Rising temperatures reduce global wheat production

Quantifying the impact of climate and management strategies on groundwater conservation in the High Plains Aquifer

Groundwater depletion in semi-arid, irrigated regions is accelerating due to intensive agricultural water use. This study uses a linked hydro-agronomic model (DSSAT-MODFLOW) to evaluate crop yield and groundwater elevation under several scenarios of future climate, irrigation system, and planting decision in Finney County, southwest Kansas, a region that has experienced significant groundwater decline over the past 50 years as a result of irrigation within the U.S. High Plains Aquifer region. Model calibration was conducted using the Generalized Likelihood Uncertainty Estimation (GLUE) based on Monte Carlo simulation. The calibrated model was applied to quantitatively assess the impacts of projected climate conditions (2021-2050), using downscaled data from seven General Circulation Models (GCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) under SSP245 and SSP585 scenarios, in combination with various irrigation systems and land-crop-water allocation strategies on crop yield and water table elevation. Results indicate that, under climate change alone, groundwater saturated thickness is projected to decline by 20 %-55 % by 2050. When combined with different management practices, groundwater levels continue to decline regardless of irrigation type and allocation level, indicating that groundwater resources can only be conserved but not fully sustained. Maize production becomes increasingly vulnerable without the adoption of heat- and drought-tolerant cultivars, while soybean, winter wheat, and sorghum remain more resilient across scenarios. A drier future climate condition further constrains management options that simultaneously support yield and groundwater conservation goals. These findings provide critical insights into developing adaptive irrigation and cropping strategies in the High Plains Aquifer and other groundwater-dependent agricultural regions worldwide.

Increasing severity of large-scale fires prolongs recovery time of forests globally since 2001

Ongoing and sharply increased global forest fires, especially extreme large-scale fires (LFs) with their greater destructiveness, have significantly altered forest structures and functions. However, long-term variations in the severity of LFs and corresponding effects on the natural post-LF recovery time of global forests remain unclear. Here, we rigorously identified 3,281 global large-scale (>10 km2) single-time fire events (LSFs) from 2001 to 2021, and used multiple indicators to understand the post-LSF recovery dynamics from different perspectives and comprehensively reveal major driving factors across regions and forests types based on multiple models. Compared with pre-2010, LSFs after 2010 caused greater forest damage, with the fire severity expanding further from low to high latitudes and from humid to arid regions, particularly affecting evergreen needleleaf forests. Fewer than one-third of the forests recovered successfully within 7 years, and most of these were tropical, moisture-rich broadleaf forests. The average time required for three indicators to recover to pre-fire conditions increased by 7.5% (vegetation density), 11.1% (canopy structure) and 27.3% (gross primary productivity). Moreover, the positive sensitivity of recovery time to increased fire severity was significantly intensified. Notably, more forests experienced recovery stagnation with increased severity, especially in boreal forests, further extending recovery time. The negative impact of the severity of LSFs on forest recovery was much stronger than that of post-LSF climate conditions. Soil moisture after LSFs was identified as the primary facilitating factor. Temperature generally had a positive role before 2010, but a strong negative influence on post-LSF forest recovery after 2010. These findings provide a useful reference for better understanding global forest recovery mechanisms, estimating forest carbon sinks and implementing post-LSF management accordingly.

The heat is on: scaling improvements in photosynthetic thermal tolerance from the leaf to canopy to predict crop yields in a changing climate

Crop production must increase to sustain a growing global population, and this challenge is compounded by increased growing season temperatures and extreme heat events that are already causing significant yield losses in staple crops. Therefore, there is an urgent need to develop strategies to adapt crops to withstand the impacts of a warmer climate. Temperature-sensitive vegetative processes fundamentally related to yield, like photosynthesis, will be impacted by warming throughout the growing season, thus strategies to enhance their resilience hold promise to future-proof crops for a warmer world. Here, we summarize three major strategies to enhance C3 photosynthesis above the thermal optimum: enhanced rubisco activation, modified photorespiration and increased rates of ribulose bisphosphate regeneration. We highlight recent experimental evidence demonstrating the efficacy of these strategies, and then use a mechanistic modelling approach to predict the benefit of these engineering strategies on leaf-level carbon assimilation and soybean yield at elevated temperatures. Our approach highlights that these three engineering targets, particularly when combined, can enhance photosynthetic rates and yield under both ambient and elevated temperatures. By targeting multiple aspects of photosynthetic metabolism, we can develop crops that are better equipped to withstand the challenges of a warming climate and contribute to future food security.This article is part of the theme issue 'Crops under stress: can we mitigate the impacts of climate change on agriculture and launch the 'Resilience Revolution'?'.

Toward Low-Emission Agriculture: Synergistic Contribution of Inorganic Nitrogen and Organic Fertilizers to GHG Emissions and Strategies for Mitigation

Nitrogen (N) and organic-source fertilizers in agriculture are important to sustain crop production for feeding the growing global population. However, their use can result in significant greenhouse gas (GHG) emissions, particularly carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), which are important climate drivers. This review discusses the interactive effects, uncovering both additive and suppressive outcomes of emissions under various soil and climatic conditions. In addition to examining the effects of nitrogen and the nitrogen use efficiency (NUE), it is crucial to comprehend the mechanisms and contributions of organic fertilizers to GHG emissions. This understanding is vital for developing mitigation strategies that effectively reduce emissions while maintaining agricultural productivity. In this review, the current knowledge is utilized for the management of nitrogen practices, such as the optimization of fertilization rates, timing, and methods of application, in terms of the nitrogen use efficiency and the related GHG emissions. Moreover, we discuss the role of organic fertilizers, including straw, manure, and biochar, as a mitigation strategy in relation to GHG emissions through soil carbon sequestration and enhanced nutrient cycling. Important strategies such as crop rotation, tillage, irrigation, organic fertilizers, and legume crops are considered as suitable approaches for minimizing emissions. Even with the progress made in mitigating fertilizer-related emissions, research gaps remain, specifically concerning the long-term effect of organic fertilizers and the interactions between microbial communities in the soil and fertilization practices. Furthermore, the differences in application practices and environmental conditions present considerable obstacles to accurate emission quantification. This review underlines the importance of conducting more thorough research on the combined application of N and organic fertilizers in multiple cropping systems to evolve region-specific mitigation strategies.

Interactive impacts of heat stress and microplastics contamination on the growth and biochemical response of wheat (Triticum aestivum) and maize (Zea mays) plants

The increasing global temperatures, driven largely by anthropogenic activities, pose a significant threat to crops worldwide, with heat stress (HS) emerging as one of the most severe challenges to agricultural productivity. Among the numerous human-induced pressures threatening terrestrial ecosystems globally, microplastics (MPs) represent one of the most persistent and urgent concerns. This study investigated the effects of heat stress (HS) at 35 °C and 40 °C (12 h exposure) on wheat (Triticum aestivum) and maize (Zea mays) grown in soil contaminated with polyethylene microplastics (PE-MPs; 0.01%, 0.1%, and 1% w/w), assessing their physiological and biochemical responses. The results indicated a significant (p < 0.05) reduction in plant height, root length, leaf area, chlorophyll content, and biomass of the selected plants due to MPs application. HS alone and in co-exposure with MPs caused damage to plant tissues as shown by significant (p < 0.05) reactive oxygen species (ROS) production, and lipid peroxidation. Under ROS induction, proline and antioxidant enzymes (CAT, POD, SOD) exhibited significantly (p < 0.05) higher levels in combined stress (HS + MPs) than in individual treatments. In conclusion, wheat exhibited higher levels of H2O2 and MDA stress markers indicating increased oxidative stress compared to maize. In contrast, maize showed elevated levels of proline, CAT, POD, and SOD, suggesting greater resistance to environmental stresses than wheat. Our results provide new understandings of sustainable agriculture practices and hold vast promise in addressing the challenges of HS and MP stresses in agricultural soils.

Emerging contemporary monetary policy issues in Africa: An application of wavelet and quantile techniques to climatic shocks on inflation

Recently, the inflationary impacts of climate change shocks have emerged among key constraints to price and financial stability. In line with this development, some Central banks are incorporating climate change risks in their surveillance activities. Thus, this study examines the asymmetric inflationary impact of climate change shocks on food and general consumer prices in Algeria, Egypt, Nigeria, and South Africa. The study employs a panel quantile via the moment's method and a wavelet coherency analysis for monthly from 2000M01 to 2023M12. The empirical results reveal that, first, there is a dynamic interconnectedness between climate change shocks and inflation. Secondly, the results show that climate change shocks have an inflationary impact on food and general consumer prices. However, the magnitude and direction of the impact depend on the prevailing inflationary regime. Finally, the analysis shows that climate change shocks raise inflation uncertainty. Collectively, these findings imply that climate change shocks are key sources of inflationary pressures and uncertainty, posing significant challenges to central banks' inflation management. One implication of these findings is that central banks in these countries will likely face extreme difficulty stabilising inflation since monetary policy instruments are mainly demand management, and thus may be ineffective in dealing with climate change shocks. In line with the findings, the study recommends that these countries should enhance their inflation surveillance and monetary policy strategies but considering the potential climate change risks.

Modeling effects of climate change on crop phenology and yield of wheat-maize cropping system and exploring sustainable solutions

BACKGROUND

Wheat-maize cropping systems in semi-arid regions are expected to be affected by climate change in the future, which is alarming for global food security, environmental sustainability and socioeconomic development. Therefore, management practices like optimized plant geometry and fertilization need to be explored to counter these expected threats. To do this, the APSIM model was calibrated using 5-year data (from 2017/2018 to 2022) regarding yield, biomass, plant height, emergence, anthesis and crop maturity of wheat and maize from farmer fields.

