Consistent negative response of US crops to high temperatures in observations and crop models

Optimized irrigation and fertilization can mitigate negative CO2 impacts on seed yield and vigor of hybrid maize

Seed yield and vigor of hybrid maize determine the planting, yield, and quality of maize, and consequently affect food, nutrition, and livelihood security; however, the response of seed yield and vigor to climate change is still unclear. We established an optimization-simulation framework consisting of a water‑nitrogen crop production function, a seed vigor and a gridded process-based model to optimize irrigation and nitrogen fertilization management, and used it to evaluate seed yield and vigor in major seed production locations of China, the USA, and Mexico. This framework could reflect the influence of water and nitrogen inputs at different stages on seed yield and vigor considering the spatio-temporal variability of climate and soil properties. Projected seed yield and vigor decreased by 5.8-9.0 % without adaptation by the 2050s, due to the 1.3-5.8 % decrease in seed number and seed protein concentration. Seed yield was positively correlated with CO2 and negatively correlated with temperature, while seed vigor depended on the response of components of seed vigor to climatic factors. Under optimized management, the direct positive effects of temperature on seed protein concentration and CO2 on seed number were strengthened, and the direct negative effects of temperature on seed number and CO2 on seed protein concentration were weakened, which mitigated the reductions in both seed yield and vigor. Elevated CO2 was projected to exacerbate the 2.6 % seed vigor reduction and mitigate the 2.9 % seed yield loss without adaptation, while optimized management could increase seed yield by 4.1 % and mitigate the 2.2 % seed vigor reduction in the Hexi Corridor of China, and decrease the seed yield and vigor reduction by 2.4-5.8 % in the USA and Mexico. Optimized management can strengthen the positive and mitigate the negative effects of climate change on irrigated hybrid maize and inform high-yield and high-quality seed production globally.

LHP1 and INO80 cooperate with ethylene signaling for warm ambient temperature response by activating specific bivalent genes

Ethylene signaling has been indicated as a potential positive regulator of plant warm ambient temperature response, but its underlying molecular mechanisms are largely unknown. Here, we show that LHP1 and INO80 cooperate with ethylene signaling for warm ambient temperature response by activating specific bivalent genes. We found that the presence of warm ambient temperature activates ethylene signaling through EIN2 and EIN3, leading to an interaction between LHP1 and accumulated EIN2-C to co-regulate a subset of LHP1-bound genes marked by H3K27me3 and H3K4me3 bivalency. Furthermore, we demonstrate that INO80 is recruited to bivalent genes by interacting with EIN2-C and EIN3, promoting H3K4me3 enrichment and facilitating transcriptional activation in response to a warm ambient temperature. Together, our findings illustrate a mechanism wherein ethylene signaling orchestrates LHP1 and INO80 to regulate warm ambient temperature response by activating specific bivalent genes in Arabidopsis.

Data-driven identification of environmental variables influencing phenotypic plasticity to facilitate breeding for future climates

Phenotypic plasticity describes a genotype's ability to produce different phenotypes in response to different environments. Breeding crops that exhibit appropriate levels of plasticity for future climates will be crucial to meeting global demand, but knowledge of the critical environmental factors is limited to a handful of well-studied major crops. Using 727 maize (Zea mays L.) hybrids phenotyped for grain yield in 45 environments, we investigated the ability of a genetic algorithm and two other methods to identify environmental determinants of grain yield from a large set of candidate environmental variables constructed using minimal assumptions. The genetic algorithm identified pre- and postanthesis maximum temperature, mid-season solar radiation, and whole season net evapotranspiration as the four most important variables from a candidate set of 9150. Importantly, these four variables are supported by previous literature. After calculating reaction norms for each environmental variable, candidate genes were identified and gene annotations investigated to demonstrate how this method can generate insights into phenotypic plasticity. The genetic algorithm successfully identified known environmental determinants of hybrid maize grain yield. This demonstrates that the methodology could be applied to other less well-studied phenotypes and crops to improve understanding of phenotypic plasticity and facilitate breeding crops for future climates.

Drip Fertigation Increases Maize Grain Yield by Affecting Phenology, Grain Filling Process, Biomass Accumulation and Translocation: A 4-Year Field Trial

Drip fertigation (DF) is a widely used technology to increase grain yield with water and fertilizer conservation. However, the mechanism of high grain yield (GY) under DF is still unclear. Here, a four-year field experiment assessed the impacts of four treatments (i.e., conventional irrigation and nitrogen application, CK; drip irrigation with conventional nitrogen fertilization, DI; split-nitrogen fertigation with conventional irrigation, SF; and drip fertigation, DF) on maize phenology, leaf photosynthetic rates, grain filling processes, plant biomass, and GY. The results showed that DF significantly increased maize GY by affecting phenology, grain filling traits, aboveground biomass (BIO) accumulation, and translocation. Specifically, DF significantly increased leaf chlorophyll content, which enhanced leaf photosynthetic rates, and together with an increase of leaf area index, promoted BIO accumulation. As a result, the BIO at the silking stage of DF increased by 29.5%, transported biomass increased by 109.2% (1.2 t ha-1), and the accumulation of BIO after silking increased by 23.1% (1.7 t ha-1) compared with CK. Meanwhile, DF prolonged grain filling days, significantly increased the grain weight of 100 kernels, and promoted GY increase. Compared with CK, the four-year averaged GY and BIO increased by 34.3% and 26.8% under DF; a 29.7%, 46.1%, and 24.2% GY increase and a 30.7%, 39.5%, and 29.9% BIO increase were contributed by irrigation, nitrogen, and coupling effects of irrigation and nitrogen, respectively. These results reveal the high yield mechanism of drip-fertigated maize, and are of important significance for promoting the application of drip fertigation.

