Rising temperatures reduce global wheat production

Impact of Climate Change on the Yield and Water Footprint of Winter Wheat in the Haihe River Basin, China

Climate change can impact the yield and water footprint of crops. Therefore, assessing such impacts carries great significance for regional water and food security. This study validated and verified the variety parameters of winter wheat for the Decision Support System for Agrotechnology Transfer (DSSAT) model, using the long-term (1993–2013) growth and yield data observed from six agricultural experiment stations in the Haihe River Basin (HRB), China. The growth process was simulated under three representative concentration pathways (RCPs), named RCP2.6, RCP4.5, and RCP8.5—climate scenarios driven by the HadGEM2-ES model. The variety parameters of winter wheat showed high accuracy in the simulation of the anthesis and maturity dates, and could be used for long-term prediction of the growth process. The trends of climate change had positive impacts on the water footprint of winter wheat but adverse impacts on the yield. The growing period was shortened by 3.6 days, 4.7 days, and 5.0 days per decade in the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, due to the rapid accumulation of heat. The yield would be increased in lower emissions scenarios (17% in RCP2.6), but decreased in high-emissions scenarios due to high temperatures, which may restrict the growth of wheat. The water footprint was decreased by 10%, 11%, and 13% in the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, indicating that the water-use efficiency could be improved in the future. The results showed broad application prospects of the DSSAT model in simulating the response of crop growth to climate change.

Mining the Vavilov wheat diversity panel for new sources of adult plant resistance to stripe rust

Multi-year evaluation of the Vavilov wheat diversity panel identified new sources of adult plant resistance to stripe rust. Genome-wide association studies revealed the key genomic regions influencing resistance, including seven novel loci. Wheat stripe rust (YR) caused by Puccinia striiformis f. sp. tritici (Pst) poses a significant threat to global food security. Resistance genes commonly found in many wheat varieties have been rendered ineffective due to the rapid evolution of the pathogen. To identify novel sources of adult plant resistance (APR), 292 accessions from the N.I. Vavilov Institute of Plant Genetic Resources, Saint Petersburg, Russia, were screened for known APR genes (i.e. Yr18, Yr29, Yr46, Yr33, Yr39 and Yr59) using linked polymerase chain reaction (PCR) molecular markers. Accessions were evaluated against Pst (pathotype 134 E16 A + Yr17 + Yr27) at seedling and adult plant stages across multiple years (2014, 2015 and 2016) in Australia. Phenotypic analyses identified 132 lines that potentially carry novel sources of APR to YR. Genome-wide association studies (GWAS) identified 68 significant marker-trait associations (P < 0.001) for YR resistance, representing 47 independent quantitative trait loci (QTL) regions. Fourteen genomic regions overlapped with previously reported Yr genes, including Yr29, Yr56, Yr5, Yr43, Yr57, Yr30, Yr46, Yr47, Yr35, Yr36, Yrxy1, Yr59, Yr52 and YrYL. In total, seven QTL (positioned on chromosomes 1D, 2A, 3A, 3D, 5D, 7B and 7D) did not collocate with previously reported genes or QTL, indicating the presence of promising novel resistance factors. Overall, the Vavilov diversity panel provides a rich source of new alleles which could be used to broaden the genetic bases of YR resistance in modern wheat varieties.

Changes in wheat traits under future climate change and their contributions to yield changes in conventional vs. conservational tillage systems

Exploring the changes in wheat traits under future climate change and their contributions to yield changes is essential to improve the understanding of climate impact mechanisms and develop climate-resilient cultivars, which however has been seldom conducted. In this study, using a process-based crop model (APSIM-Wheat), meta-regression analyses, and machine learning approaches, we assessed the impacts of different warming levels on soil environments and wheat traits; investigated the impacts of future climate change on wheat traits, growth and development; and identified the favorable wheat traits for breeding under future climate change conditions. Meta-analyses showed that climate warming could significantly advance anthesis date by 3.50% and shorten the entire growth duration by 1.18%, although the duration from anthesis to maturity could be elongated by 7.72%. It could also increase grain yield slightly by 2.72% in the North China Plain, mainly due to the increase in biomass by 6.66%, grain weight by 3.86% and the elongating grain-filling period. However, high temperatures could significantly reduce aboveground biomass. The APSIM-Wheat model was validated based on three years' high-quality environment-controlled experimental data in the long-term warming and conservation tillage fields at Yucheng comprehensive experiment station in the North China Plain. The results showed that the mean yield would decrease under RCP4.5 for both tillage managements (conservational tillage: 0.55%, no-tillage: 6.88%), but increase conservational tillage yield (7.7%) under RCP8.5, relative to 1980-2010, owing to the interactive impacts of climate, CO₂ and tillage on wheat traits. Soil moisture would play a more important role in biomass, yield, height, LAI, and grain number for conventional tillage than for no-tillage system, and in the future than in the historical period. Our findings gained insights into the impacts of climate change on wheat traits and yield under different tillage managements, which are essential to understand climate change impact mechanisms and develop climate-resilient cultivars.

Agricultural practice contributed more to changes in soybean yield than climate change from 1981 to 2010 in northeast China

BACKGROUND

Although climate change and agricultural practices have non-negligible impacts on crop yields, their quantitative contributions to soybean yields remain unclear. First-order difference multiple regression was used to determine the respective contributions of climate change and agricultural practice to changes in soybean yields at station level from 1981 to 2010 in northeast China.

RESULTS

From 1981 to 2010, the soybean yields at 87% of the stations were increasing with an average 41.18 kg ha year-1 change trend in northeast China. The individual impacts of climate change and agricultural practice on soybean yield were -0.33% to 0.58% year-1 and -3.3% to 7.89% year-1 , respectively. The sensitivity of the soybean yield to climatic factors was related to latitude, and yields at high-latitude stations were positively correlated with temperature but negatively correlated with accumulated sunshine hours. Climate change contributed -24% to 38% to the trend in soybean yield, and the temperature had the greatest effect of all the climatic factors.

CONCLUSION

The contribution of agricultural practices was greater than that of climate change, counteracting the adverse effects of climate change and even affecting the direction of soybean yield changes. In adaptive decision making, priority should be given to management measures that have less impact on the environment, such as breeding new varieties adapted to specific latitudes, thus promoting the sustainable production of soybeans. © 2021 Society of Chemical Industry.

Crop Model Parameterisation of Three Important Pearl Millet Varieties for Improved Water Use and Yield Estimation

Pearl millet is an important crop for food security in Asia and Africa’s arid and semi-arid regions. It is widely grown as a staple cereal grain for human consumption and livestock fodder. Mechanistic crop growth and water balance models are useful to forecast crop production and water use. However, very few studies have been devoted to the development of the model parameters needed for such simulations for pearl millet. The objectives of the study were to determine crop-specific model parameters for each of three pearl millet varieties (landrace, hybrid, and improved), as well as to calibrate and validate the Soil Water Balance (SWB) model for predicting pearl millet production and water use based on weather data. The SWB was chosen because it is widely used in southern Africa; however, the developed parameters should benefit other models as well. The presented crop-specific parameter values were derived from field observations and literature. Varieties with different phenology, maturity dates and tillering habits were grown under well-watered and well-fertilised conditions for calibration purposes. The calibrated model was used to predict biomass production, grain yield and crop water use. The hybrid’s water use efficiency was higher than that of the landrace and improved variety.

Essential trace metals in plant responses to heat stress

Essential trace metals function as structural components or cofactors in many proteins involved in a wide range of physiological processes in plants. Hence, trace metal deficiency can significantly hamper plant growth and development. On the other hand, excess concentrations of trace metals can also induce phytotoxicity, for example via an enhanced production of reactive oxygen species. Besides their roles in plant growth under favourable environmental conditions, trace metals also contribute to plant responses to biotic and abiotic stresses. Heat is a stress factor that will become more prevalent due to increasing climate change and is known to negatively affect crop yield and quality, posing a severe threat to food security for future generations. Gaining insight into heat stress responses is essential to develop strategies to optimize plant growth and quality under unfavourable temperatures. In this context, trace metals deserve particular attention as they contribute to defence responses and are important determinants of plant nutritional value. Here, we provide an overview of heat-induced effects on plant trace metal homeostasis and the involvement of trace metals and trace metal-dependent enzymes in plant responses to heat stress. Furthermore, avenues for future research on the interactions between heat stress and trace metals are discussed.

