Rising temperatures reduce global wheat production

Heat and Drought Stress Advanced Global Wheat Harvest Timing from 1981–2014

Studying wheat phenology can greatly enhance our understanding of how wheat growth responds to climate change, and guide us to reasonably confront its influence. However, comprehensive global-scale wheat phenology–climate analysis is still lacking. In this study, we extracted the wheat harvest date (WHD) from 1981–2014 from satellite data using threshold-, logistic-, and shape-based methods. Then, we analyzed the effects of heat and drought stress on WHD based on gridded daily temperature and monthly drought data (the Palmer drought severity index (PDSI) and the standardized precipitation evapotranspiration index (SPEI)) over global wheat-growing areas. The results show that WHD was generally delayed from the low to mid latitudes. With respect to variation trends, we detected a significant advancement of WHD in 32.1% of the world’s wheat-growing areas since 1981, with an average changing rate of −0.25 days/yr. A significant negative correlation was identified between WHD and the prior three months’ normal-growing-degree-days across 50.4% of the study region, which implies that greater preseason effective temperature accumulation may cause WHD to occur earlier. Meanwhile, WHD was also found to be significantly and negatively correlated with the prior three months’ extreme-growing-degree-days across only 9.6% of the study region (mainly located in northern South Asia and north Central-West Asia). The effects of extreme heat stress were weaker than those of normal thermal conditions. When extreme drought (measured by PDSI/SPEI) occurred in the current month, in the month prior to WHD, and in the second month prior to WHD, it forced WHD to advance by about 9.0/8.1 days, 13.8/12.2 days, and 10.8/5.3 days compared to normal conditions, respectively. In conclusion, we highlight the effects that heat and drought stress have on advancing wheat harvest timing, which should be a research focus under future climate change.

Genome-wide association studies of seven agronomic traits under two sowing conditions in bread wheat

BACKGROUND

Wheat is a cool seasoned crop requiring low temperature during grain filling duration and therefore increased temperature causes significant yield reduction. A set of 125 spring wheat genotypes from International Maize and Wheat Improvement Centre (CIMMYT-Mexico) was evaluated for phenological and yield related traits at three locations in Pakistan under normal sowing time and late sowing time for expose to prolonged high temperature. With the help of genome-wide association study using genotyping-by-sequencing, marker trait associations (MTAs) were observed separately for the traits under normal and late sown conditions.

RESULTS

Significant reduction ranging from 9 to 74% was observed in all traits under high temperature. Especially 30, 25, 41 and 66% reduction was observed for days to heading (DH), plant height (PH), spikes per plant (SPP) and yield respectively. We identified 55,954 single nucleotide polymorphisms (SNPs) using genotyping by sequencing of these 125 hexaploid spring wheat genotypes and conducted genome-wide association studies (GWAS) for days to heading (DH), grain filled duration (GFD), plant height (PH), spikes per plant (SPP), grain number per spike (GNS), thousand kernel weight (TKW) and grain yield per plot (GY). Genomic regions identified through GWAS explained up to 13% of the phenotypic variance, on average. A total of 139 marker-trait associations (MTAs) across three wheat genomes (56 on genome A, 55 on B and 28 on D) were identified for all the seven traits studied. For days to heading, 20; grain filled duration, 21; plant height, 23; spikes per plant, 13; grain numbers per spike, 8; thousand kernel weight, 21 and for grain yield, 33 MTAs were detected under normal and late sown conditions.

CONCLUSIONS

This study identifies the essential resource of genetics research and underpins the chromosomal regions of seven agronomic traits under normal and high temperature. Significant relationship was observed between the number of favored alleles and trait observations. Fourteen protein coding genes with their respective annotations have been searched with the sequence of seven MTAs which were identified in this study. These findings will be helpful in the development of a breeder friendly platform for the selection of high yielding wheat lines at high temperature areas.

The nitrogen nutrition potential of arable soils

Soils are an important source of nitrogen in many of the world’s cropping systems. Especially in low-input production systems, nitrogen release from soil organic matter turn-over is the major part of the crop’s nitrogen supply and research suggests that this process is significantly affected by changes in climate. The knowledge of the amount of nitrogen being accountable for crop nutrition is purely empirical in many production areas in the world and data as a foundation of global-scale climate change and food security assessments is scarce. Here we demonstrate that nitrogen mineralisation in general follows similar rules as for carbon, but with different implications for agricultural systems. We analysed 340 data sets from previously published incubation experiments for potential nitrogen mineralisation which covered a large range of soils and climate conditions. We find that under warm and all-year humid conditions the share of potentially mineralisable nitrogen in the soil’s total nitrogen is significantly smaller than in dry or temperate environments. We conclude that – despite relatively high soil nitrogen stocks – soil-borne nitrogen supply for crop production is very low in tropical and humid subtropical environments, which is a critical piece of information for global assessments of agricultural production and food security.

Assessing yield gap in high productive countries by designing wheat ideotypes

Designing crop ideotypes in silico is a powerful tool to explore the crop yield potential and yield gap. We defined yield gap as the difference between yield potential of a crop ideotype optimized under local environment and yield of an existing cultivar under optimal management. Wheat ideotypes were designed for the current climate using the Sirius model for both water-limited and irrigated conditions in two high wheat-productive countries viz. the United Kingdom (UK) and New Zealand (NZ) with the objective of estimating yield gap. The mean ideotype yields of 15.0-19.0 t ha-1 were achieved in water-limited conditions in the UK and NZ, whereas 15.6-19.5 t ha-1 under irrigated conditions. Substantial yield gaps were found in both water-limited, 28-31% (4-6 t ha-1), and irrigated conditions, 30-32% (5-6 t ha-1) in the UK and NZ. Both yield potential (25-27%) and yield gap (32-38%) were greater in NZ than the UK. Ideotype design is generic and could apply globally for estimating yield gap. Despite wheat breeding efforts, the considerable yield gap still potentially exists in high productive countries such as the UK and NZ. To accelerate breeding, wheat ideotypes can provide the key traits for wheat improvement and closing the yield gap.

Global wheat production with 1.5 and 2.0°C above pre-industrial warming

Efforts to limit global warming to below 2°C in relation to the pre-industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0°C warming above the pre-industrial period) on global wheat production and local yield variability. A multi-crop and multi-climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by -2.3% to 7.0% under the 1.5°C scenario and -2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980-2010, when considering changes in local temperature, rainfall, and global atmospheric CO₂ concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter-annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer-India, which supplies more than 14% of global wheat. The projected global impact of warming <2°C on wheat production is therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade.