RESULTS

The performance of a model run was assessed using root mean square error, normalized root mean square error, coefficient of residual mass, coefficient of determination (R2) and Nash-Sutcliffe efficiency, whose average was 1.59, 0.13, 0.001, 0.84 and 0.78, respectively, for calibration while 2.75, 0.20, -0.009, 0.80 and 0.75, respectively, for validation. Regarding crop phenology, it was modelled that the emergence, anthesis and maturity were earlier by 7-9 days, 8-10 days and 2-6 days, respectively, for wheat; 6-10 days, 13-20 days and 16-24 days, respectively, for spring maize; 3-5 days, 5-11 days and 8-19 days, respectively, for autumn maize under different climate change scenarios in near to far future. Simulations revealed the average reduction in the yield of wheat, spring maize and autumn maize by 11.5%, 11.8% and 11.0%, respectively, in near future (2025-2065) while 17.5%, 20.5% and 17.0%, respectively, in far future (2066-2100). Further, simulations discovered the potential of higher levels of fertilization (nitrogen = 60-100 kg ha-1 and phosphorus = 40-75 kg ha-1 for wheat while nitrogen = 75-120 kg ha-1 and phosphorus = 40-80 kg ha-1 for maize) and plant density (100 to 150 plants m-2 for wheat and 8 to 13 plants m-2 for maize) to enhance the yield of wheat, spring maize and autumn maize by 31-36%, 22-38% and 26-43%, respectively, in near future while 33-38%, 21-55% and 19-31%, respectively, in far future.

CONCLUSIONS

The findings underscore the effects of climate change on wheat-maize cropping systems and the importance of implementing optimized fertilization and adjusting plant density to mitigate the adverse effects of climate change, thereby safeguarding food security and sustaining agricultural productivity. © 2025 Society of Chemical Industry.

Molecular mechanisms and breeding strategies for enhancing wheat resilience to environmental stresses: The role of heat shock proteins and implications for food security

Wheat is a major staple crop that plays a pivotal role in global food security. However, its productivity is increasingly compromised by environmental stresses such as heat, drought, salinity and heavy metal toxicity. The broad understanding of molecular mechanisms responsible for wheat resilience is reviewed, with a particular focus on heat shock proteins (HSPs) as key mediators of stress adjustment. HSPs play the role of molecular chaperones, whereby they stabilize proteins and prevent aggregation and oxidative stress to maintain the homeostatic function of cells in the most extreme conditions. We trained omics technologies such as genomics, transcriptomics, proteomics, and metabolomics to identify genes responsive to stress, thus boosting the breeding approach for better resilience in wheat. Now, genome editing tools such as CRISPR/Cas9 have hastened the development of climate-resilient wheat varieties, complementing traditional breeding strategies. Heavy metal toxicity disturbs the metabolic pathways; however, certain metals are micronutrients, and a balanced approach is essential to improve tolerance. Molecular breeding, precision agriculture, and sustainable soil management should be integrated into future studies to mitigate stress impacts and ensure stable yields. Our interdisciplinary approaches will drive sustainable agri-ecosystems for global food security amid climate change and degradation.

The Effect of Sowing Dates on Grain Yield and Quality in Spring Wheat (Triticum aestivum L.)

The impact of sowing dates on wheat (Triticum aestivum L.) quality and yield was investigated comprehensively across two locations during the growing seasons from 2020 to 2022. The study revealed contrasting effects of temperature on grain protein content and glutenin composition. The increase in temperature during the grain-filling period, caused by delayed sowing dates, led to an increase in grain protein content and wet gluten, while concurrently decreasing SDS and Zeleny sedimentation volumes, indicative of reduced gluten strength. This opposing trend underscores the complex relationship between temperature and wheat grain quality, influenced by the synthesis and polymerization of glutenin proteins critical for dough elasticity and baking performance. Furthermore, a negative relationship between ambient temperature and grain yield was observed across locations and years, highlighting the detrimental impact of heat stress on wheat productivity. Early sowing dates, which extended the grain-filling period under cooler conditions, favored higher grain yield and superior gluten quality, characterized by higher SDS and Zeleny values. In contrast, delayed sowing dates, exposing wheat to higher temperatures during grain filling, resulted in increased grain protein content and wet gluten but compromised gluten strength. The findings underscore the importance of optimizing sowing dates and developing heat-resilient wheat varieties to mitigate the adverse effects of climate change on wheat production.

Deep learning based abiotic crop stress assessment for precision agriculture: A comprehensive review

Abiotic stresses are a leading cause of crop loss and a severe peril to global food security. Precise and prompt identification of abiotic stresses in crops is crucial for effective mitigation strategies. In recent years, Deep learning (DL) techniques have demonstrated remarkable promise for high-throughput crop stress phenotyping using remote sensing and field data. This study offers a comprehensive review of the applications of DL models like artificial neural networks (ANN), convolutional neural networks (CNN), recurrent neural networks (RNN), vision transformers (ViT), and other advanced deep learning architectures for abiotic crop stress assessment using different modalities like IoT sensor data, thermal, spectral, RGB with field, UAV and satellite based imagery. The study comprehensively analyses the abiotic stress conditions due to (a) water (b) nutrients (c) salinity (d) temperature and (e) heavy metal. Key contributions in the literature on stress classification, localization, and quantification using deep learning approaches are discussed in detail. The study also covers the principles of deep learning models, and their unique capabilities for handling complex, high-dimensional datasets inherent in abiotic crop stress assessment. The review also highlights important challenges and future directions in deep learning based abiotic crop stress assessment like limited labelled data, model interpretability, and interoperability for robust stress phenotyping. This study critically examines the research pertaining to the abiotic crop stress assessment, and provides a comprehensive view of the role deep learning plays in advancing abiotic crop stress assessment for data-driven precision agriculture.

Yolo-pest: an optimized YoloV8x for detection of small insect pests using smart traps

Fruit flies and fall-armyworm are one of the major insect pest that adversely affect fruit and crops, whereas fall-armyworm is also a highly destructive pest in maize crop but also damage other economically important field crops and vegetables. Adults of both pests can fly, making it hard to monitor them in the field. This study focuses on fine-tuning the YoloV8x model for automated monitoring and identifying insect pests, like fruit flies and fall-armyworms, in open fields and closed environments using IoT-based Smart Traps. The conventional techniques for monitoring of these insect pests involve pheromone attractants and sticky traps that require regular farm visits. We developed an IoT-based device, called Smart Trap, that attracts insect pests with pheromones and captures real-time images using cameras and IoT sensors. Its main objective is automated pest monitoring in fields or indoor grain storage houses. Images captured by smart traps are transmitted to the server, where Yolo-pest, a fine-tuned YoloV8x model with customized hyperparameters performs in real time for object detection. The performance of the smart trap was evaluated in a mango orchard (Fruit Flies) and maize field (fall Armyworm) in an arid climate, achieving a 94% average detection accuracy. The validation process on grayscale and coloured images further confirmed the model's consistent accuracy in identifying insect pests in maze crop and mango orchards. The mobile application also enhances the practical utility as having a user-friendly interface for real time identification of insect pest. Farmers can easily acces the information and data remotely that empowering them for efficient pest maangment.

Rooting for resilience: central metaxylem area as a breeding target for yield gain and resilience in wheat (Triticum aestivum L.)

BACKGROUND

To ensure food security amid unpredictable climatic conditions and depleting natural resources, larger and stable genetic gain have to be realised in wheat. Adapting to these challenges requires focus on both above-ground and below-ground traits. Root anatomy reveals the functional adaptations of the root system. Despite their potential, root anatomical traits remain underutilized but hold promise as breeding targets for developing efficient and resilient crops. Our study aims to identify highly plastic wheat genotypes with superior yield stability and robust root anatomical traits, enabling them to thrive under diverse and challenging environmental conditions. By leveraging advanced multi-trait stability indices and models, we seek to provide breeders with valuable insights for enhancing wheat resilience and productivity.

RESULTS

In this study, 150 wheat genotypes were evaluated across three diverse environments for 10 root anatomical traits along with phenological observation and grain yield. The results show significant positive correlations between root traits, such as axial hydraulic conductance based on the central metaxylem area and total xylem area, with grain yield. This highlights the critical role of these less explored root traits in yield formation. Central metaxylem area was able to explain more than 14 per cent variation in yield over all the three environments. Although the polynomial equation did not significantly improve data fitness, it clearly indicates no sign of yield saturation at the highest CMXA levels. Modern tools like GGE and AMMI though highly effective in reducing the dimensions but do not effectively rank genotypes on the basis of different trait values simultaneously. Advanced models such as BLUP, WAASB, and multi-trait stability indices (MTSI, MGIDI, and FAI-BLUP) have the power to overcome the collinearity in different variables and use the trait values to identify superior genotypes. Genotypes such as G97 and G18 (both being derivative from the cross HDCSW18/CSW1), G112, G144 (both CIMMYT material) and G131 (31ESWYT135/CSW23) consistently exhibited high yield and stability and were picked up by all models. The study demonstrated a moderate coincidence index of 22.72% among these models, confirming the value of selected genotypes. Positive correlations between traits like axial hydraulic conductance and yield highlighted the importance of efficient water transport, nutrient exchange and hydraulic safety of crop.

CONCLUSION

Central metaxylem area based axial hydraulic conductance is explaining more than 14 per cent of variation in the yield across the environment and this along with whole root area and proper phenological adjustment can play key role in yield consolidation with high resilience under more likely uncertain production condition in the future. Three out of five genotypes consistently being picked by different stability models are derivative of HDCSW18, a variety released for conservation agriculture condition and with very strong root system and biomass. High biomass accumulation facilitated by early seeding of the genotypes with mild vernalisation requirement with high root central metaxylem area can sustain higher seed production under challenging climates and thus the findings contribute to strategies for improving wheat resilience.