Increasing temperature during early spring increases winter wheat grain yield by advancing phenology and mitigating leaf senescence

High temperature usually reduces wheat yield, especially at critical growth stages, such as anthesis and grain filling. However, effects of increasing temperature during wintering period on winter wheat growth and development are rarely reported. Hence, this three-year field experiment evaluated how artificial warming during early spring (wintering period) affects winter wheat. The warming treatment (WT) advanced the wheat reviving, jointing, anthesis, and maturity stages, but the average temperature in each growing stage reduced, thus extending the duration of tillering, spike differentiation, and grain filling. Concurrently, the leaf area index and biomass accumulation were obviously increased. Additionally, WT showed a lower leaf senescence rate compared with that of control (CK). Also, the photosynthesis rate and SPAD of WT were increased relative to CK. WT increased superoxide dismutase and peroxidase activities, and reduced malondialdehyde content in flag leaf during the grain filling stage, suggesting WT during early spring could delay leaf senescence after anthesis, which contributed to a high filling rate and long filling duration. Correspondingly, the final spike number, kernel number, and kernel weight of WT were significantly increased compared with CK. In the three seasons, grain yield was increased by 18.2%-37.5% in WT compared with CK. Results of this study provided a new viewpoint that increasing temperature could shorten the wintering period but extend the effective growth phase, and increase grain yield in winter wheat.

Uncertainty in climate change impact studies for irrigated maize cropping systems in southern Spain

This study investigates the main drivers of uncertainties in simulated irrigated maize yield under historical conditions as well as scenarios of increased temperatures and altered irrigation water availability. Using APSIM, MONICA, and SIMPLACE crop models, we quantified the relative contributions of three irrigation water allocation strategies, three sowing dates, and three maize cultivars to the uncertainty in simulated yields. The water allocation strategies were derived from historical records of farmer’s allocation patterns in drip-irrigation scheme of the Genil-Cabra region, Spain (2014–2017). By considering combinations of allocation strategies, the adjusted R² values (showing the degree of agreement between simulated and observed yields) increased by 29% compared to unrealistic assumptions of considering only near optimal or deficit irrigation scheduling. The factor decomposition analysis based on historic climate showed that irrigation strategies was the main driver of uncertainty in simulated yields (66%). However, under temperature increase scenarios, the contribution of crop model and cultivar choice to uncertainty in simulated yields were as important as irrigation strategy. This was partially due to different model structure in processes related to the temperature responses. Our study calls for including information on irrigation strategies conducted by farmers to reduce the uncertainty in simulated yields at field scale.

Impacts, Tolerance, Adaptation, and Mitigation of Heat Stress on Wheat under Changing Climates

Heat stress (HS) is one of the major abiotic stresses affecting the production and quality of wheat. Rising temperatures are particularly threatening to wheat production. A detailed overview of morpho-physio-biochemical responses of wheat to HS is critical to identify various tolerance mechanisms and their use in identifying strategies to safeguard wheat production under changing climates. The development of thermotolerant wheat cultivars using conventional or molecular breeding and transgenic approaches is promising. Over the last decade, different omics approaches have revolutionized the way plant breeders and biotechnologists investigate underlying stress tolerance mechanisms and cellular homeostasis. Therefore, developing genomics, transcriptomics, proteomics, and metabolomics data sets and a deeper understanding of HS tolerance mechanisms of different wheat cultivars are needed. The most reliable method to improve plant resilience to HS must include agronomic management strategies, such as the adoption of climate-smart cultivation practices and use of osmoprotectants and cultured soil microbes. However, looking at the complex nature of HS, the adoption of a holistic approach integrating outcomes of breeding, physiological, agronomical, and biotechnological options is required. Our review aims to provide insights concerning morpho-physiological and molecular impacts, tolerance mechanisms, and adaptation strategies of HS in wheat. This review will help scientific communities in the identification, development, and promotion of thermotolerant wheat cultivars and management strategies to minimize negative impacts of HS.

Ethylene involvement in the regulation of heat stress tolerance in plants

Because of the rise in global temperature, heat stress has become a major concern for crop production. Heat stress deteriorates plant productivity and alters phenological and physiological responses that aid in precise monitoring and sensing of mild-to-severe transient heat stress. Plants have evolved several sophisticated mechanisms including hormone-signaling pathways to sense heat stimuli and acquire heat stress tolerance. In response to heat stress, ethylene, a gaseous hormone, is produced which is indispensable for plant growth and development and tolerance to various abiotic stresses including heat stress. The manipulation of ethylene in developing heat stress tolerance targeting ethylene biosynthesis and signaling pathways has brought promising out comes. Conversely increased ethylene biosynthesis and signaling seem to exhibit inhibitory effects in plant growth responses from primitive to maturity stages. This review mainly focuses on the recent studies of ethylene involvement in plant responses to heat stress and its functional regulation, and molecular mechanism underlying the plant responses in the mitigation of heat-induced damages. Furthermore, this review also describes the crosstalk between ethylene and other signaling molecules under heat stress and approaches to improve heat stress tolerance in plants.

The genetic and molecular basis for improving heat stress tolerance in wheat

Wheat production requires at least ~ 2.4% increase per year rate by 2050 globally to meet food demands. However, heat stress results in serious yield loss of wheat worldwide. Correspondingly, wheat has evolved genetic basis and molecular mechanisms to protect themselves from heat-induced damage. Thus, it is very urgent to understand the underlying genetic basis and molecular mechanisms responsive to elevated temperatures to provide important strategies for heat-tolerant varieties breeding. In this review, we focused on the impact of heat stress on morphology variation at adult stage in wheat breeding programs. We also summarize the recent studies of genetic and molecular factors regulating heat tolerance, including identification of heat stress tolerance related QTLs/genes, and the regulation pathway in response to heat stress. In addition, we discuss the potential ways to improve heat tolerance by developing new technologies such as genome editing. This review of wheat responses to heat stress may shed light on the understanding heat-responsive mechanisms, although the regulatory network of heat tolerance is still ambiguous in wheat.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42994-021-00064-z.

Molecular insights into sensing, regulation and improving of heat tolerance in plants

Climate-change-mediated increase in temperature extremes has become a threat to plant productivity. Heat stress-induced changes in growth pattern, sensitivity to pests, plant phonologies, flowering, shrinkage of maturity period, grain filling, and increased senescence result in significant yield losses. Heat stress triggers multitude of cellular, physiological and molecular responses in plants beginning from the early sensing followed by signal transduction, osmolyte synthesis, antioxidant defense, and heat stress-associated gene expression. Several genes and metabolites involved in heat perception and in the adaptation response have been isolated and characterized in plants. Heat stress responses are also regulated by the heat stress transcription factors (HSFs), miRNAs and transcriptional factors which together form another layer of regulatory circuit. With the availability of functionally validated candidate genes, transgenic approaches have been applied for developing heat-tolerant transgenic maize, tobacco and sweet potato. In this review, we present an account of molecular mechanisms of heat tolerance and discuss the current developments in genetic manipulation for heat tolerant crops for future sustainable agriculture.

Climate change impact uncertainty assessment and adaptations for sustainable maize production using multi-crop and climate models

Future climate scenarios are predicting considerable threats to sustainable maize production in arid and semi-arid regions. These adverse impacts can be minimized by adopting modern agricultural tools to assess and develop successful adaptation practices. A multi-model approach (climate and crop) was used to assess the impacts and uncertainties of climate change on maize crop. An extensive field study was conducted to explore the temporal thermal variations on maize hybrids grown at farmer's fields for ten sowing dates during two consecutive growing years. Data about phenology, morphology, biomass development, and yield were recorded by adopting standard procedures and protocols. The CSM-CERES, APSIM, and CSM-IXIM-Maize models were calibrated and evaluated. Five GCMs among 29 were selected based on classification into different groups and uncertainty to predict climatic changes in the future. The results predicted that there would be a rise in temperature (1.57-3.29 °C) during the maize growing season in five General Circulation Models (GCMs) by using RCP 8.5 scenarios for the mid-century (2040-2069) as compared with the baseline (1980-2015). The CERES-Maize and APSIM-Maize model showed lower root mean square error values (2.78 and 5.41), higher d-index (0.85 and 0.87) along reliable R² (0.89 and 0.89), respectively for days to anthesis and maturity, while the CSM-IXIM-Maize model performed well for growth parameters (leaf area index, total dry matter) and yield with reasonably good statistical indices. The CSM-IXIM-Maize model performed well for all hybrids during both years whereas climate models, NorESM1-M and IPSL-CM5A-MR, showed less uncertain results for climate change impacts. Maize models along GCMs predicted a reduction in yield (8-55%) than baseline. Maize crop may face a high yield decline that could be overcome by modifying the sowing dates and fertilizer (fertigation) and heat and drought-tolerant hybrids.