Carbon balance and source-sink metabolic changes in winter wheat exposed to high night-time temperature

Carbon loss under high night-time temperature (HNT) leads to significant reduction in wheat yield. Growth chamber studies were carried out using six winter wheat genotypes, to unravel postheading HNT (23°C)-induced alterations in carbon balance, source-sink metabolic changes, yield, and yield-related traits compared with control (15°C) conditions. Four of the six tested genotypes recorded a significant increase in night respiration after 4 days of HNT exposure, with all the cultivars regulating carbon loss and demonstrating different degree of acclimation to extended HNT exposure. Metabolite profiling indicated carbohydrate metabolism in spikes and activation of the TriCarboxylic Acid (TCA) cycle in leaves as important pathways operating under HNT exposure. A significant increase in sugars, sugar-alcohols, and phosphate in spikes of the tolerant genotype (Tascosa) indicated osmolytes and membrane protective mechanisms acting against HNT damage. Enhanced night respiration under HNT resulted in higher accumulation of TCA cycle intermediates like isocitrate and fumarate in leaves of the susceptible genotype (TX86A5606). Lower grain number due to lesser productive spikes and reduced grain weight due to shorter grain-filling duration determined HNT-induced yield loss in winter wheat. Traits and mechanisms identified will help catalyze the development of physiological and metabolic markers for breeding HNT-tolerant wheat.

Identification of Potential Genes Responsible for Thermotolerance in Wheat under High Temperature Stress

Wheat, a major worldwide staple food crop, is relatively sensitive to a changing environment, including high temperature. The comprehensive mechanism of heat stress response at the molecular level and exploitation of candidate tolerant genes are far from enough. Using transcriptome data, we analyzed the gene expression profiles of wheat under heat stress. A total of 1705 and 17 commonly differential expressed genes (DEGs) were identified in wheat grain and flag leaf, respectively, through transcriptome analysis. Gene Ontology (GO) and pathway enrichment were also applied to illustrate the functions and metabolic pathways of DEGs involved in thermotolerance of wheat grain and flag leaf. Furthermore, our data suggest that there may be a more complex molecular mechanism or tighter regulatory network in flag leaf than in grain under heat stress over time, as less commonly DEGs, more discrete expression profiles of genes (principle component analysis) and less similar pathway response were observed in flag leaf. In addition, we found that transcriptional regulation of zeatin, brassinosteroid and flavonoid biosynthesis pathways may play an important role in wheat’s heat tolerance. The expression changes of some genes were validated using quantitative real-time polymerase chain reaction and three potential genes involved in the flavonoid biosynthesis process were identified.

Q&A: modern crop breeding for future food security

Farmers around the world have recently experienced significant crop losses due to severe heat and drought. Such extreme weather events and the need to feed a rapidly growing population have raised concerns for global food security. While plant breeding has been very successful and has delivered today’s highly productive crop varieties, the rate of genetic improvement must double to meet the projected future demands. Here we discuss basic principles and features of crop breeding and how modern technologies could efficiently be explored to boost crop improvement in the face of increasingly challenging production conditions.

Increased temperatures and elevated CO2 levels reduce the sensitivity of Conyza canadensis and Chenopodium album to glyphosate

Herbicides are the most commonly used means of controlling weeds. Recently, there has been growing concern over the potential impacts of global climate change, specifically, increasing temperatures and elevated carbon dioxide (CO2) concentrations, on the sensitivity of weeds to herbicides. Here, glyphosate response of both Conyza canadensis and Chenopodium album was evaluated under different environmental conditions. Reduced glyphosate sensitivity was observed in both species in response to increased temperature, elevated CO2 level, and the combination of both factors. Increased temperature had greater effect on plant survival than elevated CO2 level. In combination, high temperature and elevated CO2 level resulted in loss of apical dominance and rapid necrosis in glyphosate-treated plants. To investigate the mechanistic basis of reduced glyphosate sensitivity, translocation was examined using 14C-glyphosate. In plants that were subjected to high temperatures and elevated CO2 level, glyphosate was more rapidly translocated out of the treated leaf to shoot meristems and roots than in plants grown under control conditions. These results suggest that altered glyphosate translocation and tissue-specific sequestration may be the basis of reduced plant sensitivity. Therefore, overreliance on glyphosate for weed control under changing climatic conditions may result in more weed control failures.

Impacts of rising temperature, carbon dioxide concentration and sea level on wheat production in North Nile delta

Climate change poses a serious threat to arid and low elevation coastal zones. Kafrelsheikh governorate, as a large agricultural and coastal region on the Egyptian North Nile Delta, is one of the most vulnerable areas to higher temperature and global sea level rise. Two DSSAT wheat models (CERES and N-Wheat) were calibrated using a local cultivar (Misr3) grown under irrigated conditions in Egypt. Experimental data of two successive growing seasons during 2014/2015 and 2015/2016 were used for calibration using different treatments of irrigation, planting dates and fertilization. Both models simulated the phenology and wheat yield well, with root mean square deviation of <10%, and d-index > 0.80. Climate change sensitivity analysis showed that rising temperature by 1 °C to 4 °C decreased wheat yield by 17.6%. However, elevated atmospheric CO₂ concentrations increased yield and could overtake some of the negative temperature responses. Sea level rise by 2.0 m will reduce the extent of agricultural land on the North Nile Delta of Egypt by ~60% creating an additional challenge to wheat production in this region.

Can wheat survive in heat? Assembling tools towards successful development of heat stress tolerance in Triticum aestivum L

Wheat is an important cereal crop that fulfils the calorie demands of the global humanity. Rapidly expanding populations are exposed to a fast approaching acute shortage in the adequate supply of food and fibre from agricultural resources. One of the significant threats to food security lies in the constantly increasing global temperatures which inflict serious injuries to the plants in terms of various physiological, biochemical and molecular processes. Wheat being a cool season crop is majorly impacted by the heat stress which adversely affects crop productivity and yield. These challenges would be potentially defeated with the implementation of genetic engineering strategies coupled with the new genome editing approaches. Development of transgenic plants for various crops has proved very effective for the incorporation of improved varietal traits in context of heat stress. With a similar approach, we need to target for the generation of heat stress tolerant wheat varieties which are capable of survival in such adverse conditions and yet produce well. In this review, we enumerate the current status of research on the heat stress responsive genes/factors and their potential role in mitigating heat stress in plants particularly in wheat with an aim to help the researchers get a holistic view of this topic. Also, we discuss on the prospective signalling pathway that is triggered in plants in general under heat stress.

Earth observations and integrative models in support of food and water security

Global food production depends upon many factors that Earth observing satellites routinely measure about water, energy, weather, and ecosystems. Increasingly sophisticated, publicly-available satellite data products can improve efficiencies in resource management and provide earlier indication of environmental disruption. Satellite remote sensing provides a consistent, long-term record that can be used effectively to detect large-scale features over time, such as a developing drought. Accuracy and capabilities have increased along with the range of Earth observations and derived products that can support food security decisions with actionable information. This paper highlights major capabilities facilitated by satellite observations and physical models that have been developed and validated using remotely-sensed observations. Although we primarily focus on variables relevant to agriculture, we also include a brief description of the growing use of Earth observations in support of aquaculture and fisheries.