Utilizing genetic variation in perennial sorghum to improve host plant resistance to aphids

With growing concerns over the sustainability of conventional farming systems, perennial crops offer an environmentally friendly and resilient alternative for long-term agricultural production. Perennial grain crops provide numerous benefits, such as low input investment, reduced tillage, soil conservation, better carbon sequestration, sustainable yields, and enhanced biodiversity support. Sorghum (Sorghum bicolor) is the fifth most-grown cereal crop grown for food, fuel, and food grain in the world. The development of perennial sorghum offers a substitute for traditional annual sorghum crops by providing long-term environmental, economic, and agronomic benefits. Sugarcane aphid (SCA; Melanaphis sacchari), a phloem-feeder, is considered a major threat to sorghum production. Since its first report in 2013, it caused $40.95 million in losses in South Texas alone by 2015, accounting for about 19% of the total value of sorghum production in the region. In this study, we screened diverse perennial sorghum genotypes using no-choice and choice assays to determine their innate antibiosis and antixenosis resistance levels to SCAs. Based on aphid reproduction and plant damage rating, no-choice bioassay classified the 43 perennial sorghum genotypes into four clusters: highly susceptible, moderately susceptible, moderately resistant, and highly resistant. To further investigate the resistance mechanisms, we selected two genotypes, X999 > R485 (SCA-resistant) and PR376 ~ Tift241 (SCA-susceptible) that showed the greatest variation in resistance to SCA, for subsequent experiments. Choice bioassay results indicated that aphids chose PR376 ~ Tift241 for settlement, whereas no significant preference was observed for X999 > R485 compared to the control genotype. Electrical penetration graph (EPG) results demonstrated that aphids feeding on the SCA-resistant genotype spent significantly less time in the phloem phase than the susceptible genotype and control plants. The identification of SCA-resistant perennial sorghum genotypes will be valuable for future sorghum breeding programs in managing this economically important pest.

Climate change adaptation: Challenges for agricultural sustainability

Climate change poses a substantial threat to agricultural sustainability globally. Agriculture is a vital component of the gross domestic production of developing countries. The multifaceted impacts of climate change on agriculture, highlighting how extreme weather events such as water stress, heatwaves, erratic rainfall, storms, floods, and emerging pest infestations are disrupting agricultural productivity. The socioeconomic status of farmers is particularly vulnerable to climatic extremes with future projections indicating significant increment in ambient air temperatures and unpredictable, intense rainfall patterns. Agriculture has historically relied on the extensive use of synthetic fertilizers, herbicides, and insecticides, combined with advancements in irrigation and biotechnological approaches to boost productivity. It encompasses a range of practices designed to enhance the resilience of agricultural systems, improve productivity, and reduce greenhouse gas emissions. By adopting climate-smart practices, farmers can better adapt to changing climatic conditions, thereby ensuring more sustainable and secure food production. Furthermore, it identifies key areas for future research, focusing on the development of innovative adaptation and mitigation strategies. These strategies are essential for minimizing the detrimental impacts of climate change on agriculture and for promoting the long-term sustainability of food systems. This article underscores the importance of interdisciplinary approaches and the integration of advanced technologies to address the challenges posed by climate change. By fostering a deeper understanding of these issues to inform policymakers, researchers, and practitioners about effective strategies to safeguard agricultural productivity and food security in the face of changing climate.

PHOTOPERIOD 1 enhances stress resistance and energy metabolism to promote spike fertility in barley under high ambient temperatures

High ambient temperature (HT) impairs reproductive development and grain yield in temperate crops. To ensure reproductive success under HT, plants must maintain developmental stability. However, the mechanisms integrating plant development and temperature resistance are largely unknown. Here, we demonstrate that PHOTOPERIOD 1 (PPD-H1), homologous to PSEUDO RESPONSE REGULATOR genes of the Arabidopsis (Arabidopsis thaliana) circadian clock, controls developmental stability in response to HT in barley (Hordeum vulgare). We analyzed the HT responses in independent introgression lines with either the ancestral wild-type Ppd-H1 allele or the natural ppd-h1 variant, selected in spring varieties to delay flowering and enhance yield under favorable conditions. HT delayed inflorescence development and reduced grain number in ppd-h1 mutant lines, while the wild-type Ppd-H1 genotypes exhibited accelerated reproductive development and showed a stable grain set under HT. CRISPR/Cas9-mediated genome editing of Ppd-H1 demonstrated that the CONSTANS, CO-like, and TOC1 domain of Ppd-H1 controls developmental stability, but not clock gene expression. Transcriptome and phytohormone analyses in developing leaves and inflorescences revealed increased expression levels of stress-responsive genes and abscisic acid levels in the leaf and inflorescence of the natural and induced mutant ppd-h1 lines. Furthermore, the ppd-h1 lines displayed downregulated photosynthesis- and energy metabolism-related genes, as well as decreased auxin and cytokinin levels in the inflorescence, which impaired anther and pollen development. In contrast, the transcriptome, phytohormone levels, and anther and pollen development remained stable under HT in the wild-type Ppd-H1 plants. Our findings suggest that Ppd-H1 enhances stress resistance and energy metabolism, thereby stabilizing reproductive development, floret fertility, and grain set under HT.

Decoding plant thermosensors: mechanism of temperature perception and stress adaption

Global climate change, characterized by increased frequency and intensity of extreme temperature events, poses significant challenges to plant survival and crop productivity. While considerable research has elucidated plant responses to temperature stress, the molecular mechanisms, particularly those involved in temperature sensing, remain incompletely understood. Thermosensors in plants play a crucial role in translating temperature signals into cellular responses, initiating the downstream signaling cascades that govern adaptive processes. This review highlights recent advances in the identification and classification of plant thermosensors, exploring their physiological roles and the biochemical mechanisms by which they sense temperature changes. We also address the challenges in thermosensor discovery and discuss emerging strategies to uncover novel thermosensory mechanisms, with implications for improving plant resilience to temperature stress in the face of a rapidly changing climate.

Characterization of Different Soil Bacterial Strains and Assessment of Their Impact on the Growth of Triticum turgidum spp. durum and Lens culinaris spp. culinaris

Plant growth-promoting bacteria (PGPB) are vital for enhancing plant growth, productivity, and sustainability in agriculture, also addressing food security challenges. The plant growth-promoting (PGP) potential of ten bacterial strains, isolated from a cultivated field in southern Italy, was characterized with biochemical and molecular analyses and plant growth-promoting activity was tested on two durum wheat varieties (RGT Aventadur and Farah) and a lentil one (Altamura Lentil) under semi-controlled conditions. The isolated strains were classified using 16S rRNA gene sequencing. Results showed that they belonged to Pseudomonaceae, Rhizobiaceae, Bacillaceae and Micrococcaceae families. They exhibited typical features of PGPB, such as inorganic phosphate solubilization, production of indole acetic acid, ammonia, and biofilm formation. Bacterial inoculation of wheat plants led to the identification of potentially interesting strains that positively affected biometric parameters (i.e., shoot height, tiller number and spike weight) in a genotype-dependent way. The contrasting effect of some bacterial strains on the two wheat genotypes supports the necessity to accurately formulate synthetic microbial consortia characterized by long-term PGP traits, taking into account that the application under field conditions might also be influenced by native soil microbiota.

Chemical Seed Priming: Molecules and Mechanisms for Enhancing Plant Germination, Growth, and Stress Tolerance

Food security is one of the world's top challenges, specifically considering global issues like climate change. Seed priming is one strategy to improve crop production, typically via increased germination, yields, and/or stress tolerance. Hydropriming, or soaking seeds in water only, is the simplest form of seed priming. However, the addition of certain seed priming agents has resulted in a variety of modified strategies, including osmopriming, halopriming, hormonal priming, PGR priming, nutripriming, and others. Most current research has focused on hormonal and nutripriming. This review will focus on the specific compounds that have been used most often over the past 3 years and the physiological effects that they have had on crops. Over half of recent research has focused on four compounds: (1) salicylic acid, (2) zinc, (3) gibberellic acid, and (4) potassium nitrate. One of the most interesting characteristics of all chemical seed priming agents is that they are exposed only to seeds yet confer benefits throughout plant development. In some cases, such benefits have been passed to subsequent generations, suggesting an epigenetic effect, which is supported by observed changes in DNA methylation and histone modification. This review will summarize the current state of knowledge on molecular changes and physiological mechanisms associated with chemical seed priming agents and discuss avenues for future research.

Unraveling the genetic basis of heat tolerance and yield in bread wheat: QTN discovery and Its KASP-assisted validation

BACKGROUND

Wheat (Triticum aestivum L.), a globally significant cereal crop and staple food, faces major production challenges due to abiotic stresses such as heat stress (HS), which pose a threat to global food security. To address this, a diverse panel of 126 wheat genotypes, primarily landraces, was evaluated across twelve environments in India, comprising of three locations, two years and two growing conditions. The study aimed to identify genetic markers associated with key agronomic traits in bread wheat, including germination percentage (GERM_PCT), ground cover (GC), days to booting (DTB), days to heading (DTHD), days to flowering (DTFL), days to maturity (DTMT), plant height (PH), grain yield (GYLD), thousand grain weight (TGW), and the normalized difference vegetation index (NDVI) under both timely and late-sown conditions using 35 K SNP genotyping assays. Multi-locus GWAS (ML-GWAS) was employed to detect significant marker-trait associations, and the identified markers were further validated using Kompetitive Allele Specific PCR (KASP).

RESULTS

Six ML-GWAS models were employed for this purpose, leading to the identification of 42 highly significant and consistent quantitative trait nucleotides (QTNs) under both timely and late sown conditions, controlled by 20 SNPs, explaining 3-58% of the total phenotypic variation. Among these, noteworthy QTNs were a major grain yield QTN (qtn_nbpgr_GYLD_3B) on chromosome 3B, a pleiotropic SNP AX-95018072 on chromosome 7A influencing phenology and NDVI, and robust TGW QTNs on chromosomes 2B (qtn_nbpgr_TGW_2B), 1A (qtn_nbpgr_TGW_1A), and 4B (qtn_nbpgr_TGW_4B). Furthermore, annotation revealed that candidate genes near these QTNs encoded stress-responsive proteins, such as chaperonins, glycosyl hydrolases, and signaling molecules. Additionally, three major SNPs AX-95018072 (7A), AX-94946941 (6B), and AX-95232570 (1B) were successfully validated using KASP assay.