Crop traits enabling yield gains under more frequent extreme climatic events

Climate change (CC) in central China will change seasonal patterns of agricultural production through increasingly frequent extreme climatic events (ECEs). Breeding climate-resilient wheat (Triticum aestivum L.) genotypes may mitigate adverse effects of ECEs on crop productivity. To reveal crop traits conducive to long-term yield improvement in the target population of environments, we created 8,192 virtual genotypes with contrasting but realistic ranges of phenology, productivity and waterlogging tolerance. Using these virtual genotypes, we conducted a genotype (G) by environment (E) by management (M) factorial analysis (G×E×M) using locations distributed across the entire cereal cropping zone in mid-China. The G×E×M invoked locally-specific sowing dates under future climates that were premised on shared socioeconomic pathways SSP5-8.5, with a time horizon centred on 2080. Across the simulated adaptation landscape, productivity was primarily driven by yield components and phenology (average grain yield increase of 6-69% across sites with optimal combinations of these traits). When incident solar radiation was not limiting carbon assimilation, ideotypes with higher grain yields were characterised by earlier flowering, higher radiation-use efficiency and larger maximum kernel size. At sites with limited solar radiation, crops required longer growing periods to realise genetic yield potential, although higher radiation-use efficiency and larger maximum kernel size were again prospective traits enabling higher rates of yield gains. By 2080, extreme waterlogging stress in some regions of mid-China will impact substantially on productivity, with yield penalties of up to 1,010 kg ha^-1. Ideotypes with optimal G×M could mitigate yield penalty caused by waterlogging by up to 15% under future climates. These results help distil promising crop trait by best management practice combinations that enable higher yields and robust adaptation to future climates and more frequent extreme climatic events, including flash flooding and soil waterlogging.

Nitric Oxide and Abscisic Acid Mediate Heat Stress Tolerance through Regulation of Osmolytes and Antioxidants to Protect Photosynthesis and Growth in Wheat Plants

Nitric oxide (NO) and abscisic acid (ABA) play a significant role to combat abiotic stress. Application of 100 µM sodium nitroprusside (SNP, NO donor) or ABA alleviated heat stress effects on photosynthesis and growth of wheat (Triticum aestivum L.) plants exposed to 40 °C for 6 h every day for 15 days. We have shown that ABA and NO synergistically interact to reduce the heat stress effects on photosynthesis and growth via reducing the content of H2O2 and thiobarbituric acid reactive substances (TBARS), as well as maximizing osmolytes production and the activity and expression of antioxidant enzymes. The inhibition of NO and ABA using c-PTIO (2-4 carboxyphenyl-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide) and fluridone (Flu), respectively, reduced the osmolyte and antioxidant metabolism and heat stress tolerance. The inhibition of NO significantly reduced the ABA-induced osmolytes and antioxidant metabolism, exhibiting that the function of ABA in the alleviation of heat stress was NO dependent and can be enhanced with NO supplementation.Thus, regulating the activity and expression of antioxidant enzymes together with osmolytes production could act as a possible strategy for heat tolerance.

Prior crop season management constrains farmer adaptation to warming temperatures: Evidence from the Indo-Gangetic Plains

Climate change induced heat stress is predicted to negatively impact wheat yields across the Indo-Gangetic Plains (IGP) of India. Research suggests that early sowing of wheat can substantially reduce this impact. However, a large proportion of farmers sow wheat late across this region, likely resulting in large-scale yield loss. We examined the extent of late wheat sowing across the IGP and which perceptional, management, biophysical, and socio-economic factors are associated with delayed sowing using household survey data from 2429 farmers and the cumulative logit model. Our results indicate that despite understanding that early sowing can be helpful to avoid terminal heat stress, over 50% of farmers sow wheat later than their perceived ideal wheat sowing date. We find that variables related to how wheat fields are prepared prior to sowing are associated with wheat sowing date. Specifically, farmers who had shorter fallow periods prior to sowing wheat and those who used zero tillage were 95% and 65% more likely to sow wheat earlier, respectively. In addition, we found that how farmers managed their rice crop in the preceding cropping season impacted wheat sowing date - farmers who transplanted and harvested rice later and/or planted longer duration rice varieties sowed their wheat later. Our results suggest that policies that promote earlier sowing of rice, such as improved access to irrigation and direct seeding machinery, and reduced field preparation time, such as wider adoption of zero tillage technologies, can help farmers across the IGP sow wheat earlier. This is critical given that warming temperatures will only increase the negative impacts of terminal heat stress on wheat yields across this region over the coming decades.

Stress granule-associated TaMBF1c confers thermotolerance through regulating specific mRNA translation in wheat (Triticum aestivum)

Heat stress is a major limiting factor for global wheat production and causes dramatic yield loss worldwide. The TaMBF1c gene is upregulated in response to heat stress in wheat. Understanding the molecular mechanisms associated with heat stress responses will pave the way to improve wheat thermotolerance. Through CRISPR/Cas9-based gene editing, polysome profiling coupled with RNA-sequencing analysis, and protein-protein interactions, we show that TaMBF1c conferred heat response via regulating a specific gene translation in wheat. The results showed that TaMBF1c is evolutionarily conserved in diploid, tetraploid and hexaploid wheat species, and its knockdown and knockout lines show increased heat sensitivity. TaMBF1c is colocalized with the stress granule complex and interacts with TaG3BP. TaMBF1c affects the translation efficiency of a subset of heat responsive genes, which are significantly enriched in the 'sequence-specific DNA binding' term. Moreover, gene expression network analysis demonstrated that TaMBF1c is closely associated with the translation of heat shock proteins. Our findings reveal a contribution of TaMBF1c in regulating the heat stress response via the translation process, and provide a new target for improving heat tolerance in wheat breeding programs.

The response of net primary productivity to climate change and its impact on hydrology in a water-limited agricultural basin

Climate change has remarkably altered growing-season vegetation growth, but the impacts of vegetation variability on the regional hydrological cycle remain poorly understood. Exploring the relationships between climate change, vegetation dynamics, and hydrologic factors would contribute to the sustainable management of ecosystems. Here, we investigated the response of vegetation dynamics to climate change and its impact on hydrologic factors in a traditional agricultural basin with limited water resources in China, Nansi Lake Basin (NLB). To this end, CASA (Carnegie-Ames-Stanford Approach) model and the SWAT (Soil and Water Assessment Tool) model were applied to simulate the net primary productivity (NPP), evapotranspiration (ET), and soil water in the growing season (April-October) from 2000 to 2016. Results showed that the mean growing-season NPP (NPP_GS) exhibited an ascending trend at a rate of 2.93 g C/m²/year during the 17-year period. The intra-annual variation of NPP_GS displayed two peaks in May and July, respectively. The first peak in May was accompanied by relative deficits in soil water, which might inhibit vegetation productivity. Precipitation was the principal climatic factor controlling NPP_GS dynamics in the water-limited NLB. The positive influence of temperature on NPP_GS was relatively weak, and even future warming could negatively affect ecosystem productivity in the south-central regions of the NLB. Furthermore, a strongly positive relationship between NPP_GS and ET was detected, suggesting that increasing NPP in the future might stimulate the rise in ET and then exacerbate drought at the watershed scale. This study provides an integrated model for a comprehensive understanding of the interaction between vegetation, climate, and hydrological cycle, and highlights the importance of water-saving agriculture for future food security.

Genome-Wide Identification and Characterization of RNA/DNA Differences Associated with Drought Response in Wheat

RNA/DNA difference (RDD) is a post-transcriptional RNA modification to enrich genetic information, widely involved in regulating diverse biological processes in eukaryotes. RDDs in the wheat nuclear genome, especially those associated with drought response or tolerance, were not well studied up to now. In this study, we investigated the RDDs related to drought response based on the RNA-seq data of drought-stressed and control samples in wheat. In total, 21,782 unique RDDs were identified, of which 265 were found to be drought-induced, representing the first drought-responsive RDD landscape in the wheat nuclear genome. The drought-responsive RDDs were located in 69 genes, of which 35 were differentially expressed under drought stress. Furthermore, the effects of RNA/DNA differences were investigated, showing that they could result in changes of RNA secondary structure, miRNA-target binding as well as protein conserved domains in the RDD-containing genes. In particular, the A to C mutation in TraesCS2A02G053100 (orthology to OsRLCK) led to the loss of tae-miR9657b-5p targeting, indicating that RNA/DNA difference might mediate miRNA to regulate the drought-response process. This study reported the first drought-responsive RDDs in the wheat nuclear genome. It sheds light on the roles of RDD in drought tolerance, and may also contribute to wheat genetic improvement based on epi-transcriptome methods.