Thresholds and extent of temperature effects on maize yield differ in different grain-filling stages

Temperature is a vital environmental factor affecting grain filling and maize yield. The response of maize yield to temperature at different stages of grain filling, however, remains uncharacterized. This study used "Zhengdan 958" as the test material to analyze the high-temperature threshold and yield sensitivity of grain-filling in different periods without water stress by using the data from staging sowing experiments at agro-meteorological experimental stations in Hebi and Suzhou in the Huang-Huai-Hai Plain from 2019 to 2022. The results demonstrated that: (1) the maximum temperature threshold was different in various periods of maize grain-filling in the Huang-Huai-Hai Plain, showing the early grain-filling period (EP) > the active grain-filling period (AP) > the late grain-filling period (LP). With the largest differences in temperature thresholds found in AP, the maximum temperature threshold of AP can better reflect the characteristics of grain filling rather than the whole filling period. (2) The heat of the grain-filling period can explain more than 80 % of the yield variation and affect the yield by influencing the number of days required to reach the maximum grain-filling rate (Vmaxd) and the duration of the active grain-filling period (DAP). (3) The growing degree days (GDD) is the most significant controlling factor affecting yield; however, the effect of heat degree days (HDD) cannot be ignored. The HDD and cumulative thresholds of HDD in the EP and AP of grain-filling can better reflect the effect of heat on yield. The accumulation thresholds of HDD at Hebi and Suzhou were 28.1 °C·d and 15.2 °C·d in the EP period, and 31.0 °C·d and 14.9 °C·d in the AP period, respectively. The results provide a basis for the precise identification of heat disasters during grain-filling and the scientific adjustment of sowing dates.

LHP1 and INO80 cooperate with ethylene signaling for warm ambient temperature response by activating specific bivalent genes

Ethylene signaling has been indicated as a potential positive regulator of plant warm ambient temperature response but its underlying molecular mechanisms are largely unknown. Here, we show that LHP1 and INO80 cooperate with ethylene signaling for warm ambient temperature response by activating specific bivalent genes. We found that the presence of warm ambient temperature activates ethylene signaling through EIN2 and EIN3, leading to an interaction between LHP1 and accumulated EIN2-C to co-regulate a subset of LHP1-bound genes marked by H3K27me3 and H3K4me3 bivalency. Furthermore, we demonstrate that INO80 is recruited to bivalent genes by interacting with EIN2-C and EIN3, promoting H3K4me3 enrichment and facilitating transcriptional activation in response to warm ambient temperature. Together, our findings illustrate a novel mechanism wherein ethylene signaling orchestrates LHP1 and INO80 to regulate warm ambient temperature response through activating specific bivalent genes in Arabidopsis.

Plant hydraulics at the heart of plant, crops and ecosystem functions in the face of climate change

Plant hydraulics is crucial for assessing the plants' capacity to extract and transport water from the soil up to their aerial organs. Along with their capacity to exchange water between plant compartments and regulate evaporation, hydraulic properties determine plant water relations, water status and susceptibility to pathogen attacks. Consequently, any variation in the hydraulic characteristics of plants is likely to significantly impact various mechanisms and processes related to plant growth, survival and production, as well as the risk of biotic attacks and forest fire behaviour. However, the integration of hydraulic traits into disciplines such as plant pathology, entomology, fire ecology or agriculture can be significantly improved. This review examines how plant hydraulics can provide new insights into our understanding of these processes, including modelling processes of vegetation dynamics, illuminating numerous perspectives for assessing the consequences of climate change on forest and agronomic systems, and addressing unanswered questions across multiple areas of knowledge.

Air quality improvements can strengthen China's food security

Air pollution exerts crucial influence on crop yields and impacts regional and global food supplies. Here we employ a statistical model using satellite-based observations and flexible functional forms to analyse the synergistic effects of reductions in ozone and aerosols on China's food security. The model consistently shows that ozone is detrimental to crops, whereas aerosol has variable effects. China's maize, rice and wheat yields are projected to increase by 7.84%, 4.10% and 3.43%, respectively, upon reaching two air quality targets (60 μg m-3 for peak-season ozone and 35 μg m-3 for annual fine particulate matter). Average calories produced from these crops would surge by 4.51%, potentially allowing China to attain grain self-sufficiency 2 years earlier than previously estimated. These results show that ozone pollution control should be a high priority to increase staple crop edible calories, and future stringent air pollution regulations would enhance China's food security.

Impact of individual, combined and sequential stress on photosynthesis machinery in rice (Oryza sativa L)

Abiotic stresses such as heat, drought and submergence are major threats to global food security. Despite simultaneous or sequential occurrence of these stresses being recurrent under field conditions, crop response to such stress combinations is poorly understood. Rice is a staple food crop for the majority of human beings. Exploitation of existing genetic diversity in rice for combined and/or sequential stress is a useful approach for developing climate-resilient cultivars. We phenotyped ~400 rice accessions under high temperature, drought, or submergence and their combinations. A cumulative performance index revealed Lomello as the best performer across stress and stress combinations at the seedling stage. Lomello showed a remarkable ability to maintain a higher quantum yield of photosystem (PS) II photochemistry. Moreover, the structural integrity of the photosystems, electron flow through both PSI and PSII and the ability to protect photosystems against photoinhibition were identified as the key traits of Lomello across the stress environments. A higher membrane stability and an increased amount of leaf chlorophyll under stress may be due to an efficient management of reactive oxygen species (ROS) at the cellular level. Further, an efficient electron flow through the photosystems and, thus, a higher photosynthetic rate in Lomello is expected to act as a sink for ROS by reducing the rate of electron transport to the high amount of molecular oxygen present in the chloroplast. However, further studies are needed to identify the molecular mechanism(s) involved in the stability of photosynthetic machinery and stress management in Lomello during stress conditions.

Detect and attribute the extreme maize yield losses based on spatio-temporal deep learning

Providing accurate crop yield estimations at large spatial scales and understanding yield losses under extreme climate stress is an urgent challenge for sustaining global food security. While the data-driven deep learning approach has shown great capacity in predicting yield patterns, its capacity to detect and attribute the impacts of climatic extremes on yields remains unknown. In this study, we developed a deep neural network based multi-task learning framework to estimate variations of maize yield at the county level over the US Corn Belt from 2006 to 2018, with a special focus on the extreme yield loss in 2012. We found that our deep learning model hindcasted the yield variations with good accuracy for 2006-2018 (R2 = 0.81) and well reproduced the extreme yield anomalies in 2012 (R2 = 0.79). Further attribution analysis indicated that extreme heat stress was the major cause for yield loss, contributing to 72.5% of the yield loss, followed by anomalies of vapor pressure deficit (17.6%) and precipitation (10.8%). Our deep learning model was also able to estimate the accumulated impact of climatic factors on maize yield and identify that the silking phase was the most critical stage shaping the yield response to extreme climate stress in 2012. Our results provide a new framework of spatio-temporal deep learning to assess and attribute the crop yield response to climate variations in the data rich era.

