climate change has led to a surge in alternative strategies for crop improvement. Advances in integrated crop breeding, social acceptance, and farm-level adoption are crucial to address future challenges to food security. Societal acceptance can be slow when consumers do not see the need for innovation or immediate benefits. We consider how best to address the issue of social licence and harmonised governance for novel gene technologies in plant breeding. In addition, we highlight optimised breeding strategies that will enable long-term genetic gains to be achieved. Promoted by harmonised global policy change, innovative plant breeding can realise high and sustainable productivity together with enhanced nutritional traits.

Regions of Chromosome 2A of Bread Wheat (Triticum aestivum L.) Associated with Variation in Physiological and Agronomical Traits under Contrasting Water Regimes

Understanding the genetic architecture of drought tolerance is of great importance for overcoming the negative impact of drought on wheat yield. Earlier, we discovered the critical role of chromosome 2A for the drought-tolerant status of wheat spring cultivar Saratovskaya 29. A set of 92 single-chromosome recombinant double haploid (SCRDH) lines were obtained in the genetic background of Saratovskaya 29. The lines carry fragments of chromosome 2A from the drought-sensitive cultivar Yanetzkis Probat. The SCRDH lines were used to identify regions on chromosome 2A associated with the manifestation of physiological and agronomical traits under distinct water supply, and to identify candidate genes that may be associated with adaptive gene networks in wheat. Genotyping was done with Illumina Infinium 15k wheat array using 590 SNP markers with 146 markers being polymorphic. In four identified regions of chromosome 2A, 53 out of 58 QTLs associated with physiological and agronomic traits under contrasting water supply were mapped. Thirty-nine candidate genes were identified, of which 18 were transcription factors. The region 73.8-78.1 cM included the largest number of QTLs and candidate genes. The variation in SNPs associated with agronomical and physiological traits revealed among the SCRDH lines may provide useful information for drought related marker-assisted breeding.

Crop Yield Prediction Based on Agrometeorological Indexes and Remote Sensing Data

Timely and reliable estimations of crop yield are essential for crop management and successful food trade. In previous studies, remote sensing data or climate data are often used alone in statistical yield estimation models. In this study, we synthetically used agrometeorological indicators and remote sensing vegetation parameters to estimate maize yield in Jilin and Liaoning Provinces of China. We applied two methods to select input variables, used the random forest method to establish yield estimation models, and verified the accuracy of the models in three disaster years (1997, 2000, and 2001). The results show that the R2 values of the eight yield estimation models established in the two provinces were all above 0.7, Lin’s concordance correlation coefficients were all above 0.84, and the mean absolute relative errors were all below 0.14. The mean absolute relative error of the yield estimations in the three disaster years was 0.12 in Jilin Province and 0.13 in Liaoning Province. A model built using variables selected by a two-stage importance evaluation method can obtain a better accuracy with fewer variables. The final yield estimation model of Jilin province adopts eight independent variables, and the final yield estimation model of Liaoning Province adopts nine independent variables. Among the 11 adopted variables in two provinces, ATT (accumulated temperature above 10 °C) variables accounted for the highest proportion (54.54%). In addition, the GPP (gross primary production) anomaly in August, NDVI (Normalized Difference Vegetation Index) anomaly in August, and standardized precipitation index with a two-month scale in July were selected as important modeling variables by all methods in the two provinces. This study provides a reference method for the selection of modeling variables, and the results are helpful for understanding the impact of climate on potential yield.