Wheat Blast in Bangladesh: The Current Situation and Future Impacts

Wheat blast occurred in Bangladesh for the first time in Asia in 2016. It is caused by a fungal pathogen, Magnaporthe oryzae Triticum (MoT) pathotype. In this review, we focused on the current status of the wheat blast in regard to host, pathogen, and environment. Despite the many efforts to control the disease, it expanded to neighboring regions including India, the world's second largest wheat producer. However, the disease occurrence has definitely decreased in quantity, because of many farmers chose to grow alternate crops according to the government's directions. Bangladesh government planned to introduce blast resistant cultivars but knowledges about genetics of resistance is limited. The genome analyses of the pathogen population revealed that the isolates caused wheat blast in Bangladesh are genetically close to a South American lineage of Magnaporthe oryzae. Understanding the genomes of virulent strains would be important to find target resistance genes for wheat breeding. Although the drier winter weather in Bangladesh was not favorable for development of wheat blast before, recent global warming and climate change are posing an increasing risk of disease development. Bangladesh outbreak in 2016 was likely to be facilitated by an extraordinary warm and humid weather in the affected districts before the harvest season. Coordinated international collaboration and steady financial supports are needed to mitigate the fearsome wheat blast in South Asia before it becomes a catastrophe.

Effects of various warming patterns on Cd transfer in soil-rice systems under Free Air Temperature Increase (FATI) conditions

Global warming has become an important research topic in different disciplines around the world, especially in the fields of environment quality and food security. As a potential problem in soil environments, cadmium (Cd) contamination of rice under global warming conditions has not been thoroughly investigated. In this study, the fate of Cd in soil-rice systems under various warming patterns was studied via pot experiments under Free Air Temperature Increase (FATI) conditions. The patterns of warming included different temperatures (0.5 °C and 0.8 °C), different day-night durations (nighttime, daytime, and the whole day), and different warming stages (WSx) (including WS1 (seedling to tillering), WS2 (jointing to booting), WS3 (heading), WS4 (grain filling to milk ripening)). At harvest, samples of different rice tissues were collected and the Cd concentrations were measured. The results showed that warming significantly increased Cd concentrations in grain by 1.45 and 2.31 times, which was positively correlated with the two temperature increases (0.5 °C and 0.8 °C), respectively. Both daytime and nighttime warming significantly increased the Cd concentration in grain, and the daytime dominated Cd translocation from roots to shoots. In addition, warming in individual growth stages contributed to increases in Cd accumulation in grain by 31.6% (WS1), 15.0% (WS2), 20.6% (WS3), and 32.8% (WS4), respectively. Specifically, warming during the vegetative phase boosted Cd translocation from roots to shoots, while warming during maturation further increased Cd uptake and remobilization into grain. The projected results could provide a new and in-depth understanding of the fate of Cd in soil-rice systems under global warming conditions in Cd contaminated areas.

Impact of Climate Change on Crops Adaptation and Strategies to Tackle Its Outcome: A Review

Agriculture and climate change are internally correlated with each other in various aspects, as climate change is the main cause of biotic and abiotic stresses, which have adverse effects on the agriculture of a region. The land and its agriculture are being affected by climate changes in different ways, e.g., variations in annual rainfall, average temperature, heat waves, modifications in weeds, pests or microbes, global change of atmospheric CO₂ or ozone level, and fluctuations in sea level. The threat of varying global climate has greatly driven the attention of scientists, as these variations are imparting negative impact on global crop production and compromising food security worldwide. According to some predicted reports, agriculture is considered the most endangered activity adversely affected by climate changes. To date, food security and ecosystem resilience are the most concerning subjects worldwide. Climate-smart agriculture is the only way to lower the negative impact of climate variations on crop adaptation, before it might affect global crop production drastically. In this review paper, we summarize the causes of climate change, stresses produced due to climate change, impacts on crops, modern breeding technologies, and biotechnological strategies to cope with climate change, in order to develop climate resilient crops. Revolutions in genetic engineering techniques can also aid in overcoming food security issues against extreme environmental conditions, by producing transgenic plants.

Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations

Climate change is expected to severely affect cropping systems and food production in many parts of the world unless local adaptation can ameliorate these impacts. Ensembles of crop simulation models can be useful tools for assessing if proposed adaptation options are capable of achieving target yields, whilst also quantifying the share of uncertainty in the simulated crop impact resulting from the crop models themselves. Although some studies have analysed the influence of ensemble size on model outcomes, the effect of ensemble composition has not yet been properly appraised. Moreover, results and derived recommendations typically rely on averaged ensemble simulation results without accounting sufficiently for the spread of model outcomes. Therefore, we developed an Ensemble Outcome Agreement (EOA) index, which analyses the effect of changes in composition and size of a multi-model ensemble (MME) to evaluate the level of agreement between MME outcomes with respect to a given hypothesis (e.g. that adaptation measures result in positive crop responses). We analysed the recommendations of a previous study performed with an ensemble of 17 crop models and testing 54 adaptation options for rainfed winter wheat (Triticum aestivum L.) at Lleida (NE Spain) under perturbed conditions of temperature, precipitation and atmospheric CO2 concentration. Our results confirmed that most adaptations recommended in the previous study have a positive effect. However, we also showed that some options did not remain recommendable in specific conditions if different ensembles were considered. Using EOA, we were able to identify the adaptation options for which there is high confidence in their effectiveness at enhancing yields, even under severe climate perturbations. These include substituting spring wheat for winter wheat combined with earlier sowing dates and standard or longer duration cultivars, or introducing supplementary irrigation, the latter increasing EOA values in all cases. There is low confidence in recovering yields to baseline levels, although this target could be attained for some adaptation options under moderate climate perturbations. Recommendations derived from such robust results may provide crucial information for stakeholders seeking to implement adaptation measures.

Climate change impact and adaptation for wheat protein

Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32-multi-model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO₂ concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low-rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO₂ . Introducing genotypes adapted to warmer temperatures (and also considering changes in CO₂ and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by -1.1 percentage points, representing a relative change of -8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production.

Climate change exacerbates pest damage through reduced pesticide efficacy

Pesticide efficacy is strongly associated with environmental conditions. Conditional resistance defined as a reduction in pesticide sensitivity under changed environmental conditions has been widely detected under climatic changes such as elevated temperatures and CO₂ enrichment. Given the effects of environmental conditions on pesticide sensitivity, many of the putative resistance reports made by farmers may be due to pesticide application followed by non-optimal environmental conditions rather than the evolution of resistance. This type of conditional resistance may be the result of phenotypic plasticity or epigenetic changes in response to environmental changes. Elevated temperatures and CO₂ enrichment can directly lead to reduced pesticide efficacy by altering pesticide metabolism and translocation, or indirectly increasing pesticide detoxification in host-plants thus reducing pesticide availability for the target pest. Stress-related signal transduction pathways, as well as physiological changes, can both be associated with accelerated pesticide detoxification under climatic changes. The possibility for parallel mechanisms controlling these responses in different pest species should be considered. It is proposed that the same mechanisms leading to non-target site resistance in pests may also play a role in conditional resistance, suggesting we can predict the pesticides to which pests are likely to be less responsive under changing climatic conditions. Using adjuvants to improve pesticide translocation or reduce pesticide metabolism, alongside with new technologies such as using nanoparticles may result in higher pesticide functionality under the projected climate change. Exploring the physiological, transcriptional and biochemical basis underlying conditional resistance is crucial in maintaining future pest management under changing environmental conditions. © 2018 Society of Chemical Industry.