Role of hydraulic traits in stomatal regulation of transpiration under different vapour pressure deficits across five Mediterranean tree crops

The differential stomatal regulation of transpiration among plant species in response to water deficit is not fully understood, although several hydraulic traits have been reported to influence it. This knowledge gap is partly due to a lack of direct and concomitant experimental data on transpiration, stomatal conductance, and hydraulic traits. We measured sap flux density (Js), stomatal conductance (gs), and different hydraulic traits in five crop species. Our aim was to contribute to establishing the causal relationship between water consumption and its regulation using a hydraulic trait-based approach. The results showed that the species-specific regulation of Js by gs was overall coordinated with the functional hydraulic traits analysed. Particularly relevant was the negative and significant relationship found between the Huber value (Hv) and its functional analogue ratio between maximum Js and gs (Jsmax/gsmax) which can be understood as a compensation to maintain the hydraulic supply to the leaves. The Hv was also significantly related to the slope of the relationship between gs and Js response to vapour pressure deficit and explained most of its variability, adding up to evidence recognizing Hv as a major trait in plant water relations. Thus, a hydraulic basis for regulation of tree water use should be considered.

Short- and long-term warming events on photosynthetic physiology, growth, and yields of field grown crops

Global temperatures are rising from increasing concentrations of greenhouse gases in the atmosphere associated with anthropogenic activities. Global warming includes a warmer shift in mean temperatures as well as increases in the probability of extreme heating events, termed heat waves. Despite the ability of plants to cope with temporal variations in temperature, global warming is increasingly presenting challenges to agroecosystems. The impact of warming on crop species has direct consequences on food security, therefore understanding impacts and opportunities to adapt crops to global warming necessitates experimentation that allows for modification of growth environments to represent global warming scenarios. Published studies addressing crop responses to warming are extensive, however, in-field studies where growth temperature is manipulated to mimic global warming are limited. Here, we provide an overview of in-field heating techniques employed to understand crop responses to warmer growth environments. We then focus on key results associated with season-long warming, as expected with rising global mean temperatures, and with heat waves, as a consequence of increasing temperature variability and rising global mean temperatures. We then discuss the role of rising temperatures on atmospheric water vapor pressure deficit and potential implications for crop photosynthesis and productivity. Finally, we review strategies by which crop photosynthetic processes might be optimized to adapt crops to the increasing temperatures and frequencies of heat waves. Key findings from this review are that higher temperatures consistently reduce photosynthesis and yields of crops even as atmospheric carbon dioxide increases, yet potential strategies to minimize losses from high-temperature exist.

A genetic tradeoff for tolerance to moderate and severe heat stress in US hybrid maize

Global climate change is increasing both average temperatures and the frequencies of extreme high temperatures. Past studies have documented a strong negative effect of exposures to temperatures >30°C on hybrid maize yields. However, these studies could not disentangle genetic adaptation via artificial selection from changes in agronomic practices. Because most of the earliest maize hybrids are no longer available, side-by-side comparisons with modern hybrids under current field conditions are generally impossible. Here, we report on the collection and curation of 81 years of public yield trial records covering 4,730 maize hybrids, which enabled us to model genetic variation for temperature responses among maize hybrids. We show that selection may have indirectly and inconsistently contributed to the genetic adaptation of maize to moderate heat stress over this time period while preserving genetic variance for continued adaptation. However, our results reveal the existence of a genetic tradeoff for tolerance to moderate and severe heat stress, leading to a decrease in tolerance to severe heat stress over the same time period. Both trends are particularly conspicuous since the mid-1970s. Such a tradeoff poses challenges to the continued adaptation of maize to warming climates due to a projected increase in the frequency of extreme heat events. Nevertheless, given recent advances in phenomics, enviromics, and physiological modeling, our results offer a degree of optimism for the capacity of plant breeders to adapt maize to warming climates, assuming appropriate levels of R&D investment.

Projected long-term climate trends reveal the critical role of vapor pressure deficit for soybean yields in the US Midwest

Extreme climate events including heat waves and droughts are projected to become more frequent under future climate change conditions. However, the mechanisms between soybean yields and climate factors, specifically involving variable rainfall and high heat episodes, are still unclear, particularly with respect to spatial trends in the United States (US) Midwest. A recently modified version of the model GLYCIM was used to evaluate rainfed soybean production across 12 states at a 10 km spatial resolution for three time periods (2011-2020, 2051-2060, 2091-2099) under Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5. Results showed that except for the northernmost Midwest counties, most of the current rainfed cropping system in the Midwest would suffer a 24.6-47.4 % yield loss without considering the CO₂ fertility effect. Incorporating the effect of elevated CO₂ showed a smaller yield loss of 11.6-29.5 %. The increased frequency of extreme degree days (EDD) or accumulation of hourly temperatures above 30 °C associated with increased vapor pressure deficit (VPD) played a key role in contributing to water deficits and resultant crop losses under these future climate conditions. Although a relatively weak relationship between summer rainfall and crop yield was observed, decreased rainfall caused VPD to increase which induced crop water deficits. These findings suggest that it is crucial to consider VPD along with high temperature and low rainfall trends simultaneously for development of potential management or breeding-based adaptative strategies for soybean.