Responses of Barley to High Ambient Temperature Are Modulated by Vernalization

Ambient temperatures are increasing due to climate change. Cereal crops development and production will be affected consequently. Flowering time is a key factor for adaptation of small grain cereals and, therefore, exploring developmental responses of barley to rising temperatures is required. In this work, we studied phasic growth, and inflorescence traits related to yield, in eight near isogenic lines of barley (Hordeum vulgare L.) differing at the VRN-H1, VRN-H2 and PPD-H1 genes, representing different growth habits. The lines were grown in contrasting vernalization treatments, under two temperature regimes (18 and 25°C), in long days. Lines with recessive ppd-H1 presented delayed development compared to lines with the sensitive PPD-H1 allele, across the two growth phases considered. High temperature delayed flowering in all unvernalized plants, and in vernalized spring barleys carrying the insensitive ppd-H1 allele, whilst it accelerated flowering in spring barleys with the sensitive PPD-H1 allele. This finding evidenced an interaction between PPD-H1, temperature and vernalization. At the high temperature, PPD-H1 lines in spring backgrounds (VRN-H1-7) yielded more, whereas lines with ppd-H1 were best in vrn-H1 background. Our study revealed new information that will support breeding high-yielding cultivars with specific combinations of major adaptation genes tailored to future climatic conditions.

D. Weber T, Tesfaye K, Streck T. Climate change impact on wheat and maize growth in Ethiopia: A multi-model uncertainty analysis

Ethiopia’s economy is dominated by agriculture which is mainly rain-fed and subsistence. Climate change is expected to have an adverse impact particularly on crop production. Previous studies have shown large discrepancies in the magnitude and sometimes in the direction of the impact on crop production. We assessed the impact of climate change on growth and yield of maize and wheat in Ethiopia using a multi-crop model ensemble. The multi-model ensemble (n = 48) was set up using the agroecosystem modelling framework Expert-N. The framework is modular which facilitates combining different submodels for plant growth and soil processes. The multi-model ensemble was driven by climate change projections representing the mid of the century (2021–2050) from ten contrasting climate models downscaled to finer resolution. The contributions of different sources of uncertainty in crop yield prediction were quantified. The sensitivity of crop yield to elevated CO₂, increased temperature, changes in precipitations and N fertilizer were also assessed. Our results indicate that grain yields were very sensitive to changes in [CO₂], temperature and N fertilizer amounts where the responses were higher for wheat than maize. The response to change in precipitation was weak, which we attribute to the high water holding capacity of the soils due to high organic carbon contents at the study sites. This may provide the sufficient buffering capacity for extended time periods with low amounts of precipitation. Under the changing climate, wheat productivity will be a major challenge with a 36 to 40% reduction in grain yield by 2050 while the impact on maize was modest. A major part of the uncertainty in the projected impact could be attributed to differences in the crop growth models. A considerable fraction of the uncertainty could also be traced back to different soil water dynamics modeling approaches in the model ensemble, which is often ignored. Uncertainties varied among the studied crop species and cultivars as well. The study highlights significant impacts of climate change on wheat yield in Ethiopia whereby differences in crop growth models causes the large part of the uncertainties.

Hotspots of Yield Loss for Four Crops of the Belt and Road Terrestrial Countries under 1.5 °C Global Warming

The Fifth Assessment Report of the Intergovernmental Panel on Climate change (IPCC) shows that climate change poses severe risks to the Belt and Road region and could cut future crop production. Identifying the positions and features of hotspots, which refer to regions with severe yield loss at 1.5 °C global warming, is the key to developing proper mitigation and adaptation policies to ensure regional food security. This study examined yield loss hotspots of four crops (maize, rice, soybean and wheat) at 1.5 °C global warming under RCP8.5. Yield data were derived from simulations of multiple climate-crop model ensembles from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). Hotspots were identified by setting a threshold of the 10th percentile of crop yields during the reference period (1986–2005). To quantify the likelihood of crop yield loss hotspots within multi-model ensembles, the agreement of model combinations for hotspots was calculated for each crop at the grid scale with 0.5° × 0.5° spatial resolution. Results revealed spatial heterogeneity of cultivation structure and hotspot likelihood for four crops. The four crops’ production of SA (South Asia) and SEA (Southeast Asia) accounts for more than 40% of the total production in the Belt and Road region, roughly four times the amount produced in CEE (Central and Eastern Europe) and NEA (Northeast Asia). Besides, the hotspots likelihood of maize, rice and soybean is generally larger in SA/SEA than that in CEE/NEA which means the risk of yield reduction is higher in the current main agricultural area. According to IPCC’s classification rules for likelihood, four crops’ hotspot patterns were displayed under the 1.5 °C global warming. As the highest-yielding crop, maize shows the largest proportion of “likely” hotspots (hotspot likelihood > 66%), which is about 6.48%, accounting for more than four times that of the other three crops. In addition, four crops’ hotspots are mainly distributed in SEA and SA. Overall, SEA and SA are vulnerable subregions and maize is the vulnerable crop of the Belt and Road region. Our results could provide information on target areas where mitigation or adaptations are needed to reduce the adverse influence of climate change in the agricultural system.

Dissecting the Genetics of Early Vigour to Design Drought-Adapted Wheat

Due to the climate change and an increased frequency of drought, it is of enormous importance to identify and to develop traits that result in adaptation and in improvement of crop yield stability in drought-prone regions with low rainfall. Early vigour, defined as the rapid development of leaf area in early developmental stages, is reported to contribute to stronger plant vitality, which, in turn, can enhance resilience to erratic drought periods. Furthermore, early vigour improves weed competitiveness and nutrient uptake. Here, two sets of a multi-reference nested association mapping (MR-NAM) population of bread wheat (Triticum aestivum ssp. aestivum L.) were used to investigate early vigour in a rain-fed field environment for 3 years, and additionally assessed under controlled conditions in a greenhouse experiment. The normalised difference vegetation index (NDVI) calculated from red/infrared light reflectance was used to quantify early vigour in the field, revealing a correlation (p < 0.05; r = 0.39) between the spectral measurement and the length of the second leaf. Under controlled environmental conditions, the measured projected leaf area, using a green-pixel counter, was also correlated to the leaf area of the second leaf (p < 0.05; r = 0.38), as well as to the recorded biomass (p < 0.01; r = 0.71). Subsequently, genetic determination of early vigour was tested by conducting a genome-wide association study (GWAS) for the proxy traits, revealing 42 markers associated with vegetation index and two markers associated with projected leaf area. There are several quantitative trait loci that are collocated with loci for plant developmental traits including plant height on chromosome 2D (log₁₀ (P) = 3.19; PVE = 0.035), coleoptile length on chromosome 1B (-log₁₀ (P) = 3.24; PVE = 0.112), as well as stay-green and vernalisation on chromosome 5A (-log₁₀ (P) = 3.14; PVE = 0.115).

Osmotic Adjustment in Wheat (Triticum aestivum L.) During Pre- and Post-anthesis Drought

Pre-anthesis drought is expected to greatly increase yield losses in wheat (Triticum aestivum L.), one of the most important crops worldwide. Most studies investigate the effects of pre-anthesis drought only at maturity. The physiology of the plant before anthesis and how it is affected during drought is less studied. Our study focused on physiological patterns in wheat plants during pre- and post-anthesis drought. To this end, we measured leaf xylem water potential, osmotic potential and water content in different plant parts at a high temporal frequency: every 3 days, three times a day. The experiment started just before booting until 2 weeks after flowering. Drought stress was induced by withholding irrigation with rewatering upon turgor loss, which occurred once before and once after anthesis. The goal was to investigate the patterns of osmotic adjustment, when it is used for protection against drought, and if the strategy changes during the phenological development of the plant. Our data gave no indication of daily osmotic adjustment, but did show a delicate control of the osmotic potential during drought in both leaves and stem. Under high drought stress, osmotic potential decreased to avoid further water loss. Before anthesis, rewatering restored leaf water potential and osmotic potential quickly. After anthesis, rewatering restored water potential in the flag leaves, but the osmotic potential in the stem and flag leaf remained low longer. Osmotic adjustment was thus maintained longer after anthesis, showing that the plants invest more energy in the osmotic adjustment after anthesis than before anthesis. We hypothesize that this is because the plants consider the developing ear after anthesis a more important carbohydrate sink than the stem, which is a carbohydrate sink before anthesis, to be used later as a reserve. Low osmotic potential in the stem allowed turgor maintenance, while the low osmotic potential in the flag leaf led to an increase in leaf turgor beyond the level of the control plants. This allowed leaf functioning under drought and assured that water was redirected to the flag leaf and not used to refill the stem storage.