Projected increases in intensity, frequency, and terrestrial carbon costs of compound drought and aridity events

Drought and atmospheric aridity pose large risks to ecosystem services and agricultural production. However, these factors are seldom assessed together as compound events, although they often occur simultaneously. Drought stress on terrestrial carbon uptake is characterized by soil moisture (SM) deficit and high vapor pressure deficit (VPD). We used in situ observations and 15 Earth system models to show that compound events with very high VPD and low SM occur more frequently than expected if these events were independent. These compound events are projected to become more frequent and more extreme and exert increasingly negative effects on continental productivity. Models project intensified negative effects of high VPD and low SM on vegetation productivity, with the intensification of SM exceeding those of VPD in the Northern Hemisphere. These results highlight the importance of compound extreme events and their threats for the capability of continents to act as a carbon sink.

Irrigation reduces the negative effect of global warming on winter wheat yield and greenhouse gas intensity

Global warming may exacerbate drought, decrease crop yield and affect greenhouse gas (GHG) emissions in semi-arid regions. However, the interactive effects of increases in temperature and water availability on winter wheat yield and GHG emissions in semi-arid climates are not well-understood. Here, we report on a two-year field experiment that examined the effects of a mean soil temperature increase of ~2 °C (at 5 cm depth) with and without additional irrigation on wheat yield and GHG emissions. Infrared heaters were placed above the crop canopy at a height of 1.8 m to simulate warming. Fluxes of CH₄, CO₂ and N₂O were measured using closed static chamber technique once per week during the wheat growing seasons. Warming decreased wheat yield by 28% in the relatively dry year of 2015, while supplemental irrigation nullified the warming effect completely. Warming did not alter the wheat yield significantly in the relatively wet year of 2016, but supplemental irrigation with no warming decreased the wheat yield by 25%. Warming increased CO₂ emissions by 28% and CH₄ uptake by 24% and tended to decrease N₂O emissions. Supplemental irrigation increased N₂O emissions but had little effect on CO₂ emissions and CH₄ uptake. Evidently, warming and supplemental irrigation had interactive effects on wheat yield, GHG emissions and GHG emissions intensity. Precision irrigation appears to be a means of simultaneously increasing wheat yield and reducing GHG emissions under warming conditions in semi-arid areas.

Genetic modification of spikelet arrangement in wheat increases grain number without significantly affecting grain weight

Crop yield is determined by the acquisition and allocation of photoassimilates in sink organs. Therefore, genetic modification of sink size is essential for understanding the complex signaling network regulating sink strength and source activities. Sink size in wheat depends on the number of spikelets per spike, floret/grain number per spikelet as well as the grain weight or dry matter accumulation. Hence, increasing spikelet number and improving sink size are targets for wheat breeding. The main objective of the present work was to genetically modify the wheat spike architecture, i.e., the sink size by introgressing the 'Miracle wheat' or the bh^t-A1 allele into an elite durum wheat cv. Floradur. After four generations of backcrossing to the recurrent parent, Floradur (FL), we have successfully developed Near Isogenic Lines (NILs) with a modified spikelet arrangement thereby increasing spikelet and grain number per spike. Genotyping of bh^t-A1 NILs using the Genotyping-By-Sequencing approach revealed that the size of the introgressed donor segments carrying bh^t-A1 ranged from 2.3 to 38 cM. The size of the shortest donor segment introgressed into bh^t-A1 NILs was estimated to be 9.8 mega base pairs (Mbp). Phenotypic analysis showed that FL-bh^t-A1-NILs (BC3F2 and BC3F3) carry up to seven additional spikelets per spike, leading to up to 29% increase in spike dry weight at harvest (SDW_h). The increased SDW_h was accompanied by up to 23% more grains per spike. More interestingly, thousand kernel weight (TKW) did not show significant differences between FL-bh^t-A1-NILs and Floradur, suggesting that besides increasing spikelet number, bh^t-A1 could also be targeted for increasing grain yield in wheat. Our study suggests that the genetic modification of spikelet number in wheat can be an entry point for improving grain yield, most interestingly and also unexpectedly without the trade-off effects on TKW. Hence, FL-bh^t-A1-NILs are not only essential for increasing grain number, but also for understanding the molecular and genetic mechanism of the source-sink interaction for a clearer picture of the complex signaling network regulating sink strength and source activities.

Decline in climate resilience of European wheat

Food security under climate change depends on the yield performance of staple food crops. We found a decline in the climate resilience of European wheat in most countries during the last 5 to 15 y, depending on the country. The yield responses of all the cultivars to different weather events were relatively similar within northern and central Europe, within southern European countries, and specifically regarding durum wheat. We also found serious Europe-wide gaps in wheat resilience, especially regarding yield performance under abundant rain. Climate resilience is currently not receiving the attention it deserves by breeders, seed and wheat traders, and farmers. Consequently, the results provide insights into the required learning tools, economic incentives, and role of public actors.

Food security relies on the resilience of staple food crops to climatic variability and extremes, but the climate resilience of European wheat is unknown. A diversity of responses to disturbance is considered a key determinant of resilience. The capacity of a sole crop genotype to perform well under climatic variability is limited; therefore, a set of cultivars with diverse responses to weather conditions critical to crop yield is required. Here, we show a decline in the response diversity of wheat in farmers’ fields in most European countries after 2002–2009 based on 101,000 cultivar yield observations. Similar responses to weather were identified in cultivar trials among central European countries and southern European countries. A response diversity hotspot appeared in the trials in Slovakia, while response diversity “deserts” were identified in Czechia and Germany and for durum wheat in southern Europe. Positive responses to abundant precipitation were lacking. This assessment suggests that current breeding programs and cultivar selection practices do not sufficiently prepare for climatic uncertainty and variability. Consequently, the demand for climate resilience of staple food crops such as wheat must be better articulated. Assessments and communication of response diversity enable collective learning across supply chains. Increased awareness could foster governance of resilience through research and breeding programs, incentives, and regulation.

Keeping global warming within 1.5 °C reduces future risk of yield loss in the United States: A probabilistic modeling approach

This study assess the possible outcomes of yield changes in the United States which is responsible for 40% of global maize supply under 1.5 °C and 2 °C global warming scenarios. Instead of providing deterministic estimates, this study introduces a probability-based approach that allow for examination of the associated probability of each outcome, which has great implications for decision-makings. Results show distinct spatial patterns in future yield loss risk associated with temperature rise at the county scale, with highest probability in central and southeastern US, and lowest risk in western US and high production regions such as Iowa. Comparing the estimates under 1.5 °C global warming against that in 2.0 °C warming indicates that keeping global warming within 1.5 °C has great benefits for reducing future yield loss risk. Based on the ensemble mean of 97 climate model simulations, the risk of yield dropping below historical long-term mean is projected to decrease from 81% to 75% for the country as a whole. Such benefit is more evident when considering the risk of yield reduction by 10% and 20%, which is expected to decrease by 25% and 28%, respectively. This suggests that constraining global temperature rise to 1.5 °C has more benefits for reducing extreme yield reductions. Spatially, keeping global warming within 1.5 °C would benefit more in Missouri, South Dakota, Eastern Kansas, Southern Texas and southeastern part of the country than other regions, highlighting the spatially variable benefits of climate mitigation efforts. The analysis framework introduced in this study can also be easily extended to other regions and crops. The results of this study highlight the areas where maize yield is most vulnerable to temperature rise, and the spatially variable benefits for reducing yield loss risk by keeping global warming within 1.5 °C.