CONCLUSION

Our study effectively uncovered novel QTNs and candidate genes linked to heat tolerance and yield-related traits in wheat through an extensive genetic approaches. These QTNs not only corresponded with previously identified QTLs and genes associated with yield traits but also highlighted several new loci, broadening the existing genetic understanding. These findings provide valuable insights into the genetic basis of heat tolerance in wheat and offer genomic resources, including validated markers that could accelerate marker-assisted breeding and the development of next-generation heat-resilient cultivars.

Future of durum wheat research and breeding: Insights from early career researchers

Durum wheat (Triticum turgidum ssp. durum) is globally cultivated for pasta, couscous, and bulgur production. With the changing climate and growing world population, the need to significantly increase durum production to meet the anticipated demand is paramount. This review summarizes recent advancements in durum research, encompassing the exploitation of existing and novel genetic diversity, exploration of potential new diversity sources, breeding for climate-resilient varieties, enhancements in production and management practices, and the utilization of modern technologies in breeding and cultivar development. In comparison to bread wheat (T. aestivum), the durum wheat community and production area are considerably smaller, often comprising many small-family farmers, notably in African and Asian countries. Public breeding programs such as the International Maize and Wheat Improvement Center (CIMMYT) and the International Center for Agricultural Research in the Dry Areas (ICARDA) play a pivotal role in providing new and adapted cultivars for these small-scale growers. We spotlight the contributions of these and others in this review. Additionally, we offer our recommendations on key areas for the durum research community to explore in addressing the challenges posed by climate change while striving to enhance durum production and sustainability. As part of the Wheat Initiative, the Expert Working Group on Durum Wheat Genomics and Breeding recognizes the significance of collaborative efforts in advancing toward a shared objective. We hope the insights presented in this review stimulate future research and deliberations on the trajectory for durum wheat genomics and breeding.

Limited improvement of crop nitrogen management sustainability through optimal crop distributions in drylands

Efficient nitrogen (N) management is essential for sustainable global food production. Although optimal crop distributions are recognized as potential adaptive strategies to offset the adverse effects of climate change, their effectiveness in improving regional crop N management sustainability is still uncertain. Here, we quantified spatiotemporal trends of the sustainable N management index (SNMI) for optimal crop distributions (determined by maximum crop suitability per grid) in the Hexi Corridor drylands in Northwest China since the 1960s, using crop yields and N use efficiency (NUE) simulated by a process-based regional crop model (pDSSAT). We also reduced the uncertainties of model parameters and climate scenarios in yield simulations through field water-nitrogen experiments for six crops (maize, wheat, potato, rapeseed, cotton, and alfalfa) and emergent-constraint approach, respectively. Analysis of SNMI shows an upward trend over the past 60 years, but future 20 years find a significant decline. Our findings indicate a 4-29% reduction in uncertainty using constrained crop yields versus regional average yields, which improve the sustainability of crop N management in optimal crop distributions with a lower SNMI. Future climate scenarios would further intensify crop yield loss, but optimal crop distributions will decline regional crop yield by 2%, increase NUE by 10%, and decrease SNMI by 13% compared to the 2011-2020. These results demonstrate a limited improvement of optimal crop distributions on historical SNMI, whereas their effectiveness is supported in future climate conditions-a result of a noticeable enhancement in NUE that compensates the detrimental impacts of yield reduction. Therefore, we recommend revisiting more adaptive strategies alongside optimal crop distributions for consistently improve the sustainability of crop N management.

Impact of heat stress on the development, physiological and biochemical characteristics of Tartary buckwheat flowers, and its transcriptomic analysis

Tartary buckwheat (Fagopyrum tataricum), a functional grain known for its medicinal and nutritional properties, has garnered significant attention due to its high flavonoid content and unique health benefits. Heat stress during the flowering stage can lead to sterility in Tartary buckwheat, resulting in reduced yields. This study investigates the effects of a treatment (30/27 °C for 7 days) on flower development, fertility, stress physiology, and gene expression in Tartary buckwheat, while also validating the efficacy of hormone treatments in alleviating the negative effects of heat stress. The results show that fertilization in Tartary buckwheat typically occurs within 3-5 days post-anthesis. By the 5th day, the stamen length in the heat-treated group was reduced by 13.89% compared to the control, while pistil length increased by 35.44%. Heat stress delayed the pistil stigma's transition into its highly receptive phase and caused a significant reduction in pollen viability by 15.25% after 5 days of treatment. Furthermore, after 7 days of treatment, the levels of H2O2 and O2- increased by 44.9% and 37.2%, respectively. However, Tartary buckwheat mitigated the impact of oxidative damage by enhancing the enzymatic activity of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT). Transcriptome analysis revealed that heat stress significantly suppressed the expression of genes in hormone signaling pathways, such as indole-3-acetic acid (IAA), gibberellin (GA), and jasmonic acid (JA). Under heat treatment conditions, exogenous hormone application significantly regulated the dynamics of flower development. Specifically, after 3 days of heat treatment, all hormone treatments significantly inhibited the abnormal elongation of stamens, with GA notably suppressing the abnormal elongation of pistils. After 5 days, GA significantly promoted stamen elongation, while IAA and jasmonic acid (JA) significantly inhibited the abnormal elongation of pistils. After 7 days, all three hormone treatments significantly promoted stamen elongation and effectively inhibited abnormal pistil growth. These results suggest that under heat stress conditions, GA plays a key role in promoting stamen elongation, while IAA and JA inhibit the abnormal elongation of the pistil. Prolonged high temperatures can impair the function of floral organs, while JA treatment on the seventh day of heat treatment effectively restored pistil receptivity and significantly improved pollen vitality. In summary, this study provides in-depth insights into the mechanisms by which heat stress affects flower development in Tartary buckwheat, offering theoretical foundations and practical guidance for reducing the impact of heat stress on buckwheat yield.

Innovative modeling on the effects of low-temperature stress on rice yields

The increasing frequency and intensity of low-temperature events in temperate and cold rice production regions threatens rice yields under climate change. While process-based crop models can project climate impacts on rice yield, their accuracy under low-temperature conditions has not been well evaluated. Our 6 year chamber experiments revealed that low temperatures reduce spikelet fertility from panicle initiation to flowering, grain number per spike during panicle development, and grain weight during grain filling. We examined the algorithms of spikelet fertility response to temperature used in crop models. The results showed that simulation performance is poor for crop yields if the same function was used at different growth stages outside the booting stage. Indeed, we replaced the algorithm for the spikelet fertility parameter of the ORYZA model and developed the function of estimated grain number per spike and grain weight. After that, the algorithm with improved equations was applied to 10 rice growth models. New functions considered the harmful effects of low temperatures on rice yield at different stages. In addition, the threshold temperatures of cold tolerance were set for different rice varieties. The improved algorithm enhances the ability of the models to simulate rice yields under climate change, providing a more reliable tool for adapting rice production to future climatic challenges.

Plant Productivity and Leaf Starch During Grain Fill Is Linked to QTL Containing Flowering Locus T1 (FT1) in Wheat (Triticum aestivum L.)

Shifts in the environment due to climate change necessitate breeding efforts aimed at adapting wheat to longer, warmer growing seasons. In this study, 21 modern wheat (Triticum aestivum L.) cultivars and 29 landraces were screened for flag leaf starch levels, with the goal of identifying a genetic marker for targeted breeding. The landrace PI 61693 was identified as having exceptionally high flag leaf starch values. Yield trials were carried out in a Berkut × PI 61693 recombinant inbred line (RIL) population and a negative correlation was observed between leaf starch, flowering time, and yield. Genetic mapping identified a Quantitative Trait Loci (QTL) explaining 22-34% variation for leaf starch, flowering time, biomass, and seed yield. The starch synthase TraesCS7D02G117800 (wSsI-1) is located in this region, which possibly accounts for leaf starch variation in this population; also within this QTL is TraesCS7D02G111600 (FT-D1). Sequencing of FT-D1 identified a single base pair deletion in the 3rd exon of the Berkut allele. This indel has recently been shown to significantly impact flowering time and productivity, and likely led to significant variation in flowering date and yield in this population. Here, we illustrate how allelic selection of FT-D1 within breeding programs may aid in adapting wheat to changing environments.

Interactions Between Climate Mean and Variability Drive Future Agroecosystem Vulnerability

Agriculture is crucial for global food supply and dominates the Earth's land surface. It is unknown, however, how slow but relentless changes in climate mean state, versus random extreme conditions arising from changing variability, will affect agroecosystems' carbon fluxes, energy fluxes, and crop production. We used an advanced weather generator to partition changes in mean climate state versus variability for both temperature and precipitation, producing forcing data to drive factorial-design simulations of US Midwest agricultural regions in the Energy Exascale Earth System Model. We found that an increase in temperature mean lowers stored carbon, plant productivity, and crop yield, and tends to convert agroecosystems from a carbon sink to a source, as expected; it also can cause local to regional cooling in the earth system model through its effects on the Bowen Ratio. The combined effect of mean and variability changes on carbon fluxes and pools was nonlinear, that is, greater than each individual case. For instance, gross primary production reduces by 9%, 1%, and 13% due to change in mean temperature, change in temperature variability, and change in both temperature mean and variability, respectively. Overall, the scenario with change in both temperature and precipitation means leads to the largest reduction in carbon fluxes (-16% gross primary production), carbon pools (-35% vegetation carbon), and crop yields (-33% and -22% median reduction in yield for corn and soybean, respectively). By unambiguously parsing the effects of changing climate mean versus variability and quantifying their nonadditive impacts, this study lays a foundation for more robust understanding and prediction of agroecosystems' vulnerability to 21st-century climate change.