Potential for surprising heat and drought events in wheat-producing regions of USA and China

Previous analyses of the possibility of global breadbasket failures have extrapolated risks based on historical relationships between climate and yields. However, climate change is causing unprecedented events globally, which could exceed critical thresholds and reduce yields, even if there is no historical precedent. This means that we are likely underestimating climate risks to our food system. In the case of wheat, parts of the USA and China show little historical relationship between yields and temperature, but extreme temperatures are now possible that exceed critical physiological thresholds in wheat plants. UNprecedented Simulated Extreme ENsemble (UNSEEN) approaches use large ensembles to generate plausible unprecedented events, which can inform our assessment of the risk to crops. We use the UNSEEN approach with a large ensemble of archived seasonal forecasts to generate thousands of plausible events over the last 40 years and compare the results with historically observed extreme temperature and precipitation. In the US midwest, extreme temperatures that would have happened approximately 1-in-100-years in 1981 now have a return period of 1-in-6 years, while in China, the current return period is on the order of 1-in-16 years. This means that in the US midwest, extreme temperatures that used to have a 1% chance to occur in 1981 now have a 17% chance to occur in any given year, while in China, the chance increased from 1% to 6%. Record-breaking years exceeding critical thresholds for enzymes in the wheat plant are now more likely than in the past, and these record-breaking hot years are associated with extremely dry conditions in both locations. Using geopotential height and wind anomalies from the UNSEEN ensemble, we demonstrate that strong winds over land pull dry air towards the regions these during extremely hot and dry unseen events. We characterize plausible extremes from the UNSEEN ensemble that can be used to help imagine otherwise unforeseen events, including a compound event in which high impacts co-occur in both regions, informing adaptation planning in these regions. Recent temperature extremes, especially in the US midwest, are unlikely to be a good proxy for what to expect in the next few years of today's climate, and local stakeholders might perceive their risk to be lower than it really is. We find that there is a high potential for surprise in these regions if people base risk analyses solely on historical datasets.

Quantifying the grapevine xylem embolism resistance spectrum to identify varieties and regions at risk in a future dry climate

Maintaining wine production under global warming partly relies on optimizing the choice of plant material for a given viticultural region and developing drought-resistant cultivars. However, progress in these directions is hampered by the lack of understanding of differences in drought resistance among Vitis genotypes. We investigated patterns of xylem embolism vulnerability within and among 30 Vitis species and sub-species (varieties) from different locations and climates, and assessed the risk of drought vulnerability in 329 viticultural regions worldwide. Within a variety, vulnerability to embolism decreased during summer. Among varieties, we have found wide variations in drought resistance of the vascular system in grapevines. This is particularly the case within Vitis vinifera, with varieties distributed across four clusters of embolism vulnerability. Ugni blanc and Chardonnay featured among the most vulnerable, while Pinot noir, Merlot and Cabernet Sauvignon ranked among the most resistant. Regions possibly at greater risk of being vulnerable to drought, such as Poitou-Charentes, France and Marlborough, New Zealand, do not necessarily have arid climates, but rather bear a significant proportion of vulnerable varieties. We demonstrate that grapevine varieties may not respond equally to warmer and drier conditions, and highlight that hydraulic traits are key to improve viticulture suitability under climate change.

The carbon and nitrogen metabolisms of Ardisia quinquegona were altered in different degrees by canopy and understory nitrogen addition in a subtropical forest

Although effects of atmospheric nitrogen (N) deposition on forest plants have been widely investigated, N interception and absorption effects by forest canopy should not be neglected. Moreover, how N deposition change the molecular biological process of understory dominant plants, which was easily influenced by canopy interception so as to further change physiological performance, remains poorly understood. To assess the effects of N deposition on forest plants, we investigated the effects of understory (UAN) and canopy N addition (CAN) on the transcriptome and physiological properties of Ardisia quinquegona, a dominant subtropical understory plant species in an evergreen broad-leaved forest in China. We identified a total of 7394 differentially expressed genes (DEGs). Three of these genes were found to be co-upregulated in CAN as compared to control (CK) after 3 and 6 h of N addition treatment, while 133 and 3 genes were respectively found to be co-upregulated and co-downregulated in UAN as compared to CK. In addition, highly expressed genes including GP1 (a gene involved in cell wall biosynthesis) and STP9 (sugar transport protein 9) were detected in CAN, which led to elevated photosynthetic capacity and accumulation of protein and amino acid as well as decrease in glucose, sucrose, and starch contents. On the other hand, genes associated with transport, carbon and N metabolism, redox response, protein phosphorylation, cell integrity, and epigenetic regulation mechanism were affected by UAN, resulting in enhanced photosynthetic capacity and carbohydrates and accumulation of protein and amino acid. In conclusion, our results showed that the CAN compared to UAN treatment had less effects on gene regulation and carbon and N metabolism. Canopy interception of N should be considered through CAN treatment to simulate N deposition in nature.

High temperature defense-related pathways, mediating lodicule expansion and spikelet opening in maize tassel

High temperature (HT) at flowering hinders pollen shedding, whereas mechanisms underlying stress-induced spikelet closure are poorly known in maize. Yield components, spikelet opening, and lodicule morphology/protein profiling upon HT stress during flowering were explored in maize inbred lines Chang 7-2 and Qi 319. HT induced spikelet closure and reduced pollen shed weight (PSW) and seed set. Qi 319 that had a 7-fold lower PSW than Chang 7-2 was more susceptible to HT. A small lodicule size reduced spikelet opening rate and angle, and more vascular bundles hastened lodicule shrinking in Qi 319. Lodicules were collected for proteomics. In HT-stressed lodicules, proteins involved in stress signal, cell wall, cell constructure, carbohydrate metabolism, and phytohormone signaling were associated with stress tolerance. Among these proteins, HT downregulated expression of ADP-ribosylation factor GTPase-activating protein domain2, SNAP receptor complex member11, and sterol methyltransferase2 in Qi 319 but not in Chang 7-2, agreeing well with protein abundance changes. Exogenous epibrassinolide enlarged spikelet opening angle and extended spikelet opening duration. These results suggest that dysfunction of actin cytoskeleton and membrane remodeling induced by HT likely limits lodicule expansion. Additionally, reduced vascular bundles in lodicule and application of epibrassinolide might confer spikelet tolerance to HT stress.

Increased probability of hot and dry weather extremes during the growing season threatens global crop yields

Although extreme weather events recur periodically everywhere, the impacts of their simultaneous occurrence on crop yields are globally unknown. In this study, we estimate the impacts of combined hot and dry extremes as well as cold and wet extremes on maize, rice, soybean, and wheat yields using gridded weather data and reported crop yield data at the global scale for 1980-2009. Our results show that co-occurring extremely hot and dry events have globally consistent negative effects on the yields of all inspected crop types. Extremely cold and wet conditions were observed to reduce crop yields globally too, although to a lesser extent and the impacts being more uncertain and inconsistent. Critically, we found that over the study period, the probability of co-occurring extreme hot and dry events during the growing season increased across all inspected crop types; wheat showing the largest, up to a six-fold, increase. Hence, our study highlights the potentially detrimental impacts that increasing climate variability can have on global food production.