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

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

miRNomes involved in imparting thermotolerance to crop plants

Thermal stress is one of the challenges to crop plants that negatively impacts crop yield. To overcome this ever-growing problem, utilization of regulatory mechanisms, especially microRNAs (miRNAs), that provide efficient and precise regulation in a targeted manner have been found to play determining roles. Besides their roles in plant growth and development, many recent studies have shown differential regulation of several miRNAs during abiotic stresses including heat stress (HS). Thus, understanding the underlying mechanism of miRNA-mediated gene expression during HS will enable researchers to exploit this regulatory mechanism to address HS responses. This review focuses on the miRNAs and regulatory networks that were involved in physiological, metabolic and morphological adaptations during HS in plant, specifically in crops. Illustrated examples including, the miR156-SPL, miR169-NF-YA5, miR395-APS/AST, miR396-WRKY, etc., have been discussed in specific relation to the crop plants. Further, we have also discussed the available plant miRNA databases and bioinformatics tools useful for miRNA identification and study of their regulatory role in response to HS. Finally, we have briefly discussed the future prospects about the miRNA-related mechanisms of HS for improving thermotolerance in crop plants.

Breeding for resilience to increasing temperatures: A field trial assessing genetic variation in soft red winter wheat

Breeding for resilience to climate change is a daunting prospect. Crop and climate models tell us that global wheat yields are likely to decline as the climate warms, causing a significant risk to global food security. High temperatures are known to affect crop development yet breeding for tolerance to heat stress is difficult to achieve in field environments. We conducted an active warming study over two years to quantify the effects of heat stress on genetic variation of soft red winter (SRW) wheat (Triticum aestivum L.). Forty SRW cultivars and breeding lines were chosen based on marker genotypes at photoperiod sensitivity and reduced height loci. These genotypes were planted in a randomized complete block design replicated twice across two environments, ambient and artificially warmed. Average heading date occurred 5 days earlier in the warmed environment than in the ambient environment over both years (p ≤ 0.05). On average, grain yield was significantly reduced in the warmed environment by 211.41 kg/ha (p ≤ 0.05) or 4.84%, though we identified 13 genotypes with increased yield in response to warming in both years. Of these genotypes, eight had significantly increased N uptake while six showed significantly increased N utilization efficiency under warming. Under warming, genotypes with wild-type alleles at the Rht-D1 locus display significantly greater yields (p ≤ 0.01) and biomass (p ≤ 0.001) than genotypes with reduced height alleles. Of the 13 genotypes with higher (p ≤ 0.01) yields under warming, nine have the wild-type allele at the Rht-D1 locus in addition to being photoperiod insensitive. The next steps will be to validate these findings in other populations and to develop an efficient breeding/phenotyping scheme that will lead to more resilient cultivars.

Characteristics of Climate Change and Extreme Weather from 1951 to 2011 in China

It has been demonstrated that climate change is an established fact. A good comprehension of climate and extreme weather variation characteristics on a temporal and a spatial scale is important for adaptation and response. In this work, the characteristics of temperature, precipitation, and extreme weather distribution and variation is summarized for a period of 60 years and the seasonal fluctuation of temperature and precipitation is also analyzed. The results illustrate the reduction in daily and annual temperature divergence on both temporal and spatial scales. However, the gaps remain relatively significant. Furthermore, the disparity in daily and annual precipitation are found to be increasing on both temporal and spatial scales. The findings indicate that climate change, to a certain extent, narrowed the temperature gap while widening the precipitation gap on temporal and spatial scales in China.

Multimodel ensembles improve predictions of crop-environment-management interactions

A recent innovation in assessment of climate change impact on agricultural production has been to use crop multimodel ensembles (MMEs). These studies usually find large variability between individual models but that the ensemble mean (e-mean) and median (e-median) often seem to predict quite well. However, few studies have specifically been concerned with the predictive quality of those ensemble predictors. We ask what is the predictive quality of e-mean and e-median, and how does that depend on the ensemble characteristics. Our empirical results are based on five MME studies applied to wheat, using different data sets but the same 25 crop models. We show that the ensemble predictors have quite high skill and are better than most and sometimes all individual models for most groups of environments and most response variables. Mean squared error of e-mean decreases monotonically with the size of the ensemble if models are added at random, but has a minimum at usually 2-6 models if best-fit models are added first. Our theoretical results describe the ensemble using four parameters: average bias, model effect variance, environment effect variance, and interaction variance. We show analytically that mean squared error of prediction (MSEP) of e-mean will always be smaller than MSEP averaged over models and will be less than MSEP of the best model if squared bias is less than the interaction variance. If models are added to the ensemble at random, MSEP of e-mean will decrease as the inverse of ensemble size, with a minimum equal to squared bias plus interaction variance. This minimum value is not necessarily small, and so it is important to evaluate the predictive quality of e-mean for each target population of environments. These results provide new information on the advantages of ensemble predictors, but also show their limitations.

Progress in modelling agricultural impacts of and adaptations to climate change

Modelling is a key tool to explore agricultural impacts of and adaptations to climate change. Here we report recent progress made especially referring to the large project initiatives MACSUR and AgMIP; in particular, in modelling potential crop impacts from field to global using multi-model ensembles. We identify two main fields where further progress is necessary: a more mechanistic understanding of climate impacts and management options for adaptation and mitigation; and focusing on cropping systems and integrative multi-scale assessments instead of single season and crops, especially in complex tropical and neglected but important cropping systems. Stronger linking of experimentation with statistical and eco-physiological crop modelling could facilitate the necessary methodological advances.

Can N management affect the magnitude of yield loss due to heat waves in wheat and maize?

Deleterious effects of heat on crop yields are well documented and the occurrence of heat stresses will likely be a major constraint to achieving increased yields of major crops. Thus, agronomic and genetic strategies for increased resilience to high temperatures will be necessary. Much of the work done on this area has been focused to identify genetic sources of increased resilience and much less has been done on the crop ecology side. Nitrogen (N) fertilization is within the most common management practices used in cereal production, however, there have been limited efforts to elucidate to what degree the level of soil fertility may affect the magnitude of the high temperature effect on crop yield. The likely interaction may be relevant for designing more appropriate fertilization strategies. We conducted different studies on maize (2009-2012) and wheat (2012-2013), always under field conditions, to determine whether the availability of N may be responsible for the magnitude of the yield penalty imposed by heat stress during reproductive phases (i.e. when heat waves are more likely). We concluded that sensitivity to heat stress increased with increasing N availability and speculated that moderate N stress might produce in the crop plants a sort of acclimation to reduce sensitivity to other stresses. Fertilisation recommendations in the future may need to balance the yielding benefits of high N availability with the detrimental effect of increasing sensitivity to heat stress.