Mediterranean viticulture in the context of climate change

The exposure of viticulture to climate change and extreme weather conditions makes the winemaking sector particularly vulnerable, being one of its major challenges in the current century. While grapevine is considered a highly tolerant crop to several abiotic stresses, Mediterranean areas are frequently affected by adverse environmental factors, namely water scarcity, heat and high irradiance, and are especially vulnerable to climate change. Due to the high socio-economic value of this sector in Europe, the study of adaptation strategies to mitigate the negative climate change impacts are of main importance for its sustainability and competitiveness. Adaptation strategies include all the set of actions and processes that can be performed in response to climate change. It is crucial to improve agronomic strategies to offset the loss of productivity and likely changes in production and fruit quality. It is important to look for new insights concerning response mechanisms to these stresses to advance with more effective and precise measures. These measures should be adjusted to local terroirs and regional climate change projections for the sustainable development of the winemaking sector. This review describes the direct climate change impacts (on phenology, physiology, yield and berry quality), risks, and uncertainties for Mediterranean viticulture, as well as a set of canopy, soil and water management practices that winegrowers can use to adapt their vines to warmer and drier conditions.

Agricultural breadbaskets shift poleward given adaptive farmer behavior under climate change

Modern food production is spatially concentrated in global "breadbaskets." A major unresolved question is whether these peak production regions will shift poleward as the climate warms, allowing some recovery of potential climate-related losses. While agricultural impacts studies to date have focused on currently cultivated land, the Global Gridded Crop Model Intercomparison Project (GGCMI) Phase 2 experiment allows us to assess changes in both yields and the location of peak productivity regions under warming. We examine crop responses under projected end of century warming using seven process-based models simulating five major crops (maize, rice, soybeans, and spring and winter wheat) with a variety of adaptation strategies. We find that in no-adaptation cases, when planting date and cultivar choices are held fixed, regions of peak production remain stationary and yield losses can be severe, since growing seasons contract strongly with warming. When adaptations in management practices are allowed (cultivars that retain growing season length under warming and modified planting dates), peak productivity zones shift poleward and yield losses are largely recovered. While most growing-zone shifts are ultimately limited by geography, breadbaskets studied here move poleward over 600 km on average by end of the century under RCP 8.5. These results suggest that agricultural impacts assessments can be strongly biased if restricted in spatial area or in the scope of adaptive behavior considered. Accurate evaluation of food security under climate change requires global modeling and careful treatment of adaptation strategies.

Simulation of Wheat Response to Future Climate Change Based on Coupled Model Inter-Comparison Project Phase 6 Multi-Model Ensemble Projections in the North China Plain

Global climate change results in more extreme temperature events, which poses a serious threat to wheat production in the North China Plain (NCP). Assessing the potential impact of temperature extremes on crop growth and yield is an important prerequisite for exploring crop adaptation measures to deal with changing climate. In this study, we evaluated the effects of heat and frost stress during wheat sensitive period on grain yield at four representative sites over the NCP using Agricultural Production System Simulator (APSIM)-wheat model driven by the climate projections from 20 Global Climate Models (GCMs) in the Coupled Model Inter-comparison Project phase 6 (CMIP6) during two future periods of 2031-2060 (2040S) and 2071-2100 (2080S) under societal development pathway (SSP) 245 and SSP585 scenarios. We found that extreme temperature stress had significantly negative impacts on wheat yield. However, increased rainfall and the elevated atmospheric CO₂ concentration could partly compensate for the yield loss caused by extreme temperature events. Under future climate scenarios, the risk of exposure to heat stress around flowering had no great change but frost risk in spring increased slightly mainly due to warming climate accelerating wheat development and advancing the flowering time to a cooler period of growing season. Wheat yield loss caused by heat and frost stress increased by -0.6 to 4.2 and 1.9-12.8% under SSP585_2080S, respectively. We also found that late sowing and selecting cultivars with a long vegetative growth phase (VGP) could significantly compensate for the negative impact of extreme temperature on wheat yields in the south of NCP. However, selecting heat resistant cultivars in the north NCP and both heat and frost resistant cultivars in the central NCP may be a more effective way to alleviate the negative effect of extreme temperature on wheat yields. Our findings showed that not only heat risk should be concerned under climate warming, but also frost risk should not be ignored.

Genome-wide association for heat tolerance at seedling stage in historical spring wheat cultivars

Increasing global temperature has adverse effects on crop health and productivity at both seedling and reproductivity stages. It is paramount to develop heat tolerant wheat cultivars able to sustain under high and fluctuating temperature conditions. An experiment was conducted to characterize 194 historical wheat cultivars of Pakistan under high temperature at seedling stage to identify loci associated with heat tolerance using genome-wide association studies (GWAS). A quantitative trait locus, TaHST1, on chr4A was also characterized to identify the haplotypes at this locus associated with heat tolerance in wheat from Pakistan. Initially, the diversity panel was planted under control conditions (25°C/20°C day and night temperature) in a glass house. At three leaf stage, plants were subjected to heat stress (HS) by increasing temperature (40°C/35°C day and night), while one treatment was kept at control condition. After 7 days of HS, data were collected for seedling morphology. Heat stress reduced these traits by 25% (root weight) to 40% (shoot weight), and shoot biomass was largely affected by heat stress. A GWAS model, fixed and random model circulating probability unification (FarmCPU), identified 43 quantitative trait nucleotides (QTNs) on all chromosomes, except chr7B, were associated under both HS and control conditions. Thirteen QTNs were identified in control, while 30 QTNs were identified in HS condition. In total, 24 haplotypes were identified at TaHST1 locus, and most of the heat tolerant genotypes were assigned to Hap-20 and Hap-21. Eleven QTNs were identified within 0.3-3.1 Mb proximity of heat shock protein (HSP). Conclusively, this study provided a detailed genetic framework of heat tolerance in wheat at the seedling stage and identify potential genetic regions associated with heat tolerance which can be used for marker assisted selection (MAS) in breeding for heat stress tolerance.

Opportunities and limits of controlled-environment plant phenotyping for climate response traits

Rising temperatures and changing precipitation patterns will affect agricultural production substantially, exposing crops to extended and more intense periods of stress. Therefore, breeding of varieties adapted to the constantly changing conditions is pivotal to enable a quantitatively and qualitatively adequate crop production despite the negative effects of climate change. As it is not yet possible to select for adaptation to future climate scenarios in the field, simulations of future conditions in controlled-environment (CE) phenotyping facilities contribute to the understanding of the plant response to special stress conditions and help breeders to select ideal genotypes which cope with future conditions. CE phenotyping facilities enable the collection of traits that are not easy to measure under field conditions and the assessment of a plant's phenotype under repeatable, clearly defined environmental conditions using automated, non-invasive, high-throughput methods. However, extrapolation and translation of results obtained under controlled environments to field environments is ambiguous. This review outlines the opportunities and challenges of phenotyping approaches under controlled environments complementary to conventional field trials. It gives an overview on general principles and introduces existing phenotyping facilities that take up the challenge of obtaining reliable and robust phenotypic data on climate response traits to support breeding of climate-adapted crops.