Elevated CO2 Concentration Extends Reproductive Growth Period and Enhances Carbon Metabolism in Wheat Exposed to Increased Temperature

Both elevated atmospheric CO2 concentration ([CO2]) and increased temperature exert notable influences on wheat (Triticum aestivum L.) growth and productivity when examined individually. Nevertheless, limited research comprehensively investigates the combined effects of both factors. Winter wheat was grown in environment-controlled chambers under two concentrations of CO2 (ambient CO2 concentration and ambient CO2 concentration plus 200 µmol mol-1) and two levels of temperature (ambient temperature and ambient temperature plus 2°C). The phenology, photosynthesis, carbohydrate and nitrogen metabolism, yield and quality responses of wheat were investigated. Elevated [CO2] did not counteract warming-induced shortening of wheat phenological period but prolonged grain filling. Even though photosynthetic adaptation occurred during the reproductive growth period, elevated [CO2] still significantly enhanced carbohydrate accumulation under warming, particularly at the grain filling stage, thereby increasing yield by 20.1% compared with the ambient control. However, elevated [CO2] inhibited nitrogen assimilation at the grain filling stage under increased temperature by downregulating the expression levels of TaNR, TaNIR, TaGS1 and TaGOGAT and reducing glutamine synthetase activity, which directly led to a significant decrease of 19.4% in grain protein content relative to the ambient control. These findings suggest that elevated [CO2] will likely increase yield but decrease grain nutritional quality for wheat under future global warming scenarios.

Dual stress, equivalent harm? hypothesizing on the type of interactions between waterlogging and high temperature

Episodes of extreme weather, such as high temperatures and heavy rains causing waterlogging, have been becoming more frequent due to climate change, posing risks to crops and reducing growth and yield. While the impact of these stresses has been individually studied, there is a significant gap in understanding their combined effects within the same growing season. There were only 15 studies in the rigorous literature addressing the combined impact of high temperatures and waterlogging. None explicitly examined whether these combined effects were additive (penalties close to the sum of the individual penalties), synergistic (more severe penalties), or antagonistic (less severe penalties). We aimed to propose a sound hypothesis on the most likely type of interaction between these two stressors. Reviewing the scarce literature we found, against expectations, that antagonistic interactions were most common, followed by cases of additive effects, with synergistic interactions being rare. Notably, while the primary concern of virtually all studies was the impact on crop yield, most of them focused exclusively on leaf-level traits, whose responses did not correlate well with yield responses. This preliminary analysis provides solid roots for hypothesizing that waterlogging and high temperatures interact antagonistically; i.e., that plants might develop some resilience when exposed to one stress, potentially reducing the impact of the other. Should this hypothesis be accepted, considering not only physiological traits but also, and mainly, yield in major crops, there would be a less pessimistic view on the expected outcome of the increased frequency of crops being exposed to combined high temperature and waterlogging.

The Genetics and Breeding of Heat Stress Tolerance in Wheat: Advances and Prospects

Heat stress is one of the major concerns for wheat production worldwide. Morphological parameters such as germination, leaf area, shoot, and root growth are affected by heat stress, with affected physiological parameters including photosynthesis, respiration, and water relation. Heat stress also leads to the generation of reactive oxygen species that disrupt the membrane systems of thylakoids, chloroplasts, and the plasma membrane. The deactivation of the photosystems, reduction in photosynthesis, and inactivation of Rubisco affect the production of photo-assimilates and their allocation, consequently resulting in reduced grain yield and quality. The development of thermo-tolerant wheat varieties is the most efficient and fundamental approach for coping with global warming. This review provides a comprehensive overview of various aspects related to heat stress tolerance in wheat, including damages caused by heat stress, mechanisms of heat stress tolerance, genes or QTLs regulating heat stress tolerance, and the methodologies of breeding wheat cultivars with high heat stress tolerance. Such insights are essential for developing thermo-tolerant wheat cultivars with high yield potential in response to an increasingly warmer environment.

Effects of future climate and land use changes on runoff in tropical regions of China

Climate change and human activities are the primary drivers influencing changes in runoff dynamics. However, current understanding of future hydrological processes under scenarios of gradual climate change and escalating human activities remains uncertain, particularly in tropical regions affected by deforestation. Based on this, we employed the SWAT model coupled with the near future (2021-2040) and middle future (2041-2060) global climate models (GCMs) under four shared socioeconomic pathways (SSP1-2.6 (SSP1 + RCP2.6), SSP2-4.5 (SSP2 + RCP4.5), SSP3-7.0 (SSP3 + RCP7.0), and SSP5-8.5 (SSP5 + RCP8.5)) from the CMIP6 and the CA-Markov model to evaluate the runoff response to future environmental changes in the Dingan River Basin (DRB). The quantification of the impacts of climate change and land use change on future runoff changes was conducted. The results revealed a non-significant increasing trend in precipitation during the historical period (1999-2018). Furthermore, all three future scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5) exhibited an upward trend in precipitation from 2021 to 2060. Notably, the SSP5-8.5 scenario demonstrated a highly significant increase (P < 0.01), while the SSP2-4.5 scenario displayed a non-significant decreasing trend. The future precipitation pattern exhibits a decrease during spring and winter, while showing an increase in summer and autumn. The temperature exhibited a significant increase (P < 0.05) across the four future scenarios, with amplitudes of 0.24 °C/(10 years), 0.36 °C/(10 years), 0.36 °C/(10 years), and 0.50 °C/(10 years) for SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 respectively. The future trend of land use change entails a continuous increase in cultivated land and a corresponding decrease in artificial forest land. By 2032, the area of cultivated land is projected to witness a growth of 4.10%, while artificial forest coverage will experience a decline of 4.45%. Furthermore, by 2046, the extent of cultivated land is anticipated to expand by 4.41%, accompanied by a reduction in artificial forest cover amounting to 5.39%. The average annual runoff during the historical period was 53.35 m³/s, and the Mann-Kendall (MK) trend test showed that it exhibited a non-significant increasing trend. Compared with the historical period, the comprehensive impact of climate change and land use will cause changes in the runoff by 0.49%, 1.98%, - 3.13%, and 3.65% for the scenarios of SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 in the near future, and - 3.24%, 1.30%, - 3.75% and 18.24% in the middle future respectively. The intra-annual variations in future runoff suggest an earlier peak and a more concentrated distribution of runoff during the wet season (May to October). Compared to historical periods, the total runoff in the wet season under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios increased by 6.53%, 8.91%, 7.17%, and 7.39%, respectively. The research findings offer significant insights into the future hydrological processes in tropical regions, while also serving as a valuable reference for watershed water resource management and disaster control.

Mapping heat tolerance QTLs in Triticum durum-Aegilops speltoides backcross introgression lines to enhance thermotolerance in wheat

Wheat, a major cereal crop, is the most consumed staple food after rice in India. Frequent episodes of heat waves during the past decade have raised concerns about food security under impending global warming and necessitate the development of heat-tolerant wheat cultivars. Wild relatives of crop plants serve as untapped reservoirs of novel genetic variations. In the present study a mapping population comprising 311 BC2F10 backcross introgression lines (BILs) developed by crossing Triticum durum and heat-tolerant diploid wild wheat relative Aegilops speltoides accession pau3809 was used to map QTLs for terminal heat tolerance. The homozygous BILs were evaluated for heat stress tolerance component traits under an optimum environment (OE) and a heat-stressed environment (HE) for the two cropping seasons. Data on spike length, spikelet number per spike, peduncle length, thousand-grain weight, grains per spike, days to heading, days to maturity, grain filling duration, NDVI at heading, plant height and plot yield were recorded. Genotyping-by-sequencing (GBS) of the BILs was carried out, and 2945 high-quality, polymorphic SNPs were obtained. Thirty QTLs were detected for various heat tolerance component traits on chromosomes 1A, IB, 2A, 2B, 3B, 4B, 5A, 5B, 6A and 6B with phenotypic variance ranging from 5 to 11.5%. Several candidate genes reported to play a role in heat stress responses were identified by browsing the 1.85 Mb physical region flanking the stable QTLs detected under the HE. Identified QTL and linked markers can be employed for genomics-assisted breeding for heat tolerance in wheat.

A bitter cup of coffee? Assessing the impact of climate change on Arabica coffee production in Brazil

Brazil, the world's largest producer and exporter of Arabica coffee, faces increasing challenges from climate changes. To maintain the sustainability of this commodity, innovative management techniques will be essential. This study aimed to assess the impact of climate projections, considering two CMIP6 emission scenarios (SSP2-4.5 and SSP5-8.5) on the phenology and yield of Arabica coffee in 36 representative locations across Brazil for the periods 2041-2060, 2061-2080, and 2081-2100. Observed meteorological data from the BR-DWGD (Brazilian Daily Weather Gridded Data) and projected data from CLIMBra (Climate Change Dataset for Brazil) were employed. An agrometeorological model, calibrated for Brazilian conditions, estimated yield and phenology. Results indicate significant impacts on coffee cultivation areas, mainly due to rising temperatures and increased water deficits. Projections also suggest changes in coffee phenology, with anthesis advancing in colder regions and delaying in warmer areas, while maturation timing occurring earlier in all climates. Yield increases from CO₂ fertilization were more pronounced in category C climates (Cfa, Cfb, Cwa, and Cwb), particularly in Cwb climates, reaching 2.9 bags ha-1 (3.7 bags ha-1 with irrigation) under the SSP2-4.5 scenario and 2.5 bags ha-1 (3.5 bags ha-1 with irrigation) under SSP5-8.5. However, higher temperatures and water deficits could cause severe yield losses, especially in Aw climates and under high-emission scenarios, where losses may reach 100 %. Irrigation will play an important role in mitigating yield losses, especially in northern regions such as northern Minas Gerais and Bahia, where yields could exceed 30 bags ha-1. While southern Minas Gerais, São Paulo, and northern Paraná are projected to have the highest yields, these regions also face greater uncertainty and variability. This study underscores the need for adaptive agricultural practices, the development of resilient coffee cultivars, and supportive research policies to ensure the sustainability of coffee farming in the face of climate change.