Maize yields over Europe may increase in spite of climate change, with an appropriate use of the genetic variability of flowering time

The consequences of climate change on European maize yields may become positive if farmers in 2050 use the decision rules they currently follow for adapting plant cycle duration and sowing dates to the diversity of environmental conditions. Experiments and simulations show that the current genetic variability of flowering time allows identifying a cycle duration that maximizes yield at every maize field in Europe. The assumption that farmers use this optimal cycle length in each site was supported by comparison with historical data. Simulated European production for 2050 was stable under the hypotheses of unchanged practices but was increased if farmers continued adopting the decision rules they currently use for adjusting sowing date and crop cycle duration to local environment.

Projections based on invariant genotypes and agronomic practices indicate that climate change will largely decrease crop yields. The comparatively few studies considering farmers’ adaptation result in a diversity of impacts depending on their assumptions. We combined experiments and process-based modeling for analyzing the consequences of climate change on European maize yields if farmers made the best use of the current genetic variability of cycle duration, based on practices they currently use. We first showed that the genetic variability of maize flowering time is sufficient for identifying a cycle duration that maximizes yield in a range of European climatic conditions. This was observed in six field experiments with a panel of 121 accessions and extended to 59 European sites over 36 years with a crop model. The assumption that farmers use optimal cycle duration and sowing date was supported by comparison with historical data. Simulations were then carried out for 2050 with 3 million combinations of crop cycle durations, climate scenarios, management practices, and modeling hypotheses. Simulated grain production over Europe in 2050 was stable (−1 to +1%) compared with the 1975–2010 baseline period under the hypotheses of unchanged cycle duration, whereas it was increased (+4–7%) when crop cycle duration and sowing dates were optimized in each local environment. The combined effects of climate change and farmer adaptation reduced the yield gradient between south and north of Europe and increased European maize production if farmers continued to make the best use of the genetic variability of crop cycle duration.

Climate Shifts within Major Agricultural Seasons for +1.5 and +2.0 °C Worlds: HAPPI Projections and AgMIP Modeling Scenarios

This study compares climate changes in major agricultural regions and current agricultural seasons associated with global warming of +1.5 or +2.0 °C above pre-industrial conditions. It describes the generation of climate scenarios for agricultural modeling applications conducted as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Global and Regional Assessments. Climate scenarios from the Half a degree Additional warming, Projections, Prognosis and Impacts project (HAPPI) are largely consistent with transient scenarios extracted from RCP4.5 simulations of the Coupled Model Intercomparison Project phase 5 (CMIP5). Focusing on food and agricultural systems and top-producing breadbaskets in particular, we distinguish maize, rice, wheat, and soy season changes from global annual mean climate changes. Many agricultural regions warm at a rate that is faster than the global mean surface temperature (including oceans) but slower than the mean land surface temperature, leading to regional warming that exceeds 0.5 °C between the +1.5 and +2.0 °C Worlds. Agricultural growing seasons warm at a pace slightly behind the annual temperature trends in most regions, while precipitation increases slightly ahead of the annual rate. Rice cultivation regions show reduced warming as they are concentrated where monsoon rainfall is projected to intensify, although projections are influenced by Asian aerosol loading in climate mitigation scenarios. Compared to CMIP5, HAPPI slightly underestimates the CO2 concentration that corresponds to the +1.5 °C World but overestimates the CO2 concentration for the +2.0 °C World, which means that HAPPI scenarios may also lead to an overestimate in the beneficial effects of CO2 on crops in the +2.0 °C World. HAPPI enables detailed analysis of the shifting distribution of extreme growing season temperatures and precipitation, highlighting widespread increases in extreme heat seasons and heightened skewness toward hot seasons in the tropics. Shifts in the probability of extreme drought seasons generally tracked median precipitation changes; however, some regions skewed toward drought conditions even where median precipitation changes were small. Together, these findings highlight unique seasonal and agricultural region changes in the +1.5°C and +2.0°C worlds for adaptation planning in these climate stabilization targets.

Satellite sun-induced chlorophyll fluorescence detects early response of winter wheat to heat stress in the Indian Indo-Gangetic Plains

Extremely high temperatures represent one of the most severe abiotic stresses limiting crop productivity. However, understanding crop responses to heat stress is still limited considering the increases in both the frequency and severity of heat wave events under climate change. This limited understanding is partly due to the lack of studies or tools for the timely and accurate monitoring of crop responses to extreme heat over broad spatial scales. In this work, we use novel spaceborne data of sun-induced chlorophyll fluorescence (SIF), which is a new proxy for photosynthetic activity, along with traditional vegetation indices (Normalized Difference Vegetation Index NDVI and Enhanced Vegetation Index EVI) to investigate the impacts of heat stress on winter wheat in northwestern India, one of the world's major wheat production areas. In 2010, an abrupt rise in temperature that began in March adversely affected the productivity of wheat and caused yield losses of 6% compared to previous year. The yield predicted by satellite observations of SIF decreased by approximately 13.9%, compared to the 1.2% and 0.4% changes in NDVI and EVI, respectively. During early stage of this heat wave event in early March 2010, the SIF observations showed a significant reduction and earlier response, while NDVI and EVI showed no changes and could not capture the heat stress until late March. The spatial patterns of SIF anomalies closely tracked the temporal evolution of the heat stress over the study area. Furthermore, our results show that SIF can provide large-scale, physiology-related wheat stress response as indicated by the larger reduction in fluorescence yield (SIF_yield ) than fraction of photosynthetically active radiation during the grain-filling phase, which may have eventually led to the reduction in wheat yield in 2010. This study implies that satellite observations of SIF have great potential to detect heat stress conditions in wheat in a timely manner and assess their impacts on wheat yields at large scales.

Unconventional splicing of wheat TabZIP60 confers heat tolerance in transgenic Arabidopsis

Conditions that disrupt protein folding, such as heat stress, can overwhelm the capacity of cells to fold proteins, thus causing endoplasmic reticulum (ER) stress. In Arabidopsis thaliana and other plants, inositol-requiring enzyme-1 mediated unconventional splicing of bZIP60 plays a crucial role in the heat and ER stress responses. However, little is known about this pathway in wheat (Triticum aestivum), especially its importance in heat tolerance. Here, we found that heat stress induced upregulation and unconventional splicing of TabZIP60 occurred in wheat seedlings. Constitutive expression of the spliced form of TabZIP60 (TabZIP60s) enhanced heat tolerance in Arabidopsis, but overexpression of the unspliced form (TabZIP60u) did not. RNA-sequencing analysis revealed ER stress related genes involved in heat responses in TabZIP60s-overexpression transgenic Arabidopsis. Chromatin immunoprecipitation-qPCR showed that TabZIP60s directly binds to 17 target genes including AtbZIP60. Also, the 26S proteasome pathway post-translationally regulates TabZIP60s levels during heat stress responses. Our findings suggest that unconventional splicing of TabZIP60 could contribute to heat tolerance in transgenic plants by modulating the expression of ER stress-related genes.