Effects of Different Gene Editing Modes of CRISPR/Cas9 on Soybean Fatty Acid Anabolic Metabolism Based on GmFAD2 Family

Δ¹²-fatty acid dehydrogenase (FAD2) is the essential enzyme responsible for catalyzing the formation of linoleic acid from oleic acid. CRISPR/Cas9 gene editing technology has been an essential tool for molecular breeding in soybeans. To evaluate the most suitable type of gene editing in soybean fatty acid synthesis metabolism, this study selected five crucial enzyme genes of the soybean FAD2 gene family-GmFAD2-1A, GmFAD2-1B, GmFAD2-2A, GmFAD2-2B, and GmFAD2-2C-and created a CRISPR/Cas9-mediated single gene editing vector system. The results of Sanger sequencing showed that 72 transformed plants positive for T₁ generation were obtained using Agrobacterium-mediated transformation, of which 43 were correctly edited plants, with the highest editing efficiency of 88% for GmFAD2-2A. The phenotypic analysis revealed that the oleic acid content of the progeny of GmFAD2-1A gene-edited plants had a higher increase of 91.49% when compared to the control JN18, and the rest of the gene-edited plants in order were GmFAD2-2A, GmFAD2-1B, GmFAD2-2C, and GmFAD2-2B. The analysis of gene editing type has indicated that base deletions greater than 2bp were the predominant editing type in all editing events. This study provides ideas for the optimization of CRISPR/Cas9 gene editing technology and the development of new tools for precise base editing in the future.

Effects of high night temperature on soybean yield and compositions

Introduction

Soybean is sensitive to light and temperature. Under the background of global asymmetric climate warming.

Methods

The increase of night temperature may have an important impact on soybean yield. In this study, three varieties with different level of protein were planted under 18°C and 28°C night temperatures for investigating the effects of high night temperatures on soybean yield formation and the dynamic changes of non-structural carbohydrates (NSC) during the seed filling period (R5-R7).

Results and discussion

The results indicated that high night temperatures resulted in smaller seed size, lower seed weight, and a reduced number of effective pods and seeds per plant, and thus, a significant reduction in yield per plant. Analysis of the seed composition variations showed carbohydrates were more substantially affected by high night temperature than protein and oil. We observed "carbon hunger" caused by high night temperature increased photosynthesis and sucrose accumulation in the leaves during the early stage of high night temperature treatment. With elongated treated time, the excessive carbon consumption led to the decrease of sucrose accumulation in soybean seeds. Transcriptome analysis of leaves after 7 days of treatment showed that the expression of most sucrose synthase and sucrose phosphatase genes decreased significantly under the high night temperature. Which could be another important reason for the decrease of sucrose. These findings provided a theoretical basis for enhancing the tolerance of soybean to high night temperature.

Global warming and testis function: A challenging crosstalk in an equally challenging environmental scenario

Environmental pollution, accounting for both chemical and physical factors, is a major matter of concern due to its health consequences in both humans and animals. The release of greenhouse gases with the consequent increase in environmental temperature is acknowledged to have a major impact on the health of both animals and humans, in current and future generations. A large amount of evidence reports detrimental effects of acute heat stress on testis function, particularly on the spermatogenetic and steroidogenetic process, in both animal and human models, wich is largely related to the testis placement within the scrotal sac and outside the abdomen, warranting an overall scrotal temperature of 2°C-4°C lower than the core body temperature. This review will provide a thorough evaluation of environmental temperature's effect on testicular function. In particular, basic concepts of body thermoregulation will be discussed together with available data about the association between testis damage and heat stress exposure. In addition, the possible association between global warming and the secular decline of testis function will be critically evaluated in light of the available epidemiological studies.

Contrasting impacts of dry versus humid heat on US corn and soybean yields

The impact of extreme heat on crop yields is an increasingly pressing issue given anthropogenic climate warming. However, some of the physical mechanisms involved in these impacts remain unclear, impeding adaptation-relevant insight and reliable projections of future climate impacts on crops. Here, using a multiple regression model based on observational data, we show that while extreme dry heat steeply reduced U.S. corn and soy yields, humid heat extremes had insignificant impacts and even boosted yields in some areas, despite having comparably high dry-bulb temperatures as their dry heat counterparts. This result suggests that conflating dry and humid heat extremes may lead to underestimated crop yield sensitivities to extreme dry heat. Rainfall tends to precede humid but not dry heat extremes, suggesting that multivariate weather sequences play a role in these crop responses. Our results provide evidence that extreme heat in recent years primarily affected yields by inducing moisture stress, and that the conflation of humid and dry heat extremes may lead to inaccuracy in projecting crop yield responses to warming and changing humidity.

Maize cytolines as models to study the impact of different cytoplasms on gene expression under heat stress conditions

BACKGROUND

Crops are under constant pressure due to global warming, which unfolds at a much faster pace than their ability to adapt through evolution. Agronomic traits are linked to cytoplasmic-nuclear genome interactions. It thus becomes important to understand the influence exerted by the organelles on gene expression under heat stress conditions and profit from the available genetic diversity. Maize (Zea mays) cytolines allow us to investigate how the gene expression changes under heat stress conditions in three different cytoplasmic environments, but each having the same nucleus. Analyzing retrograde signaling in such an experimental set-up has never been done before. Here, we quantified the response of three cytolines to heat stress as differentially expressed genes (DEGs), and studied gene expression patterns in the context of existing polymorphism in their organellar genomes.

RESULTS

Our study unveils a plethora of new genes and GO terms that are differentially expressed or enriched, respectively, in response to heat stress. We report 19,600 DEGs as responding to heat stress (out of 30,331 analyzed), which significantly enrich 164 GO biological processes, 30 GO molecular functions, and 83 GO cell components. Our approach allowed for the discovery of a significant number of DEGs and GO terms that are not common in the three cytolines and could therefore be linked to retrograde signaling. Filtering for DEGs with a fold regulation > 2 (absolute values) that are exclusive to just one of the cytolines, we find a total of 391 up- and down-DEGs. Similarly, there are 19 GO terms with a fold enrichment > 2 that are cytoline-specific. Using GBS data we report contrasting differences in the number of DEGs and GO terms in each cytoline, which correlate with the genetic distances between the mitochondrial genomes (but not chloroplast) and the original nuclei of the cytolines, respectively.