Climate risks and adaptation strategies of farmers in East Africa and South Asia

Understanding major climate risks, adaptation strategies, and factors influencing the choice of those strategies is crucial to reduce farmers’ vulnerability. Employing comprehensive data from 2822 farm households in Ethiopia and Kenya (East Africa; EA) and 1902 farm households in Bangladesh, India, and Nepal (South Asia; SA), this study investigates the main climate risks that farmers faced and the adaptation strategies they used. Among others, excessive rainfall and heightened crop pest/disease incidence are commonly observed climate-induced risks in all study areas, while cyclones and salinity are unique to Bangladesh. Drought is prevalent in Ethiopia, India, Kenya, and Nepal. Farmers in those countries responded with strategies that include change in farming practices, sustainable land management, reduce consumption, sell assets, use savings and borrowings, seek alternative employment and assistance from government or NGO. In general, farmers faced several multiple climate risks simultaneously and they responded with multiple adaptation strategies. Therefore, this study used a multivariate probit (MVP) approach to examine the factors influencing the adoption of adaptation strategies. Unlike other studies, we also tested and corrected for possible endogeneity in model estimation. All the countries mentioned have low adaptive capacity to address climate change, which is further weakened by inadequate governance and inefficient institutions. We observed significant differences in the choice of adaptation strategies between male-headed households (MHHs) and female-headed households (FHHs), as well as across countries. Generally, MHHs are more likely to seek additional employment and change agricultural practices, while FHHs and households headed by older persons tend to reduce consumption and rely on savings and borrowings. Institutional support for adaptation is much less in EA compared to SA. Training on alternative farming practices, enhancing non-farm employment options, better institutional support, and social security for older farmers are crucial for climate change adaptation in both regions.

Understanding climate-risk coping strategies among farm households: Evidence from five countries in Eastern and Southern Africa

Climate change is having a catastrophic impact on the livelihoods of farm households in Eastern and Southern Africa (ESA). This study employs comprehensive data obtained in 2018 from 4351 farm households in five countries to appraise the key climate hazards experienced by farmers, the risk coping methods adopted, and factor influencing the use of these methods. Although droughts, floods, hailstorms, and crop pests/diseases are major climate-induced risks in ESA, droughts are predominant in all these countries. Farm households in ESA have adopted various strategies to address climate risk, which includes changing farming practices, reducing consumption, using savings and borrowing, and seeking new employment. Farming families headed by a female, married, or an elderly member opt to change farming methods and decrease consumption, whereas they are less inclined to look for alternate livelihood options. Farming families with higher livestock endowments commonly use savings or borrow and are unlikely to change farming methods, decrease consumption, and search for alternate employment. Better-off families tend to change farming methods but are unlikely to adopt other risk coping options. Farming families with non-farm livelihood options are unlikely to change farming methods, use savings/borrowings, or decrease consumption, whereas they tend to search for alternate employment. Training on agriculture and economic status are crucial for climate change adaptation in these regions. Findings exhibit substantial differences among the study countries regarding the adoption of coping strategies. Compared to farmers in Kenya, farmers in other countries change agricultural methods to cope with climate shocks. Ethiopian farmers, compared to their Kenyan counterparts, decrease consumption to deal with climate risks, whereas, farmers in Tanzania, Malawi, and Mozambique are less likely to use this option. Similarly, the likelihood of seeking alternative employment as a risk coping strategy is lower among Ethiopian farmers, while it is higher among the farmers in other countries.

Field-based remote sensing models predict radiation use efficiency in wheat

Wheat yields are stagnating or declining in many regions, requiring efforts to improve the light conversion efficiency, known as radiation use efficiency (RUE). RUE is a key trait in plant physiology because it links light capture and primary metabolism with biomass accumulation and yield, but its measurement is time consuming and this has limited its use in fundamental research and large-scale physiological breeding. In this study, high-throughput plant phenotyping (HTPP) approaches were used among a population of field-grown wheat with variation in RUE and photosynthetic traits to build predictive models of RUE, biomass, and intercepted photosynthetically active radiation (IPAR). Three approaches were used: best combination of sensors; canopy vegetation indices; and partial least squares regression. The use of remote sensing models predicted RUE with up to 70% accuracy compared with ground truth data. Water indices and canopy greenness indices [normalized difference vegetation index (NDVI), enhanced vegetation index (EVI)] are the better option to predict RUE, biomass, and IPAR, and indices related to gas exchange, non-photochemical quenching [photochemical reflectance index (PRI)] and senescence [structural-insensitive pigment index (SIPI)] are better predictors for these traits at the vegetative and grain-filling stages, respectively. These models will be instrumental to explain canopy processes, improve crop growth and yield modelling, and potentially be used to predict RUE in different crops or ecosystems.