Managing the risk of extreme climate events in Australian major wheat production systems

Extreme climate events (ECEs) such as drought, frost risk and heat stress cause significant economic losses in Australia. The risk posed by ECEs in the wheat production systems of Australia could be better managed through the identification of safe flowering (SFW) and optimal time of sowing (TOS) windows. To address this issue, three locations (Narrabri, Roseworthy and Merredin), three cultivars (Suntop and Gregory for Narrabri, Mace for both Roseworthy and Merredin) and 20 TOS at 1-week intervals between 1 April and 12 August for the period from 1957 to 2007 were evaluated using the Agricultural Production System sIMulator (APSIM)-Wheat model. Simulation results show that (1) the average frequency of frost events decreased with TOS from 8 to 0 days (d) across the four cases (the combination of locations and cultivars), (2) the average frequency of heat stress events increased with TOS across all cases from 0 to 10 d, (3) soil moisture stress (SMS) increased with earlier TOS before reaching a plateau and then slightly decreasing for Suntop and Gregory at Narrabri and Mace at Roseworthy while SMS increased with TOS for Mace at Merredin from 0.1 to 0.8, (4) Mace at Merredin had the earliest and widest SFW (216-260) while Mace at Roseworthy had latest SFW (257-280), (5) frost risk and heat stress determine SFW at wetter sites (i.e. Narrabri and Roseworthy) while frost risk and SMS determine SFW at drier site (i.e. Merredin) and (6) the optimal TOS (window) to maximise wheat yield are 6-20 May, 13-27 May and 15 April at Narrabri, Roseworthy and Merredin, respectively. These findings provide important and specific information for wheat growers about the management of ECE risk on farm. Furthermore, the coupling of the APSIM crop models with state-of-the-art seasonal and intra-seasonal climate forecast information provides an important tool for improved management of the risk of ECEs in economically important cropping industries in the foreseeable future.

Temperature-induced changes in the wheat phosphoproteome reveal temperature-regulated interconversion of phosphoforms

Wheat (Triticum ssp.) is one of the most important human food sources. However, this crop is very sensitive to temperature changes. Specifically, processes during wheat leaf, flower, and seed development and photosynthesis, which all contribute to the yield of this crop, are affected by high temperature. While this has to some extent been investigated on physiological, developmental, and molecular levels, very little is known about early signalling events associated with an increase in temperature. Phosphorylation-mediated signalling mechanisms, which are quick and dynamic, are associated with plant growth and development, also under abiotic stress conditions. Therefore, we probed the impact of a short-term and mild increase in temperature on the wheat leaf and spikelet phosphoproteome. In total, 3822 (containing 5178 phosphosites) and 5581 phosphopeptides (containing 7023 phosphosites) were identified in leaf and spikelet samples, respectively. Following statistical analysis, the resulting data set provides the scientific community with a first large-scale plant phosphoproteome under the control of higher ambient temperature. This community resource on the high temperature-mediated wheat phosphoproteome will be valuable for future studies. Our analyses also revealed a core set of common proteins between leaf and spikelet, suggesting some level of conserved regulatory mechanisms. Furthermore, we observed temperature-regulated interconversion of phosphoforms, which probably impacts protein activity.

Evaluation of different gridded rainfall datasets for rainfed wheat yield prediction in an arid environment

The accuracy of daily output of satellite and reanalysis data is quite crucial for crop yield prediction. This study has evaluated the performance of APHRODITE (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation), PERSIANN (Rainfall Estimation from Remotely Sensed Information using Artificial Neural Networks), TRMM (Tropical Rainfall Measuring Mission), and AgMERRA (The Modern-Era Retrospective Analysis for Research and Applications) precipitation products to apply as input data for CSM-CERES-Wheat crop growth simulation model to predict rainfed wheat yield. Daily precipitation output from various sources for 7 years (2000-2007) was obtained and compared with corresponding ground-observed precipitation data for 16 ground stations across the northeast of Iran. Comparisons of ground-observed daily precipitation with corresponding data recorded by different sources of datasets showed a root mean square error (RMSE) of less than 3.5 for all data. AgMERRA and APHRODITE showed the highest correlation (0.68 and 0.87) and index of agreement (d) values (0.79 and 0.89) with ground-observed data. When daily precipitation data were aggregated over periods of 10 days, the RMSE values, r, and d values increased (30, 0.8, and 0.7) for AgMERRA, APHRODITE, PERSIANN, and TRMM precipitation data sources. The simulations of rainfed wheat leaf area index (LAI) and dry matter using various precipitation data, coupled with solar radiation and temperature data from observed ones, illustrated typical LAI and dry matter shape across all stations. The average values of LAI_max were 0.78, 0.77, 0.74, 0.70, and 0.69 using PERSIANN, AgMERRA, ground-observed precipitation data, APHRODITE, and TRMM. Rainfed wheat grain yield simulated by using AgMERRA and APHRODITE daily precipitation data was highly correlated (r² ≥ 70) with those simulated using observed precipitation data. Therefore, gridded data have high potential to be used to supply lack of data and gaps in ground-observed precipitation data.

Alterations in wheat pollen lipidome during high day and night temperature stress

Understanding the adaptive changes in wheat pollen lipidome under high temperature (HT) stress is critical to improving seed set and developing HT tolerant wheat varieties. We measured 89 pollen lipid species under optimum and high day and/or night temperatures using electrospray ionization-tandem mass spectrometry in wheat plants. The pollen lipidome had a distinct composition compared with that of leaves. Unlike in leaves, 34:3 and 36:6 species dominated the composition of extraplastidic phospholipids in pollen under optimum and HT conditions. The most HT-responsive lipids were extraplastidic phospholipids, phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylinositol, phosphatidic acid, and phosphatidylserine. The unsaturation levels of the extraplastidic phospholipids decreased through the decreases in the levels of 18:3 and increases in the levels of 16:0, 18:0, 18:1, and 18:2 acyl chains. PC and PE were negatively correlated. Higher PC:PE at HT indicated possible PE-to-PC conversion, lower PE formation, or increased PE degradation, relative to PC. Correlation analysis revealed lipids experiencing coordinated metabolism under HT and confirmed the HT responsiveness of extraplastidic phospholipids. Comparison of the present results on wheat pollen with results of our previous research on wheat leaves suggests that similar lipid changes contribute to HT adaptation in both leaves and pollen, though the lipidomes have inherently distinct compositions.

A Modeling Framework to Evaluate the Impacts of Future Climate on Soil Organic Carbon Dynamics

Soil organic C (SOC) is significantly affected by changes in climate that control the physical, chemical, and biological processes in the soil. Simulating the impacts of future climate on SOC is challenging due to the limited availability of soil and climate variables required to properly simulate future SOC dynamics. The main objective of this study was to develop a modeling framework to quantify the impacts of future climate on SOC dynamics. The framework was developed for the Model for Nitrogen and Carbon in Agro-Ecosystems (MONICA) using the data collected from three University of Illinois Crop Science Research Centers. Projected precipitation and air temperature, collected from 32 global circulation models, were used to estimate the climate variables and cropping operation schedules required as inputs in MONICA. Six corn ()-soybean [ (L.) Merr.] rotation scenarios were considered in the simulations. Results showed that the total SOC in the upper 30 cm of the soil was expected to decrease from 43 to 70% in 2015 to 2075, with an uncertainty range of 13 to 16% due to the variation in climate prediction. The SOC in corn-soybean rotation schemes did not vary significantly from that of continuous corn scheme. The ability of a model to simulate realistic results depends significantly on the reliability of input data used to parameterize the model. A methodology that comprehensively estimates the impacts of future climatic conditions on SOC allows for realistic model results that can be used as a basis for environmental options, leading to a sustainable agro-production system.