Inoculation with Micromonospora sp. enhances carbohydrate and amino acid production, strengthening antioxidant metabolism to mitigate heat stress in wheat cultivars

Introduction

Heat stress caused by global warming adversely affects wheat yield through declining most nutritional quality attributes in grains, excluding grain protein content.

Methods

This research investigated the biochemical, physiological, and antioxidant responses of wheat plants under heat stress, focusing on the role of plant growth-promoting bacteria (Micromonospora sp.). Two wheat genotypes were studied: one heat-sensitive and one heat-tolerant, examining their responses to heat stress with and without bacterial inoculation.

Results

Under heat stress, the sensitive cultivar experienced significant reductions in photosynthesis rate, chlorophyll content, and RuBisCO activity (57-61%), while the tolerant cultivar had milder reductions (24-28%). Micromonospora sp. treatment notably improved these parameters in the sensitive cultivar (+48-78%), resulting in a substantial increase in biomass production (+43-53%), which was not seen in the tolerant cultivar. Additionally, oxidative stress markers (H2O2 and MDA) were elevated more in the sensitive cultivar (82% and 90% higher) compared to the tolerant one. Micromonospora sp. treatment effectively reduced these markers in the sensitive cultivar (-28% and -27%). Enhanced activity of antioxidant enzymes and ASC-GSH pathway enzymes was particularly evident in Micromonospora sp.-treated sensitive plants. Carbohydrate metabolism shifted, with increased soluble sugars and significant rises in sucrose content in Micromonospora sp.-treated plants under stress.

Discussion

The higher soluble sugar levels facilitated amino acid synthesis, contributing to biosynthesis of secondary metabolites, including flavonoids, polyphenols, and anthocyanins. This was reflected in increased activity of phenylalanine ammonia-lyase, cinnamate (CA) 4-hydroxylase, and chalcone synthase enzymes, indicating the activation of phenylpropanoid pathways. Overall, the findings suggest that Micromonospora sp. can mitigate heat stress effects by enhancing photosynthetic efficiency, antioxidant defense, and metabolic adaptations in heat-sensitive wheat cultivars.

Temporal resolution trumps spectral resolution in UAV-based monitoring of cereal senescence dynamics

BACKGROUND

Senescence is a complex developmental process that is regulated by a multitude of environmental, genetic, and physiological factors. Optimizing the timing and dynamics of this process has the potential to significantly impact crop adaptation to future climates and for maintaining grain yield and quality, particularly under terminal stress. Accurately capturing the dynamics of senescence and isolating the genetic variance component requires frequent assessment as well as intense field testing. Here, we evaluated and compared the potential of temporally dense drone-based RGB- and multispectral image sequences for this purpose. Regular measurements were made throughout the grain filling phase for more than 600 winter wheat genotypes across three experiments in a high-yielding environment of temperate Europe. At the plot level, multispectral and RGB indices were extracted, and time series were modelled using different parametric and semi-parametric models. The capability of these approaches to track senescence was evaluated based on estimated model parameters, with corresponding parameters derived from repeated visual scorings as a reference. This approach represents the need for remote-sensing based proxies that capture the entire process, from the onset to the conclusion of senescence, as well as the rate of the progression.

RESULTS

Our results indicated the efficacy of both RGB and multispectral reflectance indices in monitoring senescence dynamics and accurately identifying key temporal parameters characterizing this phase, comparable to more sophisticated proximal sensing techniques that offer limited throughput. Correlation coefficients of up to 0.8 were observed between multispectral (NDVIred668-index) and visual scoring, respectively 0.9 between RGB (ExGR-index) and visual scoring. Sub-sampling of measurement events demonstrated that the timing and frequency of measurements were highly influential, arguably even more than the choice of sensor.

CONCLUSIONS

Remote-sensing based proxies derived from both RGB and multispectral sensors can capture the senescence process accurately. The sub-sampling emphasized the importance of timely and frequent assessments, but also highlighted the need for robust methods that enable such frequent assessments to be made under variable environmental conditions. The proposed measurement and data processing strategies can improve the measurement and understanding of senescence dynamics, facilitating adaptive crop breeding strategies in the context of climate change.

Transcriptomic Analysis of the CAM Species Kalanchoë fedtschenkoi Under Low- and High-Temperature Regimes

Temperature stress is one of the major limiting environmental factors that negatively impact global crop yields. Kalanchoë fedtschenkoi is an obligate crassulacean acid metabolism (CAM) plant species, exhibiting much higher water-use efficiency and tolerance to drought and heat stresses than C3 or C4 plant species. Previous studies on gene expression responses to low- or high-temperature stress have been focused on C3 and C4 plants. There is a lack of information about the regulation of gene expression by low and high temperatures in CAM plants. To address this knowledge gap, we performed transcriptome sequencing (RNA-Seq) of leaf and root tissues of K. fedtschenkoi under cold (8 °C), normal (25 °C), and heat (37 °C) conditions at dawn (i.e., 2 h before the light period) and dusk (i.e., 2 h before the dark period). Our analysis revealed differentially expressed genes (DEGs) under cold or heat treatment in comparison to normal conditions in leaf or root tissue at each of the two time points. In particular, DEGs exhibiting either the same or opposite direction of expression change (either up-regulated or down-regulated) under cold and heat treatments were identified. In addition, we analyzed gene co-expression modules regulated by cold or heat treatment, and we performed in-depth analyses of expression regulation by temperature stresses for selected gene categories, including CAM-related genes, genes encoding heat shock factors and heat shock proteins, circadian rhythm genes, and stomatal movement genes. Our study highlights both the common and distinct molecular strategies employed by CAM and C3/C4 plants in adapting to extreme temperatures, providing new insights into the molecular mechanisms underlying temperature stress responses in CAM species.

The contribution of beneficial wheat seed fungal communities beyond disease-causing fungi: Advancing heritable mycobiome-based plant breeding

Wheat (Triticum sp.) is a staple cereal crop, providing nearly a fifth of the world's protein and available calories. While fungi associated with wheat plants have been known for centuries, attention to fungi associated with wheat seeds has increased over the last hundred years. Initially, research focused on fungal taxa that cause seed-borne diseases. Seeds act as a physical link between generations and host specialized fungal communities that affect seed dormancy, germination, quality, and disease susceptibility. Interest in beneficial, non-disease-causing fungal taxa associated with seeds has grown since the discovery of Epichloë in fescue, leading to a search for beneficial fungal endophytes in cereal grains. Recent studies of the wheat seed mycobiome have shown that disease, seed development, and temporal variation significantly influence the composition and structure of these fungal communities. This research, primarily descriptive, aims to better understand the wheat seed mycobiome's function in relation to the plant host. A deeper understanding of the wheat seed mycobiome's functionality may offer potential for microbiome-assisted breeding.

Uneven changes in air and crown temperatures associated with snowpack changes affect the phenology of overwintering cereals

Time series analysis of overwintering cereals in snowy areas has revealed several phenological patterns associated with climate changes in winter. Herein, to investigate the recent effect of climatic variations on overwintering cereals, we investigated the phenology over multiple decades at three snowy region sites with an air temperature (Tair) increase trend of 0.48-1.09 °C/decade. Our findings were as follows: heading trends differed within the same cultivar at different sites; phenology was promoted with increasing temperatures in cooler regions and decreasing snow duration in regions with heavy snow; crown temperature (Tcrown) was a more direct determinant than Tair in phenology estimation model in regions with heavy snow. A thermal gap of more than a few degrees Celsius between Tair and Tcrown, owing to the insulation effect of snowpack, affected the phenology of overwintering cereals. A shorter snow cover period promoted phenology in locations with temperatures >0 °C. Subsequently, we found that when the thermal gap was >0 °C of the growing temperature range, Tcrown directly helped determine the phenology of overwintering cereals, and irrespective of the warming trend, the periodic inflow of cold air into the northern mid-latitudes of the Northern Hemisphere and associated snow cover changes dominated Tcrown, resulting in annual phenological anomalies with a range of fluctuations of approximately 1 month. The trend of increasing Tair during spring in northern Japan is consistent with the global trend, with a pronounced trend of advancing phenology reaching >4 days/decade in a typical cooler location experiencing snowmelt in March.

Identification of key chlorophyll fluorescence parameters as biomarkers for dryland wheat under future climate conditions

Nowadays, climate change is the primary factor shaping the future of food and nutritional security. To investigate the interactive effects of various climate variables on photosynthetic efficiency, an experiment was conducted using 10 dryland wheat genotypes. These genotypes were exposed to different conditions: temperatures of 25 ± 3 °C and 34 ± 3 °C, carbon dioxide concentrations of 380 ± 50 ppm and 800 ± 50 ppm, and irrigation regimes of 50% field capacity and well-watered. Our results indicated that the wheat genotypes responded differently to both individual and combined climate stress factors. The traditional winter wheat genotype *Sardari*, along with the newly developed dryland wheat genotype *Ivan*, exhibited resilience to anticipated climate conditions. This resilience was reflected in enhancements in photochemical quantum efficiency parameters (Y(II), qP, and qL) under combined stress conditions. Resilient genotypes demonstrated superior regulation of the stomatal conductance (GS) and electron transport rate (ETR) under elevated temperature and CO2 levels. Principal component analysis (PCA) revealed significant correlations between chlorophyll fluorescence parameters and climate factors, such as NPQ with temperature, Y(NO) with CO2, qL in response to drought stress, and both qP and Y(II) with the interactions among temperature, CO2, and drought stress. Elevated CO2 reduced the ETR and GS across all genotypes. Our findings underscore the importance of assessing not only fundamental chlorophyll fluorescence parameters like Fm and Fo but also the efficiency of NPQ and Y(II) to understand climate change impacts on dryland wheat genotypes. We suggest that these parameters could serve as valuable biomarkers for breeding programs aimed at improving plant adaptation to future dryland climate conditions.