Effect of wind speed variation on rainfed wheat production evaluated by the CERES-Wheat model

Climate is one of the major factors affecting crop phenology and yield. In most previous studies, impacts of temperature (T) and rainfall (R) on crop development, growth, and yield were investigated, while the effect of wind speed (WS) has so far not been assessed. In this study, the influence of WS alteration on rainfed wheat production was evaluated in arid and semi-arid environments during a 25-year period in northeast Iran. In so doing, various climatic scenarios were defined using T, R, and WS changes, and then applied to the CERES-Wheat model included in DSSAT v4.7.5. The results showed that WS variation can alter total ET (planting to harvest) from -12.1 to +8.9%, aboveground biomass from -8.4 to +11.0%, water use efficiency from -13.4 to +19.7%, and grain yield from -11.2 to +15.3%. These changes were in many cases related to the climatic conditions. It was also revealed that in a greater amount of rainfall and shorter growing season (i.e., less drought stress), the WS variation had the stronger impact on total ET; while for aboveground biomass, water use efficiency, and grain yield, the greatest effect of WS variation was detected under the water scarcity conditions (i.e., low rainfall). The results demonstrate that wind speed needs to be better considered in climate change impact studies, in particular in water-scarce regions.

Impacts of irrigation efficiency on water-dependent sectors are heavily controlled by region-specific institutions and infrastructures

Farmers' investment in more efficient irrigation systems represents a primary adaptation strategy when confronting climate change. However, the regional benefits of these investments and their influence on the conflicting demands among different water dependent stakeholders for intensely irrigated regions remains an open question. Using the Pacific Northwest of the United States as an illustrative region of focus, we show that higher irrigation efficiency has diverse effects across stakeholders that are contingent on many local climatic, institutional and infrastructural factors such as the availability of water storage, the location of hydropower generators, and water rights. These complexities limit simple abstractions of irrigation efficiency as broader policy challenge and are central to its inclusion within the class of "wicked problems". Additionally, we argue that the widely used rebound effect concept, which implicitly discourages irrigation efficiency supporting policies, should not be assumed to fully capture the nuances of the complex suite of regional impacts that emerge from irrigation efficiency investments. Consequently, the evaluation of irrigation efficiency investments requires a broader framing across a diversity of perspectives. policies and actions that are pluralistic, context-specific, and closely engage various groups of stakeholders in the policymaking process.

Exploring the legacy of Central European historical winter wheat landraces

Historical wheat landraces are rich sources of genetic diversity offering untapped reservoirs for broadening the genetic base of modern varieties. Using a 20K SNP array, we investigated the accessible genetic diversity in a Central European bread wheat landrace collection with great drought, heat stress tolerance and higher tillering capacity. We discovered distinct differences in the number of average polymorphisms between landraces and modern wheat cultivars, and identified a set of novel rare alleles present at low frequencies in the landrace collection. The detected polymorphisms were unevenly distributed along the wheat genome, and polymorphic markers co-localized with genes of great agronomic importance. The geographical distribution of the inferred Bayesian clustering revealed six genetically homogenous ancestral groups among the collection, where the Central European core bared an admixed background originating from four ancestral groups. We evaluated the effective population sizes (Ne) of the Central European collection and assessed changes in diversity over time, which revealed a dramatic ~ 97% genetic erosion between 1955 and 2015.

Calibration and Validation of AQUACROP and APSIM Models to Optimize Wheat Yield and Water Saving in Arid Regions

The APSIM-Wheat and AQUACROP models were calibrated for the Sakha 95 cultivar using phenological data, grain and biomass yield, and genetic parameters based on field observation. Various treatments of planting dates, irrigation, and fertilization were applied over the two successive winter growing seasons of 2019/2020 and 2020/2021. Both models simulated anthesis, maturity dates, grain yield, and aboveground biomass accurately with high performances (coefficient of determination, index of agreement greater than 0.8, and lower values of root mean square deviation) in most cases. The calibrated models were then employed to explore wheat yield and water productivity (WP) in response to irrigation and nitrogen fertilization applications. Scenario analyses indicated that water productivity and yield of wheat ranged from 1.2–2.0 kg m–3 and 6.8–8.7 t ha–1, respectively. Application of 0.8 from actual evapotranspiration and 120% from recommended nitrogen dose was the best-predicted scenario achieving the highest value of crop WP. Investigating the suitable option achieving the current wheat yield by farmers (7.4 t ha–1), models demonstrated that application of 1.4 from actual evapotranspiration with 80% of the recommended nitrogen dose was the best option to achieve this yield. At this point, predicted WP was low and recorded 1.5 kg m–3. Quantifying wheat yield in all districts of the studied area was also predicted using both models. APSIM-Wheat and AQUACROP can be used to drive the best management strategies in terms of N fertilizer and water regime for wheat under Egyptian conditions.

Association analysis for agronomic traits in wheat under terminal heat stress

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Terminal heat stress leads to irreversible damage in wheat.

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Marker assisted selection and gene pyramiding for portrayal of heat tolerance.

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Allelic frequency and polymorphic information showed significant variability.

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Markers xcfa2147 and xwmc671 could be potentail for heat stress tolerance.

Terminal heat stress causes irreversible damage to wheat crop productivity. It reduces the vegetative growth and flowering period that consequently declines the efficiency to capture available stem reserves (carbohydrates) in grains. Markers associated with thermotolerant traits ease in marker assisted selection (MAS) for crop improvement. It identifies the genomic regions associated with thermotolerant traits in wheat, but the scarcity of markers is the major hindrance in crop improvement. Therefore, 158 wheat genotypes were subjected to genotyping with 165 simple sequence repeat markers dispersed on three genomes (A, B and D). Allelic frequency and polymorphic information content values were highest on genome A (5.34 (14% greater than the lowest value at genome D) and 0.715 (3% greater than the lowest value at genome D)), chromosome 4 (5.40 (16% greater than the lowest value at chromosome 2) and 0.725 (5% greater than the lowest value at chromosome 6)) and marker xgwm44 (13.0 (84% greater than the lowest value at marker xbarc148) and 0.916 (46% greater than the lowest value at marker xbarc148)). Bayesian based population structure discriminated the wheat genotypes into seven groups based on genetic similarity indicating their ancestral origin and geographical ecotype. Linkage disequilibrium pattern had highest significant (P < 0.001) linked loci pairs 732 on genome A at r² > 0.1 whereas, 58 on genome B at r² > 0.5. Linkage disequilibrium decay (P < 0.01 and r² > 0.1) had larger LD block (5–10 cM) on genome A. Highly significant MTAs (P < 0.000061) under heat stress conditions were identified for flag leaf area (xwmc336), spikelet per spike (xwmc553), grains per spike (cxfa2147, xwmc418 and xwmc121), biomass (xbarc7) and grain yield (xcfa2147 and xwmc671). The identified markers in this study could facilitate in MAS and gene pyramiding against heat stress in wheat.

Challenges of Biomass Utilization for Bioenergy in a Climate Change Scenario

The climate changes expected for the next decades will expose plants to increasing occurrences of combined abiotic stresses, including drought, higher temperatures, and elevated CO2 atmospheric concentrations. These abiotic stresses have significant consequences on photosynthesis and other plants' physiological processes and can lead to tolerance mechanisms that impact metabolism dynamics and limit plant productivity. Furthermore, due to the high carbohydrate content on the cell wall, plants represent a an essential source of lignocellulosic biomass for biofuels production. Thus, it is necessary to estimate their potential as feedstock for renewable energy production in future climate conditions since the synthesis of cell wall components seems to be affected by abiotic stresses. This review provides a brief overview of plant responses and the tolerance mechanisms applied in climate change scenarios that could impact its use as lignocellulosic biomass for bioenergy purposes. Important steps of biofuel production, which might influence the effects of climate change, besides biomass pretreatments and enzymatic biochemical conversions, are also discussed. We believe that this study may improve our understanding of the plant biological adaptations to combined abiotic stress and assist in the decision-making for selecting key agronomic crops that can be efficiently adapted to climate changes and applied in bioenergy production.

A Deep Learning Method for Fully Automatic Stomatal Morphometry and Maximal Conductance Estimation

Stomata are integral to plant performance, enabling the exchange of gases between the atmosphere and the plant. The anatomy of stomata influences conductance properties with the maximal conductance rate, g _smax, calculated from density and size. However, current calculations of stomatal dimensions are performed manually, which are time-consuming and error prone. Here, we show how automated morphometry from leaf impressions can predict a functional property: the anatomical g_smax. A deep learning network was derived to preserve stomatal morphometry via semantic segmentation. This forms part of an automated pipeline to measure stomata traits for the estimation of anatomical g_smax. The proposed pipeline achieves accuracy of 100% for the distinction (wheat vs. poplar) and detection of stomata in both datasets. The automated deep learning-based method gave estimates for g_smax within 3.8 and 1.9% of those values manually calculated from an expert for a wheat and poplar dataset, respectively. Semantic segmentation provides a rapid and repeatable method for the estimation of anatomical g_smax from microscopic images of leaf impressions. This advanced method provides a step toward reducing the bottleneck associated with plant phenotyping approaches and will provide a rapid method to assess gas fluxes in plants based on stomata morphometry.