Simulating Soil Organic Carbon Responses to Cropping Intensity, Tillage, and Climate Change in Pacific Northwest Dryland

Managing dryland cropping systems to increase soil organic C (SOC) under changing climate is challenging after decades of winter wheat ( L.)-fallow and moldboard plow tillage (W-F/MP). The objective was to use CQESTR, a process-based C model, and SOC data collected in 2004, 2008, and 2012 to predict the best management to increase SOC under changing climate in four cropping systems, which included continuous wheat under no tillage (W-W/NT), wheat and sorghum × sudangrass [ (L.) Moench. × L.] under no tillage, wheat-fallow under sweep tillage, and W-F/MP. Since future yields and climate are uncertain, 20 scenarios for each cropping system were simulated with four climate projections and five crop yield scenarios (current crop yields, and 10 or 30% greater or lesser yields). Measured and simulated SOC were significantly ( < 0.0001) correlated ( = 0.98) at all soil depths. Predicted SOC changes ranged from -12.03 to 2.56 Mg C ha in the 1-m soil depth for W-F/MP and W-W/NT, respectively, during the 2012 to 2052 predictive period. Only W-W/NT sequestered SOC at a rate of 0.06 Mg C ha yr under current crop yields and climate. Under climate change and yield scenarios, W-W/NT lost SOC except with a 30% wheat yield increase for 40 yr. Predicted SOC increases in W-W/NT were 0.71, 1.16, and 0.88 Mg C ha under the Oregon Climate Assessment Reports for low emissions and high emissions and the Regional Climate Model version 3 with boundary conditions from the Third Generation Coupled Global Climate Model, respectively, with 30% yield increases. Continuous no-till cropping would increase SOC and improve soil health and resiliency to lessen the impact of extreme weather.

Performance of four crop model for simulations of wheat phenology, leaf growth, biomass and yield across planting dates

Robustness of four wheat simulation model were tested with 2-year field experiments of three cultivars across a wide range of sowing dates in two different climatic regions: Faisalabad (semi-arid) and Layyah (arid), in Punjab-Pakistan. Wheat growing season temperature ranged from -0.1°C to 43°C. The wide series of sowing dates was a unique opportunity to grow the wheat in an environment which temperatures varies from -0.1°C to 43°C. The CERES-Wheat, Nwheat, CROPSIM-Wheat and APSIM-Wheat model were calibrated against the least-stressed treatment for each wheat cultivar. Overall, the four models described performance of early, optimum and late sown wheat well, but poorly described yields of very late planting dates with associated high temperatures during grain filling. The poor accuracy of simulations of yield for extreme planting dates point to the need to improve the accuracy of model simulations at the high end of the growing temperature range, especially given the expected future increases in growing season temperature. Improvement in simulation of maximum leaf area index of wheat for all models is needed. APSIM-Wheat only poorly simulated days to maturity of very and extremely late sown wheat compared to other models. Overall, there is a need of improvement in function of models to response high temperature.

Comparative physiological and metabolomics analysis of wheat (Triticum aestivum L.) following post-anthesis heat stress

Genetic improvement for stress tolerance requires a solid understanding of biochemical processes involved with different physiological mechanisms and their relationships with different traits. The objective of this study was to demonstrate genetic variability in altered metabolic levels in a panel of six wheat genotypes in contrasting temperature regimes, and to quantify the correlation between those metabolites with different traits. In a controlled environment experiment, heat stress (35:28 ± 0.08°C) was initiated 10 days after anthesis. Flag leaves were collected 10 days after heat treatment to employ an untargeted metabolomics profiling using LC-HRMS based technique called IROA. High temperature stress produced significant genetic variations for cell and thylakoid membrane damage, and yield related traits. 64 known metabolites accumulated 1.5 fold of higher or lower due to high temperature stress. In general, metabolites that increased the most under heat stress (L-tryptophan, pipecolate) showed negative correlation with different traits. Contrary, the metabolites that decreased the most under heat stress (drummondol, anthranilate) showed positive correlation with the traits. Aminoacyl-tRNA biosysnthesis and plant secondary metabolite biosynthesis pathways were most impacted by high temperature stress. The robustness of metabolic change and their relationship with phenotypes renders those metabolites as potential bio-markers for genetic improvement.

Abiotic Stress Signaling in Wheat - An Inclusive Overview of Hormonal Interactions During Abiotic Stress Responses in Wheat

Rapid global warming directly impacts agricultural productivity and poses a major challenge to the present-day agriculture. Recent climate change models predict severe losses in crop production worldwide due to the changing environment, and in wheat, this can be as large as 42 Mt/°C rise in temperature. Although wheat occupies the largest total harvested area (38.8%) among the cereals including rice and maize, its total productivity remains the lowest. The major production losses in wheat are caused more by abiotic stresses such as drought, salinity, and high temperature than by biotic insults. Thus, understanding the effects of these stresses becomes indispensable for wheat improvement programs which have depended mainly on the genetic variations present in the wheat genome through conventional breeding. Notably, recent biotechnological breakthroughs in the understanding of gene functions and access to whole genome sequences have opened new avenues for crop improvement. Despite the availability of such resources in wheat, progress is still limited to the understanding of the stress signaling mechanisms using model plants such as Arabidopsis, rice and Brachypodium and not directly using wheat as the model organism. This review presents an inclusive overview of the phenotypic and physiological changes in wheat due to various abiotic stresses followed by the current state of knowledge on the identified mechanisms of perception and signal transduction in wheat. Specifically, this review provides an in-depth analysis of different hormonal interactions and signaling observed during abiotic stress signaling in wheat.

Future warming increases probability of globally synchronized maize production shocks

Meeting the global food demand of roughly 10 billion people by the middle of the 21st century will become increasingly challenging as the Earth's climate continues to warm. Earlier studies suggest that once the optimum growing temperature is exceeded, mean crop yields decline and the variability of yield increases even if interannual climate variability remains unchanged. Here, we use global datasets of maize production and climate variability combined with future temperature projections to quantify how yield variability will change in the world's major maize-producing and -exporting countries under 2 °C and 4 °C of global warming. We find that as the global mean temperature increases, absent changes in temperature variability or breeding gains in heat tolerance, the coefficient of variation (CV) of maize yields increases almost everywhere to values much larger than present-day values. This higher CV is due both to an increase in the SD of yields and a decrease in mean yields. For the top four maize-exporting countries, which account for 87% of global maize exports, the probability that they have simultaneous production losses greater than 10% in any given year is presently virtually zero, but it increases to 7% under 2 °C warming and 86% under 4 °C warming. Our results portend rising instability in global grain trade and international grain prices, affecting especially the ∼800 million people living in extreme poverty who are most vulnerable to food price spikes. They also underscore the urgency of investments in breeding for heat tolerance.