Wheat heat tolerance is impaired by heightened deletions in the distal end of 4AL chromosomal arm

Heat stress (HS) causes substantial damages to worldwide crop production. As a cool season crop, wheat (Triticum aestivum) is sensitive to HS-induced damages. To support the genetic improvement of wheat HS tolerance (HST), we conducted fine mapping of TaHST1, a locus required for maintaining wheat vegetative and reproductive growth under elevated temperatures. TaHST1 was mapped to the distal terminus of 4AL chromosome arm using genetic populations derived from two BC₆ F₆ breeding lines showing tolerance (E6015-4T) or sensitivity (E6015-3S) to HS. The 4AL region carrying TaHST1 locus was approximately 0.949 Mbp and contained the last 19 high confidence genes of 4AL according to wheat reference genome sequence. Resequencing of E6015-3S and E6015-4T and haplotype analysis of 3087 worldwide wheat accessions revealed heightened deletion polymorphisms in the distal 0.949 Mbp region of 4AL, which was confirmed by the finding of frequent gene losses in this region in eight genome-sequenced hexaploid wheat cultivars. The great majority (86.36%) of the 3087 lines displayed different degrees of nucleotide sequence deletions, with only 13.64% of them resembling E6015-4T in this region. These deletions can impair the presence and/or function of TaHST1 and surrounding genes, thus rendering global wheat germplasm vulnerable to HS or other environmental adversities. Therefore, conscientious and urgent efforts are needed in global wheat breeding programmes to optimize the structure and function of 4AL distal terminus by ensuring the presence of TaHST1 and surrounding genes. The new information reported here will help to accelerate the ongoing global efforts in improving wheat HST.

Climate change risks pushing one-third of global food production outside the safe climatic space

Food production on our planet is dominantly based on agricultural practices developed during stable Holocene climatic conditions. Although it is widely accepted that climate change perturbs these conditions, no systematic understanding exists on where and how the major risks for entering unprecedented conditions may occur. Here, we address this gap by introducing the concept of safe climatic space (SCS), which incorporates the decisive climatic factors of agricultural production: precipitation, temperature, and aridity. We show that a rapid and unhalted growth of greenhouse gas emissions (SSP5-8.5) could force 31% of the global food crop and 34% of livestock production beyond the SCS by 2081-2100. The most vulnerable areas are South and Southeast Asia and Africa's Sudano-Sahelian Zone, which have low resilience to cope with these changes. Our results underpin the importance of committing to a low-emissions scenario (SSP1-2.6), whereupon the extent of food production facing unprecedented conditions would be a fraction.

Greenhouse gas emissions intensity of food production systems and its determinants

It is estimated that about 1/4th of all greenhouse gas (GHG) emissions may be caused by the global food system. Reducing the GHG emissions from food production is a major challenge in the context of the projected growth of the world's population, which is increasing demand for food. In this context, the goal should be to achieve the lowest possible emission intensity of the food production system, understood as the amount of GHG emissions per unit of output. The study aimed to calculate the emission intensity of food production systems and to specify its determinants based on a panel regression model for 14 countries, which accounted for more than 65% of food production in the world between 2000 and 2014. In this article, emission intensity is defined as the amount of GHG emissions per value of global output. Research on the determinants of GHG emissions related to food production is well documented in the literature; however, there is a lack of research on the determinants of the emission intensity ratio for food production. Hence, the original contribution of this paper is the analysis of the determinants of GHG emissions intensity of food production systems. The study found the decreased of emission intensity from an average of more than 0.68 kg of CO2 equivalent per USD 1 worth of food production global output in 2000 to less than 0.46 in 2014. The determinants of emission intensity decrease included the yield of cereals, the use of nitrogen fertilizers, the agriculture material intensity, the Human Development Index, and the share of fossil fuel energy consumption in total energy use. The determinants of growth of emission intensity of food production systems included GDP per capita, population density, nitrogen fertilizer production, utilized agriculture area, share of animal production, and energy use per capita.