MicroRNA-mediated bioengineering for climate-resilience in crops

Global projections on the climate change and the dynamic environmental perturbations indicate severe impacts on food security in general, and crop yield, vigor and the quality of produce in particular. Sessile plants respond to environmental challenges such as salt, drought, temperature, heavy metals at transcriptional and/or post-transcriptional levels through the stress-regulated network of pathways including transcription factors, proteins and the small non-coding endogenous RNAs. Amongs these, the miRNAs have gained unprecedented attention in recent years as key regulators for modulating gene expression in plants under stress. Hence, tailoring of miRNAs and their target pathways presents a promising strategy for developing multiple stress-tolerant crops. Plant stress tolerance has been successfully achieved through the over expression of microRNAs such as Os-miR408, Hv-miR82 for drought tolerance; OsmiR535A and artificial DST miRNA for salinity tolerance; and OsmiR535 and miR156 for combined drought and salt stress. Examples of miR408 overexpression also showed improved efficiency of irradiation utilization and carbon dioxide fixation in crop plants. Through this review, we present the current understanding about plant miRNAs, their roles in plant growth and stress-responses, the modern toolbox for identification, characterization and validation of miRNAs and their target genes including in silico tools, machine learning and artificial intelligence. Various approaches for up-regulation or knock-out of miRNAs have been discussed. The main emphasis has been given to the exploration of miRNAs for development of bioengineered climate-smart crops that can withstand changing climates and stressful environments, including combination of stresses, with very less or no yield penalties.

Wheat speciation and adaptation: perspectives from reticulate evolution

Reticulate evolution through the interchanging of genetic components across organisms can impact significantly on the fitness and adaptation of species. Bread wheat (Triticum aestivum subsp. aestivum) is one of the most important crops in the world. Allopolyploid speciation, frequent hybridization, extensive introgression, and occasional horizontal gene transfer (HGT) have been shaping a typical paradigm of reticulate evolution in bread wheat and its wild relatives, which is likely to have a substantial influence on phenotypic traits and environmental adaptability of bread wheat. In this review, we outlined the evolutionary history of bread wheat and its wild relatives with a highlight on the interspecific hybridization events, demonstrating the reticulate relationship between species/subspecies in the genera Triticum and Aegilops. Furthermore, we discussed the genetic mechanisms and evolutionary significance underlying the introgression of bread wheat and its wild relatives. An in-depth understanding of the evolutionary process of Triticum species should be beneficial to future genetic study and breeding of bread wheat.

Climate impacts on global agriculture emerge earlier in new generation of climate and crop models

Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project's Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to -6% (SSP126) and from +1% to -24% (SSP585)-explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO₂ concentrations and expanded high-latitude gains. The 'emergence' of climate impacts consistently occurs earlier in the new projections-before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

Using a gene-based phenology model to identify optimal flowering periods of spring wheat in irrigated mega-environments

To maximize the grain yield of spring wheat, flowering needs to coincide with the optimal flowering period (OFP) by minimizing frost and heat stress on reproductive development. This global study conducted a comprehensive modelling analysis of genotype, environment, and management to identify the OFPs for sites in irrigated mega-environments of spring wheat where the crop matures during a period of increasing temperatures. We used a gene-based phenology model to conduct long-term simulation analysis with parameterized genotypes to identify OFPs and optimal sowing dates for sites in irrigated mega-environments, considering the impacts of frost and heat stress on yield. The validation results showed that the gene-based model accurately predicted wheat heading dates across global wheat environments. The long-term simulations indicated that frost and heat stress significantly advanced or delayed OFPs and shrank the durations of OFPs in irrigated mega-environments when compared with OFPs where the model excluded frost and heat stress impacts. The simulation results (incorporating frost and heat penalties on yield) also showed that earlier flowering generally resulted in higher yields, and early sowing dates and/or early flowering genotypes were suggested to achieve early flowering. These results provided an interpretation of the regulation of wheat flowering to the OFP by the selection of sowing date and cultivar to achieve higher yields in irrigated mega-environments.

Prediction of municipality-level winter wheat yield based on meteorological data using machine learning in Hokkaido, Japan

This study analyzed meteorological constraints on winter wheat yield in the northern Japanese island, Hokkaido, and developed a machine learning model to predict municipality-level yields from meteorological data. Compared to most wheat producing areas, this island is characterized by wet climate owing to greater annual precipitation and abundant snowmelt water supply in spring. Based on yield statistics collected from 119 municipalities for 14 years (N = 1,516) and high-resolution surface meteorological data, correlation analyses showed that precipitation, daily minimum air temperature, and irradiance during the grain-filling period had significant effects on the yield throughout the island while the effect of snow depth in early winter and spring was dependent on sites. Using 10-d mean meteorological data within a certain period between seeding and harvest as predictor variables and one-year-leave-out cross-validation procedure, performance of machine learning models based on neural network (NN), random forest (RF), support vector machine regression (SVR), partial least squares regression (PLS), and cubist regression (CB) were compared to a multiple linear regression model (MLR) and a null model that returns an average yield of the municipality. The root mean square errors of PLS, SVR, and RF were 872, 982, and 1,024 kg ha⁻¹ and were smaller than those of MLR (1,068 kg ha⁻¹) and null model (1,035 kg ha⁻¹). These models outperformed the controls in other metrics including Pearson’s correlation coefficient and Nash-Sutcliffe efficiency. Variable importance analysis on PLS indicated that minimum air temperature and precipitation during the grain-filling period had major roles in the prediction and excluding predictors in this period (i.e. yield forecast with a longer lead-time) decreased forecast performance of the models. These results were consistent with our understanding of meteorological impacts on wheat yield, suggesting usefulness of explainable machine learning in meteorological crop yield prediction under wet climate.

Temporal Pattern Analysis of Cropland Phenology in Shandong Province of China Based on Two Long-Sequence Remote Sensing Data

Vegetation phenology dynamics have attracted worldwide attention due to its direct response to global climate change and the great influence on terrestrial carbon budgets and ecosystem productivity in the past several decades. However, most studies have focused on phenology investigation on natural vegetation, and only a few have explored phenology variation of cropland. In this study, taking the typical cropland in the Shandong province of China as the target, we analyzed the temporal pattern of the Normalized Difference Vegetation Index (NDVI) and phenology metrics (growing season start (SOS) and end (EOS)) derived from the Global Inventory Monitoring and Modeling System (GIMMS) 3-generation version 1 (1982–2015) and the Vegetation Index and Phenology (VIP) version 4 (1981–2016), and then investigated the influence of climate factors and Net Primary Production (NPP, only for EOS) on SOS/EOS. Results show a consistent seasonal profile and interannual variation trend of NDVI for the two products. Annual average NDVI has significantly increased since 1980s, and hugely augmentations of NDVI were detected from March to June for both NDVI products (p < 0.01), which indicates a consistent greening tendency of the study region. SOSs from both products are correlated well with the ground-observed wheat elongation and spike date and have significantly advanced since the 1980s, with almost the same changing rate (0.65/0.64 days yr-1, p < 0.01). EOS also exhibits an earlier but weak advancing trend. Due to the significant advance of SOS, the growing season duration has significantly lengthened. Spring precipitation has a relatively stronger influence on SOS than temperature and shortwave radiation, while a greater correlation coefficient was diagnosed between EOS and autumn temperature/shortwave radiation than precipitation/NDVI. Autumn NPP exhibits a nonlinear effect on EOS, which is first earlier and then later with the increase of autumn NPP. Overall, we highlight the similar capacity of the two NDVI products in characterizing the temporal patterns of cropland phenology.