Comparative analysis of IRE1s in plants: insights into heat stress adaptation in Triticum aestivum

BACKGROUND

The unfolded protein response (UPR) pathway serves as a crucial mechanism enabling plants to perceive, respond to, and shield themselves from adverse environmental conditions. Inositol-requiring enzyme 1 (IRE1) is one of the key players of the UPR, and resides in the endoplasmic reticulum (ER) within the cell. This study provides a comprehensive analysis of 195 IRE1 genes across 90 diverse plant species, with a focus on their identification and characterization.

RESULTS

To decipher the functions of IRE1 family members, we investigated the evolution and spread of IREs in plants and analysed their structural and localization characteristics. Our detailed cis-element analysis revealed unique IRE1 regulation patterns in different plant species. Furthermore, gene expression analysis revealed tissue-specific and heat stress-responsive expression patterns of TaIRE1s, which were subsequently confirmed via quantitative gene expression analysis. TaIRE1-6A was upregulated in response to dithiothreitol (DTT) treatment as well as heat stress. This finding suggests that IRE1 might play a role in linking the UPR pathway and the heat stress response (HSR).

CONCLUSIONS

Our findings provide a comprehensive understanding of the evolution and expansion of IRE1 genes in different plant species. These findings provide a foundation for further in-depth research on the functional diversity of IREs in nutritious crops following polyploidization. By linking the UPR with HSR, IRE1 could be a key contributor to wheat's resilience against heat stress. Additionally, this connection offers important insights for future functional studies in other crops. Thus, this knowledge could be used for engineering climate resilience in crops such as wheat.

Predicting rice phenology across China by integrating crop phenology model and machine learning

This study explores the integration of crop phenology models and machine learning approaches for predicting rice phenology across China, to gain a deeper understanding of rice phenology prediction. Multiple approaches were used to predict heading and maturity dates at 337 locations across the main rice growing regions of China from 1981 to 2020, including crop phenology model, machine learning and hybrid model that integrate both approaches. Furthermore, an interpretable machine learning (IML) using SHapley Additive exPlanation (SHAP) was employed to elucidate influence of climatic and varietal factors on uncertainty in crop phenology model predictions. Overall, the hybrid model demonstrated a high accuracy in predicting rice phenology, followed by machine learning and crop phenology models. The best hybrid model, based on a serial structure and the eXtreme Gradient Boosting (XGBoost) algorithm, achieved a root mean square error (RMSE) of 4.65 and 5.72 days and coefficient of determination (R2) values of 0.93 and 0.9 for heading and maturity predictions, respectively. SHAP analysis revealed temperature to be the most influential climate variable affecting phenology predictions, particularly under extreme temperature conditions, while rainfall and solar radiation were found to be less influential. The analysis also highlighted the variable importance of climate across different phenological stages, rice cultivation patterns, and geographic regions, underscoring the notable regionality. The study proposed that a hybrid model using an IML approach would not only improve the accuracy of prediction but also offer a robust framework for leveraging data-driven in crop modeling, providing a valuable tool for refining and advancing the modeling process in rice.

Effects of Temperature, Precipitation, and Sunshine on Cold-Tolerant Wheat Yield Under Warming Trends: A 20-Year Study in Hokkaido, Japan

To clarify the adaptation strategies of cold-tolerant wheat against global warming, this study examined the effects of daily temperature, precipitation, and sunshine duration on wheat yield in Hokkaido, Japan, over 13 years (2011-2023). Yield components were also analyzed over 20 years (2004-2023). The number of snow-cover days decreased by about 24 days over the 20-year period. As a result, the growth of overwintered wheat accelerated, with the heading and maturity of plants advancing by about 8 and 5 days, respectively, and the grain-filling period extending from about 44 to about 48 days. Multiple regression analysis was conducted using wheat yield as the objective variable and weather conditions as explanatory variables. Three weather conditions were selected: precipitation for 8 days from 27 March, sunshine hours for 8 days from 21 March, and sunshine hours for 12 days from 13 June, which yielded a coefficient of determination of 0.953. Despite the highest mean summer temperatures on record being registered in 2023, high yields were ensured by the number of sunshine hours, which were approximately 1.5 times the normally recorded hours. This highlights the importance of this parameter in mitigating the impact of high summer temperatures.

Seed market dynamics and diffusion of new wheat varieties in Bihar, India: a supply-side perspective

An examination of the dynamics of seed markets in Bihar, India, reveals a paradox-despite an influx of wheat varieties bred by public and private sectors and the proliferation of seed market networks in rural villages, older wheat varieties remain prevalent-necessitating a thorough investigation of the seed distribution system. Unlike most empirical studies that examine the adoption of new and improved crop varieties from a farmer's perspective, our study shifts the focus to the seed supply side. We analyse data collected from 200 private seed dealers who cater to the needs of over 163,000 farmers spread across 10 districts in Bihar. We use descriptive statistics alongside dealer-level and varietal-level regression models to examine the relationship between seed sales and varietal age. Findings indicate that the number of varieties available with a dealer (varietal richness) is positively associated with the number of seed buyers (dealer's reach) and the total quantity of seeds sold. Private varieties are in demand despite their higher prices. Dealer-level models showed that varietal age affects neither the reach nor the sales, allowing older public-sector varieties to coexist with more recent private-sector ones. However, the varietal-level regression models show that dealers rank the new varieties higher as the ones being sold more. To explore the potential of private seed markets to reduce the proliferation of old wheat varieties that are more susceptible to evolving biotic and abiotic stress factors, we recommend strengthening the varietal registration and seed certification processes, implementing better seed traceability systems, and fostering public-private partnerships in variety development and seed dissemination. Investing in market experiments to incentivize seed dealers to engage in quality assurance can help refine strategies and ensure efficient and inclusive dissemination of promising wheat varieties.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40100-024-00330-w.

Impacts of future climate change on rice yield based on crop model simulation-A meta-analysis

Rice is one of the world's major food crops. Changes in major climatic factors such as temperature, rainfall, solar radiation and carbon dioxide (CO2) concentration have an important impact on rice growth and yield. However, many of the current studies that predict the impact of future climate change on rice yield are affected by uncertainties such as climate models, climate scenarios, model parameters and structure, and showing great differences. This study was based on the assessment results of the impact of climate change on rice in the future of 111 published literature, and comprehensively analyzed the impact and uncertainty of climate change on rice yield. This study utilized local polynomial (Loess) regression analysis to investigate the impact of changes in mean temperature, minimum temperature, maximum temperature, solar radiation, and precipitation on relative rice yield variations within a complete dataset. A linear mixed-effects model was used to quantitatively analyze the relationships between the restricted datasets. The qualitative analysis based on the entire dataset revealed that rice yields decreased with increasing average temperature. The precipitation changed between 0 and 25 %, it was conducive to the stable production of rice, and when the precipitation changed >25 %, it would cause rice yield reduction. The change of solar radiation was less than -1.15 %, the rice yield increases with the increase of solar radiation, and when the change of solar radiation exceeds -1.15 %, the rice yield decreases. Elevated CO2 concentrations and management practices could mitigate the negative effects of climate change. The results of a quantitative analysis utilizing the mixed effects model revealed that average temperature, precipitation, CO2 concentration, and adaptation methods all had a substantial impact on rice production, and elevated CO2 concentrations and management practices could exert positive influences on rice production. For every 1 °C and 1 % increase in average temperature and precipitation, rice yield decreased by 3.85 % and 0.56 %, respectively. For every 100 ppm increase in CO2 concentration, rice yield increased by 7.1 %. The variation of rice yield under different climate models, study sites and climate scenarios had significant variability. Elevated CO2 concentrations and management practices could compensate for the negative effects of climate change, benefiting rice production. This study comprehensively collected and analyzed a wide range of literature and research, which provides an in-depth understanding of the impacts of climate change on rice production and informs future research and policy development.

Source-sink relationships during grain filling in wheat in response to various temperature, water deficit, and nitrogen deficit regimes

Grain filling is a critical process for improving crop production under adverse conditions caused by climate change. Here, using a quantitative method, we quantified post-anthesis source-sink relationships of a large dataset to assess the contribution of remobilized pre-anthesis assimilates to grain growth for both biomass and nitrogen. The dataset came from 13 years of semi-controlled field experimentation, in which six bread wheat genotypes were grown at plot scale under contrasting temperature, water, and nitrogen regimes. On average, grain biomass was ~10% higher than post-anthesis above-ground biomass accumulation across regimes and genotypes. Overall, the estimated relative contribution (%) of remobilized assimilates to grain biomass became increasingly significant with increasing stress intensity, ranging from virtually nil to 100%. This percentage was altered more by water and nitrogen regimes than by temperature, indicating the greater impact of water or nitrogen regimes relative to high temperatures under our experimental conditions. Relationships between grain nitrogen demand and post-anthesis nitrogen uptake were generally insensitive to environmental conditions, as there was always significant remobilization of nitrogen from vegetative organs, which helped to stabilize the amount of grain nitrogen. Moreover, variations in the relative contribution of remobilized assimilates with environmental variables were genotype dependent. Our analysis provides an overall picture of post-anthesis source-sink relationships and pre-anthesis assimilate contributions to grain filling across (non-)environmental factors, and highlights that designing wheat adaptation to climate change should account for complex multifactor interactions.

Phenological Adaptation of Wheat Varieties to Rising Temperatures: Implications for Yield Components and Grain Quality

This study examined the effects of late sowing, water restrictions, and interannual weather variations on wheat grain yield and quality through field trials in Spain over two growing seasons. Delayed sowing and water scarcity significantly reduced yields, with grain quality mainly affected under rainfed conditions. Early-maturing varieties performed better in these conditions, benefiting from lower temperatures and extended grain-filling periods, leading to higher solar radiation interception, potentially increased photosynthetic activity, and improved yields. These varieties also saved water through reduced total cumulative evapotranspiration from sowing to maturity (ETo TOT), which was advantageous in water-limited environments. In contrast, late-maturing varieties were exposed to higher maximum temperatures during grain filling and experienced greater ETo TOT, leading to lower yields, reduced hectoliter weight, and a lower P/L ratio (tenacity/extensibility). This study highlighted the importance of optimizing temperature exposure and evapotranspiration for improved grain yield and quality, especially under climate change conditions with higher temperatures and water shortages. Notably, it established, for the first time, the importance of phenology on wheat quality of different varieties, suggesting that targeted selection for specific phenology could mitigate the negative impacts of heat stress not only on grain yield but also on grain quality.