Shortened key growth periods of soybean observed in China under climate change

Phenology is an important indicator of global climate change. Revealing the spatiotemporal characteristics of crop phenology is vital for ameliorating the adverse effects of climate change and guiding regional agricultural production. This study evaluated the spatiotemporal variability of soybean's phenological stages and key growth periods, and assessed their sensitivity to key climatic factors, utilizing a long-term dataset (1992-2018) of soybean phenology and associated meteorological data collected at 51 stations across China. The results showed that (1) during the soybean growing seasons from 1992 to 2018, the average temperature (0.34 ± 0.09 ℃ decade-1) and cumulative precipitation (6.66 ± 0.93 mm decade-1) increased, but cumulative sunshine hours (- 33.98 ± 1.05 h decade-1) decreased. (2) On a national scale, dates of sowing, emergence, trifoliate, anthesis, and podding of soybean were delayed, while the maturity date showed an advancing trend. The vegetative growth period (- 0.52 ± 0.24 days decade-1) and whole growth period (- 1.32 ± 0.30 days decade-1) of soybean were shortened, but the reproductive growth period (0.05 ± 0.26 days decade-1) was slightly extended. Trends in soybean phenological stages and key growth periods diverged in regions. Soybean phenological stages were delayed in Huang-Huai-Hai soybean zone, whereas advanced in southern soybean zone. Moreover, the key growth periods were greatly shortened in northern soybean zone. (3) In general, the sensitivity of soybean key growth periods to temperature was negative, whereas those to precipitation and sunshine hours differed among regions. In particular, most phenological stages were negatively sensitive to sunshine hours. Our results will provide scientific support for decision-making in agricultural production practices.

Evaluation and Dietary Exposure Assessment of Selected Toxic Trace Elements in Durum Wheat (Triticum durum) Imported into the Italian Market: Six Years of Official Controls

Durum wheat grains, which are mostly used for the production of pasta and several baked goods, represent a main source of vegetable proteins and calories. Concurrently, many contaminants, including toxic trace elements, may accumulate in them, posing a potential severe hazard to human health. In this context, for official control and food safety purposes, 346 samples of whole durum wheat imported into the Italian market from six countries (Australia, Canada, Kazakhstan, Russia, Turkey, and the United States) during the period 2015-2020 were analysed for cadmium (Cd), lead (Pb), and mercury (Hg) content using inductively coupled plasma mass spectrometry (ICP-MS). All the analysed samples were compliant with Food Agriculture Organization-World Health Organization and European Union regulations. The mean values were 0.0322 and 0.0162 mg kg-1, respectively, for Cd and Pb, while all samples showed levels below the limit of detection (0.004 mg kg-1) for Hg. The results were construed in terms of seasonality, year, and country of production, and compared with reference tolerance values. Confirming previous exposure studies, the obtained data and the dietary intake assessment showed that durum wheat-based products may have a significant impact on exposure to Pb and Cd (20-50%) in the overall population, particularly in more sensitive and/or exposed subgroups (infants, toddlers, and females).

The effect of increasing temperature on crop photosynthesis: from enzymes to ecosystems

As global land surface temperature continues to rise and heatwave events increase in frequency, duration, and/or intensity, our key food and fuel cropping systems will likely face increased heat-related stress. A large volume of literature exists on exploring measured and modelled impacts of rising temperature on crop photosynthesis, from enzymatic responses within the leaf up to larger ecosystem-scale responses that reflect seasonal and interannual crop responses to heat. This review discusses (i) how crop photosynthesis changes with temperature at the enzymatic scale within the leaf; (ii) how stomata and plant transport systems are affected by temperature; (iii) what features make a plant susceptible or tolerant to elevated temperature and heat stress; and (iv) how these temperature and heat effects compound at the ecosystem scale to affect crop yields. Throughout the review, we identify current advancements and future research trajectories that are needed to make our cropping systems more resilient to rising temperature and heat stress, which are both projected to occur due to current global fossil fuel emissions.

Expression of seed storage proteins responsible for maintaining kernel traits and wheat flour quality in common wheat under heat stress conditions

Heat stress during grain filling has been documented to decrease wheat grain yield and quality in arid regions worldwide. We studied the effect of heat stress on wheat flour quality in heat tolerant cultivars to define the effects of heat stress on flour quality and to identify germplasm combining traits for heat tolerance and good flour quality. We studied the kernel phenotypic traits, the expression of seed storage proteins (SSPs), and the resulting flour quality under heat and normal conditions. Under heat stress, all cultivars yielded narrow-shaped seeds, and increased protein contents as compared to the control plants grown under normal conditions. The specific sedimentation values used to estimate the gluten quality varied between cultivars. We identified cultivars that could maintain good flour quality under heat stress conditions: 'Imam', which possessed the Glu-D1d allele responsible for the suitable bread-making; 'Bohaine', which displayed high expression level of SSPs; and 'Condor', which possessed slight variations in the ratio of each SSP under heat stress conditions. Combining the desirable traits from these cultivars could yield a wheat cultivar with heat tolerance and good flour quality.