CONCLUSIONS

The experimental design used here adds a new facet to the paradigm used to explain how gene expression changes in response to heat stress, capturing the influence exerted by different organelles upon one nucleus rather than investigating the response of several nuclei in their innate cytoplasmic environments.

A dynamic phosphoproteomic analysis provides insight into the C4 plant maize (Zea mays L.) response to natural diurnal changes

As sessile organisms, plants need to respond to rapid changes in numerous environmental factors, mainly diurnal changes of light, temperature, and humidity. Maize is the world's most grown crop, and as a C4 plant it exhibits high photosynthesis capacity, reaching the highest rate of net photosynthesis at midday; that is, there is no "midday depression." Revealing the physiological responses to diurnal changes and underlying mechanisms will be of great significance for guiding maize improvement efforts. In this study, we collected maize leaf samples and analyzed the proteome and phosphoproteome at nine time points during a single day/night cycle, quantifying 7424 proteins and 5361 phosphosites. The new phosphosites identified in our study increased the total maize phosphoproteome coverage by 8.5%. Kinase-substrate network analysis indicated that 997 potential substrates were phosphorylated by 20 activated kinases. Through analysis of proteins with significant changes in abundance and phosphorylation, we found that the response to a heat stimulus involves a change in the abundance of numerous proteins. By contrast, the high light at noon and rapidly changing light conditions induced changes in the phosphorylation level of proteins involved in processes such as chloroplast movement, photosynthesis, and C4 pathways. Phosphorylation is involved in regulating the activity of large number of enzymes; for example, phosphorylation of S55 significantly enhanced the activity of maize phosphoenolpyruvate carboxykinase1 (ZmPEPCK1). Overall, the database of dynamic protein abundance and phosphorylation we have generated provides a resource for the improvement of C4 crop plants.

Choosing multiple linear regressions for weather-based crop yield prediction with ABSOLUT v1.2 applied to the districts of Germany

ABSOLUT v1.2 is an adaptive algorithm that uses correlations between time-aggregated weather variables and crop yields for yield prediction. In contrast to conventional regression-based yield prediction methods, a very broad range of possible input features and their combinations are exhaustively tested for maximum explanatory power. Weather variables such as temperature, precipitation, and sunshine duration are aggregated over different seasonal time periods preceding the harvest to 45 potential input features per original variable. In a first step, this large set of features is reduced to those aggregates very probably holding explanatory power for observed yields. The second, computationally demanding step evaluates predictions for all districts with all of their possible combinations. Step three selects those combinations of weather features that showed the highest predictive power across districts. Finally, the district-specific best performing regressions among these are used for actual prediction, and the results are spatially aggregated. To evaluate the new approach, ABSOLUT v1.2 is applied to predict the yields of silage maize, winter wheat, and other major crops in Germany based on two decades of data from about 300 districts. It turned out to be absolutely crucial to not only make out-of-sample predictions (solely based on data excluding the target year to predict) but to also consequently separate training and testing years in the process of feature selection. Otherwise, the prediction accuracy would be over-estimated by far. The question arises whether performances claimed for other statistical modelling examples are often upward-biased through input variable selection disregarding the out-of-sample principle.

Whole farm planning raises profit despite burgeoning climate crisis

The climate crisis challenges farmer livelihoods as increasingly frequent extreme weather events impact the quantum and consistency of crop production. Here, we develop a novel paradigm to raise whole farm profit by optimising manifold variables that drive the profitability of irrigated grain farms. We build then invoke a new decision support tool-WaterCan Profit-to optimise crop type and areas that collectively maximise farm profit. We showcase four regions across a climate gradient in the Australian cropping zone. The principles developed can be applied to cropping regions or production systems anywhere in the world. We show that the number of profitable crop types fell from 35 to 10 under future climates, reflecting the interplay between commodity price, yield, crop water requirements and variable costs. Effects of climate change on profit were not related to long-term rainfall, with future climates depressing profit by 11-23% relative to historical climates. Impacts of future climates were closely related to crop type and maturity duration; indeed, many crop types that were traditionally profitable under historical climates were no longer profitable in future. We demonstrate that strategic whole farm planning of crop types and areas can yield significant economic benefits. We suggest that future work on drought adaptation consider genetic selection criteria more diverse than phenology and yield alone. Crop types with (1) higher value per unit grain weight, (2) lower water requirements and (3) higher water-use efficiency are more likely to ensure the sustainability and prosperity of irrigated grain production systems under future climates.

Empirical analysis of rice and maize production under climate change in China

The past few decades of extreme drought and flooding caused by changing climate conditions have significantly affected agricultural production globally. This study focuses on two vital crops in China-maize and rice-and provides a comprehensive analysis of how these crops are affected by climate change-induced factors over the periods 1978Q1-2015Q4. Four key findings were obtained. First, using a nonparametric approach to estimate actual and observed trends of climatic variables, the results show a significant positive trend in average temperature from February to October. On the other hand, seasonal temperature increases during spring, summer, and autumn. Second, the results show no significant change in the monthly, seasonal, and annual rainfall patterns when examined over the study period. Third, using an autoregressive distributed lag (ARDL) model, we find that while temperature and rainfall do not significantly support rice production in the long and short run, they play a substantial role in maize production in China. Finally, we find no significant difference in the results for rice when the quantile regression (QR) technique that controls for distributional asymmetry effects is employed. However, the impact of temperature on maize decreases at higher quantiles. Given the outcomes of our study, we argue that an advanced irrigation system is crucial and must be encouraged to minimize the effects of climate change on crop production.