The Physiological Basis of Improved Heat Tolerance in Selected Emmer-Derived Hexaploid Wheat Genotypes

Wheat is sensitive to high-temperature stress with crop development significantly impaired depending on the severity and timing of stress. Various physiological mechanisms have been identified as selection targets for heat tolerance; however, the complex nature of the trait and high genotype × temperature interaction limits the selection process. A three-tiered phenotyping strategy was used to overcome this limitation by using wheat genotypes developed from the ancient domesticated wheat, emmer (Triticum dicoccon Schrank), which was considered to have a wide variation for abiotic stress tolerance. A contrasting pair of emmer-based hexaploid lines (classified as tolerant; G1 and susceptible; G2) developed from a backcross to the same recurrent hexaploid parent was chosen based on heat stress responses in the field and was evaluated under controlled glasshouse conditions. The same pair of contrasting genotypes was also subsequently exposed to a short period of elevated temperature (4 days) at anthesis under field conditions using in-field temperature-controlled chambers. The glasshouse and field-based heat chambers produced comparable results. G1 was consistently better adapted to both extended and short periods of heat stress through slow leaf senescence under heat stress, which extended the grain filling period, increased photosynthetic capacity, increased grain filling rates, and resulted in greater kernel weight and higher yield. The use of a combination of phenotyping methods was effective in identifying heat tolerant materials and the mechanisms involved.

How does post-flowering heat impact grain growth and its determining processes in wheat?

Wheat grain yield is anticipated to suffer from the increased temperatures expected under climate change. In particular, the effects of post-anthesis temperatures on grain growth and development must be better understood in order to improve crop models. Grain growth and development involve several processes, and we hypothesized that some of the most important processes, namely grain dry biomass and water accumulation, grain volume expansion, and endosperm cell proliferation, will have different thermal sensitivity. To assess this, we established temperature-response curves of these processes for steady post-anthesis temperatures between 15 °C and 36 °C. From anthesis to maturity, grain dry mass, water mass, volume, and endosperm cell number were monitored, whilst considering grain temperature. Different sensitivities to heat of these various processes were revealed. The rate of grain dry biomass accumulation increased linearly up to 25 °C, while the reciprocal of its duration increased linearly up to at least 32 °C. In contrast, the growth rates of traits contributing to grain expansion, such as increase in grain volume and cell numbers, had higher optimum temperatures, while the reciprocal of their durations were significantly lower. These temperature-response curves can contribute to improve current crop models, and allow targeting of specific mechanisms for genetic and genomic studies.

Morpho-Physiological Traits and Functional Markers Based Molecular Dissection of Heat-Tolerance in Urdbean

Urdbean (Vigna mungo L. Hepper) is one of the important pulse crops. Its cultivation is not so popular during summer seasons because this crop is unable to withstand excessive heat stress beside lack of humidity in the atmosphere. Therefore, a panel of 97 urdbean diverse genotypes was assessed for yield under stress and non-stress conditions with an aim to identify heat tolerant genotypes. This study identified 8 highly heat tolerant and 35 highly heat sensitive genotypes based on heat susceptibility index. Further, physiological and biochemical traits-based characterization of a group of six highly heat sensitive and seven highly heat tolerant urdbean genotypes showed genotypic variability for leaf nitrogen balance index (NBI), chlorophyll (SPAD), epidermal flavnols, and anthocyanin contents under 42/25°C max/min temperature. Our results showed higher membrane stability index among heat tolerant genotypes compared to sensitive genotypes. Significant differences among genotypes for ETR at different levels of PAR irradiances and PAR × genotypes interactions indicated high photosynthetic ability of a few genotypes under heat stress. Further, the most highly sensitive genotype PKGU-1 showed a decrease in different fluorescence parameters indicating distortion of PS II. Consequently, reduction in the quantum yield of PS II was observed in a sensitive one as compared to a tolerant genotype. Fluorescence kinetics showed the delayed and fast quenching of Fm in highly heat sensitive (PKGU 1) and tolerant (UPU 85-86) genotypes, respectively. Moreover, tolerant genotype (UPU 85-86) had high antioxidant activities explaining their role for scavenging superoxide radicals (ROS) protecting delicate membranes from oxidative damage. Molecular characterization further pinpointed genetic differences between heat tolerant (UPU 85-86) and heat sensitive genotypes (PKGU 1). These findings will contribute to the breeding toward the development of heat tolerant cultivars in urdbean.

Introducing Beneficial Alleles from Plant Genetic Resources into the Wheat Germplasm

Wheat (Triticum sp.) is one of the world's most important crops, and constantly increasing its productivity is crucial to the livelihoods of millions of people. However, more than a century of intensive breeding and selection processes have eroded genetic diversity in the elite genepool, making new genetic gains difficult. Therefore, the need to introduce novel genetic diversity into modern wheat has become increasingly important. This review provides an overview of the plant genetic resources (PGR) available for wheat. We describe the most important taxonomic and phylogenetic relationships of these PGR to guide their use in wheat breeding. In addition, we present the status of the use of some of these resources in wheat breeding programs. We propose several introgression schemes that allow the transfer of qualitative and quantitative alleles from PGR into elite germplasm. With this in mind, we propose the use of a stage-gate approach to align the pre-breeding with main breeding programs to meet the needs of breeders, farmers, and end-users. Overall, this review provides a clear starting point to guide the introgression of useful alleles over the next decade.

Drought and High Temperature Stress in Sorghum: Physiological, Genetic, and Molecular Insights and Breeding Approaches

Sorghum is one of the staple crops for millions of people in Sub-Saharan Africa (SSA) and South Asia (SA). The future climate in these sorghum production regions is likely to have unexpected short or long episodes of drought and/or high temperature (HT), which can cause significant yield losses. Therefore, to achieve food and nutritional security, drought and HT stress tolerance ability in sorghum must be genetically improved. Drought tolerance mechanism, stay green, and grain yield under stress has been widely studied. However, novel traits associated with drought (restricted transpiration and root architecture) need to be explored and utilized in breeding. In sorghum, knowledge on the traits associated with HT tolerance is limited. Heat shock transcription factors, dehydrins, and genes associated with hormones such as auxin, ethylene, and abscisic acid and compatible solutes are involved in drought stress modulation. In contrast, our understanding of HT tolerance at the omic level is limited and needs attention. Breeding programs have exploited limited traits with narrow genetic and genomic resources to develop drought or heat tolerant lines. Reproductive stages of sorghum are relatively more sensitive to stress compared to vegetative stages. Therefore, breeding should incorporate appropriate pre-flowering and post-flowering tolerance in a broad genetic base population and in heterotic hybrid breeding pipelines. Currently, more than 240 QTLs are reported for drought tolerance-associated traits in sorghum prospecting discovery of trait markers. Identifying traits and better understanding of physiological and genetic mechanisms and quantification of genetic variability for these traits may enhance HT tolerance. Drought and HT tolerance can be improved by better understanding mechanisms associated with tolerance and screening large germplasm collections to identify tolerant lines and incorporation of those traits into elite breeding lines. Systems approaches help in identifying the best donors of tolerance to be incorporated in the SSA and SA sorghum breeding programs. Integrated breeding with use of high-throughput precision phenomics and genomics can deliver a range of drought and HT tolerant genotypes that can improve yield and resilience of sorghum under drought and HT stresses.

Improvement in drought tolerance in bread wheat is related to an improvement in osmolyte production, antioxidant enzyme activities, and gaseous exchange

Water deficit stress negatively affects wheat growth, physiology, and yield. In lab and hydroponic experiments, osmotic stress levels (control, −2, −4, −6 and −8 Bars) created by PEG-6000, caused a significant decline in germination, mean germination time, root, shoot, and coleoptile length in both wheat genotypes examined. Germination was inhibited more in Wafaq-2001 than in Chakwal-50. Wafaq-2001 showed a higher susceptibility index based on root and shoot dry weight than did Chakwal-50. Wheat plants exhibited osmotic adjustment through the accumulation of proline, soluble sugars, soluble proteins, and free amino acids, and increased antioxidation activities of superoxide dismutase, peroxidase, catalase, and malondialdehyde. Increasing water deficit stress caused a linear decline in chlorophyll contents, leaf membrane stability, and relative water content in all wheat plants, with Wafaq-2001 showing a more severe negative impact on these parameters with increasing stress levels. The results suggest the possibility of utilizing some of these parameters as quantitative indicators of water stress tolerance in plants. Gas exchange measurements (photosynthesis, transpiration, stomatal conductance), leaf osmotic potential, water potential, and yield attributes decreased more abruptly with increasing water deficit, whereas leaf cuticular wax content increased in both genotypes, with more severe impacts on Wagaq-2001. More reduction in biochemical, physiological, and yield attributes was observed in Wafaq-2001 than was observed in Chakwal-50. Based on these results, we can conclude that Chakwal-50 is a more drought-tolerant genotype, and has excellent potential for future use in breeding programs to improve wheat drought tolerance.