Impact of coupled input data source-resolution and aggregation on contributions of high-yielding traits to simulated wheat yield

High-yielding traits can potentially improve yield performance under climate change. However, data for these traits are limited to specific field sites. Despite this limitation, field-scale calibrated crop models for high-yielding traits are being applied over large scales using gridded weather and soil datasets. This study investigates the implications of this practice. The SIMPLACE modeling platform was applied using field, 1 km, 25 km, and 50 km input data resolution and sources, with 1881 combinations of three traits [radiation use efficiency (RUE), light extinction coefficient (K), and fruiting efficiency (FE)] for the period 2001-2010 across Germany. Simulations at the grid level were aggregated to the administrative units, enabling the quantification of the aggregation effect. The simulated yield increased by between 1.4 and 3.1 t ha- 1 with a maximum RUE trait value, compared to a control cultivar. No significant yield improvement (< 0.4 t ha- 1) was observed with increases in K and FE alone. Utilizing field-scale input data showed the greatest yield improvement per unit increment in RUE. Resolution of water related inputs (soil characteristics and precipitation) had a notably higher impact on simulated yield than of temperature. However, it did not alter the effects of high-yielding traits on yield. Simulated yields were only slightly affected by data aggregation for the different trait combinations. Warm-dry conditions diminished the benefits of high-yielding traits, suggesting that benefits from high-yielding traits depend on environments. The current findings emphasize the critical role of input data resolution and source in quantifying a large-scale impact of high-yielding traits.

Phenological Adaptation Is Insufficient to Offset Climate Change-Induced Yield Losses in US Hybrid Maize

Climate change is projected to decrease maize yields due to warmer temperatures and their consequences. Studies using crop growth models (CGMs), however, have predicted that, through a combination of alterations to planting date, flowering time, and maturity, these yield losses can be mitigated or even reversed. Here, we examine three assumptions of such studies: (1) that climate has driven historical phenological trends, (2) that CGM ensembles provide unbiased estimates of yields under high temperatures, and (3) that the effects of temperature on yields are an emergent property of interactions between phenology and environment. We used data on maize phenology from the United States Department of Agriculture, a statistical model of maize hybrid heat tolerance derived from 80 years of public yield trial records across four US states, and outputs of an ensemble of CMIP6 climate models. While planting dates have advanced historically, we found a trend toward later planting dates after 2005 and no trend for silking or maturity, shifting more time into the reproductive period. We then projected maize yields using the historical model and crop calendars devised using three previously proposed adaptation strategies. In contrast to studies using CGMs, our statistical yield model projected severe yield losses under all three strategies. Finally, we projected maize yields accounting for historical genetic variability for heat tolerance, discovering that it was insufficient to overcome the negative effects of projected warming. These projections are driven by greater heat stress exposure under all crop calendars and climate scenarios. Combined with analysis of the internal sensitivities of CGMs to temperature, our results suggest that current projections do not adequately account for the effects of increasing temperatures on maize yields. Climate adaptation in the US Midwest must utilize a richer set of strategies than phenological adaptation, including improvements to heat tolerance and crop diversification.

Unveiling geospatial heterogeneity in climate's impacts on wheat production to advance spatially-matched climate-adaptive agricultural management in the North China plain

Influence of climate change on the geospatial heterogeneity in agricultural production remains poorly understood. In this study, heterogeneity in climate's impacts on wheat production across the North China Plain (NCP) was explored by integrating APSIM model, process-based factor-control quantitative approach, and geostatistical analyses. The results indicated that increased precipitation and minimum temperature boosted yields, while elevated maximum temperature and reduced radiation exerted adverse effects. The most pronounced negative impact arose from the coupling variation between maximum temperature and radiation, contributing to yields' variations of -5.84% from 2000 to 2010 and -5.22% from 2010 to 2020. In last two decades, climate change has augmented the overall geospatial heterogeneity degree in wheat yields. The chief factor contributing to yields' heterogeneity was the maximum temperature during anthesis-maturation stage, explaining an average of 37.6% of yields' heterogeneity, followed by precipitation throughout the whole growth period and the anthesis-maturation stage, explaining 36.1% and 34.5% respectively. A reciprocal enhancement mechanism exists between factors in driving yields' heterogeneity. Wheat yields in the southwestern NCP benefited more from increased precipitation and minimum temperature. Between 2000 and 2010, yields in the central NCP (junctions of Henan, Hebei, and Shandong) experienced the most pronounced adverse impact from increased maximum temperature. However, by 2010-2020, significant adverse impact shifted to western NCP, expanding spatially. During 2010-2020, the geospatial scope of radiation's significant negative impact expanded compared to the preceding decade, particularly affecting the yields in central and eastern NCP. The identified geospatial heterogeneity pattern of climate's impacts can guide spatially-matched climate-adaptive management adjustments. For instance, intensifying the defense against high-temperature's impacts in northwestern Henan, southern Hebei, and western Shandong, while improving the adaptation to radiation reduction in the central and eastern NCP. The findings are expected to advance regional-scale climate-smart agricultural development.

Observational evidence for groundwater influence on crop yields in the United States

As climate change shifts crop exposure to dry and wet extremes, a better understanding of factors governing crop response is needed. Recent studies identified shallow groundwater-groundwater within or near the crop rooting zone-as influential, yet existing evidence is largely based on theoretical crop model simulations, indirect or static groundwater data, or small-scale field studies. Here, we use observational satellite yield data and dynamic water table simulations from 1999 to 2018 to provide field-scale evidence for shallow groundwater effects on maize yields across the United States Corn Belt. We identify three lines of evidence supporting groundwater influence: 1) crop model simulations better match observed yields after improvements in groundwater representation; 2) machine learning analysis of observed yields and modeled groundwater levels reveals a subsidy zone between 1.1 and 2.5 m depths, with yield penalties at shallower depths and no effect at deeper depths; and 3) locations with groundwater typically in the subsidy zone display higher yield stability across time. We estimate an average 3.4% yield increase when groundwater levels are at optimum depth, and this effect roughly doubles in dry conditions. Groundwater yield subsidies occur ~35% of years on average across locations, with 75% of the region benefitting in at least 10% of years. Overall, we estimate that groundwater-yield interactions had a net monetary contribution of approximately $10 billion from 1999 to 2018. This study provides empirical evidence for region-wide groundwater yield impacts and further underlines the need for better quantification of groundwater levels and their dynamic responses to short- and long-term weather conditions.

CO2 response screen in grass Brachypodium reveals the key role of a MAP kinase in CO2-triggered stomatal closure

Plants respond to increased CO2 concentrations through stomatal closure, which can contribute to increased water use efficiency. Grasses display faster stomatal responses than eudicots due to dumbbell-shaped guard cells flanked by subsidiary cells working in opposition. However, forward genetic screening for stomatal CO2 signal transduction mutants in grasses has yet to be reported. The grass model Brachypodium distachyon is closely related to agronomically important cereal crops, sharing largely collinear genomes. To gain insights into CO2 control mechanisms of stomatal movements in grasses, we developed an unbiased forward genetic screen with an EMS-mutagenized B. distachyon M5 generation population using infrared imaging to identify plants with altered leaf temperatures at elevated CO2. Among isolated mutants, a "chill1" mutant exhibited cooler leaf temperatures than wild-type Bd21-3 parent control plants after exposure to increased CO2. chill1 plants showed strongly impaired high CO2-induced stomatal closure despite retaining a robust abscisic acid-induced stomatal closing response. Through bulked segregant whole-genome sequencing analyses followed by analyses of further backcrossed F4 generation plants and generation and characterization of sodium azide and CRISPR-cas9 mutants, chill1 was mapped to a protein kinase, Mitogen-Activated Protein Kinase 5 (BdMPK5). The chill1 mutation impaired BdMPK5 protein-mediated CO2/HCO3- sensing together with the High Temperature 1 (HT1) Raf-like kinase in vitro. Furthermore, AlphaFold2-directed structural modeling predicted that the identified BdMPK5-D90N chill1 mutant residue is located at the interface of BdMPK5 with the BdHT1 Raf-like kinase. BdMPK5 is a key signaling component that mediates CO2-induced stomatal movements and is proposed to function as a component of the primary CO2 sensor in grasses.

Natural variation in LONELY GUY-Like 1 regulates rice grain weight under warmer night conditions

Global nighttime temperatures are rising at twice the rate of daytime temperatures and pose a challenge for rice (Oryza sativa) production. High nighttime temperature (HNT) stress affects rice yield by reducing grain weight, size, and fertility. Although the genes associated with these yield parameters have been identified and characterized under normal temperatures, the genetic basis of grain weight regulation under HNT stress remains less explored. We examined the natural variation for rice single grain weight (SGW) under HNT stress imposed during grain development. A genome-wide association analysis identified several loci associated with grain weight under HNT stress. A locus, SGW1, specific to HNT conditions resolved to LONELY GUY-Like 1 (LOGL1), which encodes a putative cytokinin-activation enzyme. We demonstrated that LOGL1 contributes to allelic variation at SGW1. Accessions with lower LOGL1 transcript abundance had higher grain weight under HNT. This was supported by the higher grain weight of logl1-mutants relative to the wild type under HNT. Compared to logl1-mutants, LOGL1 over-expressers showed increased sensitivity to HNT. We showed that LOGL1 regulates the thiamin biosynthesis pathway, which is under circadian regulation, which in turn is likely perturbed by HNT stress. These findings provide a genetic source to enhance rice adaptation to warming night temperatures and improve our mechanistic understanding of HNT stress tolerance pathways.