Physiological and biochemical responses of hybrid maize (Zea mays L.) varieties grown under heat stress conditions

Maize (Zea mays L.) is the second most commonly produced and consumed crop after wheat globally and is adversely affected by high heat, which is a significant abiotic stress factor. This study was carried out to determine the physiological and biochemical responses of hybrid corn varieties under heat stress ('HS') compared to control ('C') conditions during the 2020 and 2021 growing seasons. The experiment was conducted under natural conditions in the Southeastern region of Turkey, where the most intense temperatures are experienced. This experiment used split plots in randomized blocks with three replications, with 'HS' and 'C' growing conditions applied to the main plots and the different hybrid corn varieties (FAO 650) planted on the sub plots. Mean values of days to 50% tasseling (DT, day), grain yield (GY, kg ha^-1), leaf water potential (LWP, %), chlorophyll-a (Chl-a, mg g^-1), cell membrane damage (CMD, %), and total phenol content (TPC, μg g^-1) were significantly different between years, growing conditions, and hybrid corn varieties. Changes in the climate played a significant role in the differences between the years and growing conditions (GC), while the genetic characteristics of the different corn varieties explained the differences in outcomes between them. The values of DT, GY, LWP, Chl-a, CMD, and TPC ranged from 49.06-53.15 days, 9,173.0-10,807.2 kg ha^-1, 78.62-83.57%, 6.47-8.62 mg g^-1, 9.61-13.54%, and 232.36-247.01 μg g^-1, respectively. Significant correlations were recorded between all the parameters. Positive correlations were observed between all the variables except for CMD. The increased damage to cell membranes under 'HS' caused a decrease in the other measured variables, especially GY. In contrast, the GY increased with decreased CMD. CMD was important in determining the stress and tolerance level of corn varieties under 'HS' conditions. The GY and other physiological parameters of ADA 17.4 and SYM-307 candidate corn varieties surpassed the control hybrid corn cultivars. The results revealed that the ADA 17.4 and SYM-307 cultivars might have 'HS'-tolerate genes.

Maize stomatal responses against the climate change

Drought and heat, in the context of climate change, are expected to increase in many agricultural areas across the globe. Among current abiotic stresses, they are the most limiting factors that influence crop growth and productivity. Maize is one of most widely produced crops of the world, being the first in grain production with a yield that exceeded 1.1 billion tons in 2021. Despite its wide distribution in semi-arid regions, it is highly vulnerable to climate change, which triggers important losses in its productivity. This article explores how maize yield may persevere through climate change by focusing on the stomatal regulation of gas exchange. The emerging picture unravels that maize copes with drought stress by reducing stomatal size and stomatal pore area, and increasing stomatal density, which, in turn, reduces transpiration and photosynthetic rate. When drought and heat co-occur, heat enhances stomatal response to drought stress. To avoid plant heat damage, the decline in stomatal aperture could trigger the expansion of the distance of action, from the longitudinal leaf veins, of ZmSHR1, which might act to positively regulate ZmSPCHs/ZmICE1 heterodimers, increasing the stomatal density. Only when drought is not very severe, elevated CO2 levels reduce yield losses. The knowledge of the upcoming climate changes together with the prediction of the developmental and physiological stomatal responses will allow not only to anticipate maize yield in the next years, but also to contribute to the correct decision-making in the management of this important crop.

Impacts of mean climate and extreme climate indices on soybean yield and yield components in Northeast China

Soybean is an important oil crop in China, and the national focus of soybean production is in Northeast China. In order to achieve high-stable yield, it is crucial to acknowledge the impacts of mean climate and extreme climate indices on soybean yield and yield components. In this study, based on the weather data from 61 counties from 1981 to 2017 in Northeast China, we assessed the impacts of mean climate and extreme climate indices on soybean observed yield and simulated yield. Mean climate include effective growing degree days (GDD10), precipitation (Pre), and solar radiation (SR); extreme climate indices include the number of cool days during seed-filling period (C15), the number of cool days during 15 days before anthesis (C17), the number of hot days (H30), maximum amount of 5 Day accumulated precipitation (P5), and consecutive dry days (CDD)). We used the DSSAT-CROPGRO-Soybean model to identify the main yield components for soybean. The results showed that observed soybean yield reduced by 3.57% due to the collective changes in the eight study climate indices. Increases in GDD10, decreases in Pre, and decreases in SR caused a 3.96%, -3.89%, and - 0.48% change in soybean yield, respectively. Decreases in C15 and C17 led to a 5.36% increase in soybean yield; increases in H30, P5, and CDD caused a 5.75%, 0.30%, and 1.14% reduction in soybean yield, respectively. By comparing the response of observed and simulated soybean yield to climate indices (excluding P5) in the DSSAT-CROPGRO-Soybean model, we identified the key yield components for soybean as the number of pods and seed weight. The negative impacts on the number of pods and seed weight were mainly attributed to changes in Pre and H30 from anthesis to podding and during seed-filling period. Our results could be used to assist the local soybean community adapt to climate change.

Amand P, Bai G, Nakata PA, Rieu I, Jackson DP, Cheng N, Valent B, Hirschi KD, Jagadish SVK, Liu S, White FF, Park S. Redox-engineering enhances maize thermotolerance and grain yield in the field

Increasing populations and temperatures are expected to escalate food demands beyond production capacities, and the development of maize lines with better performance under heat stress is desirable. Here, we report that constitutive ectopic expression of a heterologous glutaredoxin S17 from Arabidopsis thaliana (AtGRXS17) can provide thermotolerance in maize through enhanced chaperone activity and modulation of heat stress-associated gene expression. The thermotolerant maize lines had increased protection against protein damage and yielded a sixfold increase in grain production in comparison to the non-transgenic counterparts under heat stress field conditions. The maize lines also displayed thermotolerance in the reproductive stages, resulting in improved pollen germination and the higher fidelity of fertilized ovules under heat stress conditions. Our results present a robust and simple strategy for meeting rising yield demands in maize and, possibly, other crop species in a warming global environment.