Impact of elevated CO2 and heat stress on wheat pollen viability and grain production

Periods of high temperature and an expected increase in atmospheric CO2 concentration as a result of global climate change are major threats to wheat (Triticum aestivum L.) production. Developing heat-tolerant wheat cultivars demands improved understanding of the impacts of high temperature and elevated CO2 on plant growth and development. This research investigated the interactive effects of heat stress and CO2 concentration on pollen viability and its relationship to grain formation and yield of wheat in greenhouse conditions. Nineteen wheat genotypes and a current cultivar, Suntop, were heat stressed at either meiosis or anthesis at ambient (400 µL L-1) or elevated (800 µL L-1) CO2. Elevated CO2 and heat stress at meiosis reduced pollen viability, spikelet number and grain yield per spike; however, increased tillering at the elevated CO2 level helped to minimise yield loss. Both heat-tolerant genotypes (e.g. genotype 1, 2, 10 or 12) and heat-sensitive genotypes (e.g. genotype 6 or 9) were identified and response related to pollen sensitivity and subsequent impacts on grain yield and yield components were characterised. A high-throughput protocol for screening wheat for heat stress response at elevated CO2 was established and meiosis was the most sensitive stage, affecting pollen viability, grain formation and yield.

Robust modeling of additive and nonadditive variation with intuitive inclusion of expert knowledge

We propose a novel Bayesian approach that robustifies genomic modeling by leveraging expert knowledge (EK) through prior distributions. The central component is the hierarchical decomposition of phenotypic variation into additive and nonadditive genetic variation, which leads to an intuitive model parameterization that can be visualized as a tree. The edges of the tree represent ratios of variances, for example broad-sense heritability, which are quantities for which EK is natural to exist. Penalized complexity priors are defined for all edges of the tree in a bottom-up procedure that respects the model structure and incorporates EK through all levels. We investigate models with different sources of variation and compare the performance of different priors implementing varying amounts of EK in the context of plant breeding. A simulation study shows that the proposed priors implementing EK improve the robustness of genomic modeling and the selection of the genetically best individuals in a breeding program. We observe this improvement in both variety selection on genetic values and parent selection on additive values; the variety selection benefited the most. In a real case study, EK increases phenotype prediction accuracy for cases in which the standard maximum likelihood approach did not find optimal estimates for the variance components. Finally, we discuss the importance of EK priors for genomic modeling and breeding, and point to future research areas of easy-to-use and parsimonious priors in genomic modeling.

Robust modeling of additive and nonadditive variation with intuitive inclusion of expert knowledge

We propose a novel Bayesian approach that robustifies genomic modeling by leveraging expert knowledge (EK) through prior distributions. The central component is the hierarchical decomposition of phenotypic variation into additive and nonadditive genetic variation, which leads to an intuitive model parameterization that can be visualized as a tree. The edges of the tree represent ratios of variances, for example broad-sense heritability, which are quantities for which EK is natural to exist. Penalized complexity priors are defined for all edges of the tree in a bottom-up procedure that respects the model structure and incorporates EK through all levels. We investigate models with different sources of variation and compare the performance of different priors implementing varying amounts of EK in the context of plant breeding. A simulation study shows that the proposed priors implementing EK improve the robustness of genomic modeling and the selection of the genetically best individuals in a breeding program. We observe this improvement in both variety selection on genetic values and parent selection on additive values; the variety selection benefited the most. In a real case study, EK increases phenotype prediction accuracy for cases in which the standard maximum likelihood approach did not find optimal estimates for the variance components. Finally, we discuss the importance of EK priors for genomic modeling and breeding, and point to future research areas of easy-to-use and parsimonious priors in genomic modeling.

The WtmsDW Locus on Wheat Chromosome 2B Controls Major Natural Variation for Floret Sterility Responses to Heat Stress at Booting Stage

Heat stress at booting stage causes significant losses to floret fertility (grain set) and hence yield in wheat (Triticum aestivum L.); however, there is a lack of well-characterized sources of tolerance to this type of stress. Here, we describe the genetic analysis of booting stage heat tolerance in a cross between the Australian cultivars Drysdale (intolerant) and Waagan (tolerant), leading to the definition of a major-effect tolerance locus on the short arm of chromosome 2B, Wheat thermosensitive male sterile Drysdale/Waagan (WtmsDW). WtmsDW offsets between 44 and 65% of the losses in grain set due to heat, suggesting that it offers significant value for marker-assisted tolerance breeding. In lines lacking the WtmsDW tolerance allele, peaks in sensitivity were defined with reference to auricle distance, for various floret positions along the spike. Other (relatively minor) floret fertility response effects, including at the Rht-D1 dwarfing locus, were considered likely escape artifacts, due to their association with height and flowering time effects that might interfere with correct staging of stems for heat treatment. Heat stress increased grain set at distal floret positions in spikelets located at the top of the spike and increased the size of spikelets at the base of the spike, but these effects were offset by greater reductions in grain set at other floret positions. Potentially orthologous loci on chromosomes 1A and 1B were identified for heat response of flowering time. The potential significance of these findings for tolerance breeding and further tolerance screening is discussed.

The WtmsDW Locus on Wheat Chromosome 2B Controls Major Natural Variation for Floret Sterility Responses to Heat Stress at Booting Stage

Heat stress at booting stage causes significant losses to floret fertility (grain set) and hence yield in wheat (Triticum aestivum L.); however, there is a lack of well-characterized sources of tolerance to this type of stress. Here, we describe the genetic analysis of booting stage heat tolerance in a cross between the Australian cultivars Drysdale (intolerant) and Waagan (tolerant), leading to the definition of a major-effect tolerance locus on the short arm of chromosome 2B, Wheat thermosensitive male sterile Drysdale/Waagan (WtmsDW). WtmsDW offsets between 44 and 65% of the losses in grain set due to heat, suggesting that it offers significant value for marker-assisted tolerance breeding. In lines lacking the WtmsDW tolerance allele, peaks in sensitivity were defined with reference to auricle distance, for various floret positions along the spike. Other (relatively minor) floret fertility response effects, including at the Rht-D1 dwarfing locus, were considered likely escape artifacts, due to their association with height and flowering time effects that might interfere with correct staging of stems for heat treatment. Heat stress increased grain set at distal floret positions in spikelets located at the top of the spike and increased the size of spikelets at the base of the spike, but these effects were offset by greater reductions in grain set at other floret positions. Potentially orthologous loci on chromosomes 1A and 1B were identified for heat response of flowering time. The potential significance of these findings for tolerance breeding and further tolerance screening is discussed.

Effects of Heat Stress on Growth, Physiology of Plants, Yield and Grain Quality of Different Spring Wheat (Triticum aestivum L.) Genotypes

Heat stress is one of the major threats to wheat production in many wheat-growing areas of the world as it causes severe yield loss at the reproductive stage. In the current study, 28 crosses were developed using 11 parental lines, including 7 female lines and 4 male testers following line × tester matting design in 2018–2019. Twenty-eight crosses along with their 11 parental lines were sown in a randomized complete block design in triplicate under optimal and heat stress conditions. Fifteen different morpho-physiological and grain quality parameters were recorded at different growth stages. Analysis of variance illustrated the presence of highly significant differences among wheat genotypes for all traits under both optimal and heat stress conditions. The results of combining ability unveiled the predominant role of non-additive gene action in the inheritance of almost all the studied traits under both conditions. Among parents, 3 parental lines WL-27, WT-39, and WL-57 showed good combining ability under both normal and heat stress conditions. Among crosses, WL-8 × WT-17, WL-37 × WT-17, WL-7 × WT-39, and WL-37 × WT-39 portrayed the highest specific combining ability effects for grain yield and its related traits under optimal as well as heat stress conditions. Biplot and cluster analysis confirmed the results of general and specific combining ability by showing that these wheat crosses belonged to a highly productive and heat tolerant cluster. Correlation analysis revealed a significantly positive correlation of grain yield with net photosynthetic rate, thousand-grain rate, and the number of grains per spike. The designated parental lines and their crosses were selected for future breeding programs in the development of heat resilient, climate-smart wheat genotypes.