More accurate specification of water supply shows its importance for global crop production

Warming temperatures tend to damage crop yields, yet the influence of water supply on global yields and its relation to temperature stress remains unclear. Here we use satellite-based measurements to provide empirical estimates of how root zone soil moisture and surface air temperature jointly influence the global productivity of maize, soybeans, millet and sorghum. Relative to empirical models using precipitation as a proxy for water supply, we find that models using soil moisture explain 30-120% more of the interannual yield variation across crops. Models using soil moisture also better separate water-supply stress from correlated heat stress and show that soil moisture and temperature contribute roughly equally to historical variations in yield. Globally, our models project yield damages of -9% to -32% across crops by end-of-century under Shared Socioeconomic Pathway 5-8.5 from changes in temperature and soil moisture. By contrast, projections using temperature and precipitation overestimate damages by 28% to 320% across crops both because they confound stresses from dryness and heat and because changes in soil moisture and temperature diverge from their historical association due to climate change. Our results demonstrate the importance of accurately representing water supply for predicting changes in global agricultural productivity and for designing effective adaptation strategies.

Climate Change Impact on Yield and Water Use of Rice-Wheat Rotation System in the Huang-Huai-Hai Plain, China

Global climate change has had a significant impact on crop production and agricultural water use. Investigating different future climate scenarios and their possible impacts on crop production and water consumption is critical for proposing effective responses to climate change. In this study, based on daily downscaled climate data from 22 Global Climate Models (GCMs) provided by Coupled Model Intercomparison Project Phase 6 (CMIP6), we applied the well-validated Agricultural Production Systems sIMulator (APSIM) to simulate crop phenology, yield, and water use of the rice-wheat rotation at four representative stations (including Hefei and Shouxian stations in Anhui province and Kunshan and Xuzhou stations in Jiangsu province) across the Huang-Huai-Hai Plain, China during the 2041-2070 period (2050s) under four Shared Socioeconomic Pathways (i.e., SSP126, SSP245, SSP370, and SSP585). The results showed a significant increase in annual mean temperature (Temp) and solar radiation (Rad), and annual total precipitation (Prec) at four investigated stations, except Rad under SSP370. Climate change mainly leads to a consistent advance in wheat phenology, but inconsistent trends in rice phenology across four stations. Moreover, the reproductive growth period (RGP) of wheat was prolonged while that of rice was shorted at three of four stations. Both rice and wheat yields were negatively correlated with Temp, but positively correlated with Rad, Prec, and CO2 concentration ([CO2]). However, crop ET was positively correlated with Rad, but negatively correlated with [CO2], as elevated [CO2] decreased stomatal conductance. Moreover, the water use efficiency (WUE) of rice and wheat was negatively correlated with Temp, but positively correlated with [CO2]. Overall, our study indicated that the change in Temp, Rad, Prec, and [CO2] have different impacts on different crops and at different stations. Therefore, in the impact assessment for climate change, it is necessary to explore and analyze different crops in different regions. Additionally, our study helps to improve understanding of the impacts of climate change on crop production and water consumption and provides data support for the sustainable development of agriculture.

Variability in Crop Response to Spatiotemporal Variation in Climate in China, 1980–2014

As the population increases and climate extremes become more frequent, the pressure on food supply increases. A better understanding of the influence of climate variations on crop yield in China would be of great benefit to global food security. In this study, gridded, daily meteorological data and county-level annual yield data were used to quantify the climate sensitivity of corn, rice, and spring wheat yields, and identify the spatiotemporal variation relationship between climate and yields from 1980 to 2014. The results showed that rice and corn were more sensitive to climate variations than spring wheat, both spatially and temporally. Photosynthetic active radiation (PAR) was found to be beneficial to rice in northeast China and the Yangtze River basin, as well as corn in the south and spring wheat in Xinjiang, but not to rice in the south of the Yangtze River and spring wheat in the southeast coast. The temperature centroid shift was the main driving factor causing the movement of the centroid of the three crops. For every 1 km shift of the temperature centroid, the corn and rice yield centroids moved 0.97 km and 0.34 km, respectively. These findings improve our understanding of the impacts of climate variations on agricultural yields in different regions of China.

Seasonal Variations in Grain Yield, Greenhouse Gas Emissions and Carbon Sequestration for Maize Cultivation in Bangladesh

Rationale: Greenhouse gas (GHG) emissions from crop agriculture are of great concern in the context of changing climatic conditions; however, in most cases, data based on lifecycle assessments are not available for grain yield variations or the carbon footprint of maize. The current study aimed to determine net carbon emissions and sequestration for maize grown in Bangladesh. Methods: The static closed-chamber technique was used to determine total GHG emissions using data on GHG emissions from maize fields and secondary sources for inputs. A secondary source for regional yield data was used in the current study. GHG emission intensity is defined as the ratio of total emissions to grain yield. The net GHG emission/carbon sequestration was determined by subtracting total GHG emissions (CO2 eq.) from net primary production (NPP). Results: Grain yields varied from 1590 to 9300 kg ha−1 in the wet season and from 680 to 11,820 kg ha−1 in the dry season. GHG emission intensities were 0.53–2.21 and 0.37–1.70 kg CO2 eq. kg−1 grain in the wet and dry seasons, respectively. In Bangladesh, the total estimated GHG emissions were 1.66–4.09 million tonnes (MT) CO2 eq. from 2015 to 2020, whereas the net total CO2 sequestration was 1.51–3.91 MT. The net CO2 sequestration rates were 984.3–5757.4 kg ha−1 in the wet season and 1188.62–5757.39 kg ha−1 in the dry season. This study observed spatial variations in carbon emissions and sequestration depending on growing seasons. In the rice–maize pattern, maize sequestered about 1.23 MT CO2 eq. per year−1, but rice emitted about 0.16 MT CO2 eq. per year−1. This study showed potential spatiotemporal variations in carbon footprints. Recommendation: Special care is needed to improve maize grain yields in the wet season. Fertiliser and water use efficiencies need to be improved to minimise GHG emissions under changing climatic conditions. Efforts to increase the area under cultivation with rice–maize or other non-rice crop-based cropping systems are needed to augment CO2 sequestration. The generation of a regional data bank on carbon footprints would be beneficial for combating the impact of climate change.

Enhanced Weather-Based Index Insurance Design for Hedging Crop Yield Risk

This study proposes an optimization-based weather-yield model to reduce the basis risk of weather-based index insurance. This weather-yield model helps us capture the growing season's monthly variation as it involves monthly explanatory weather indices. In addition, it can capture additional extreme weather effects by including extreme cooling or heating weather indices. This study presents an innovative machine learning framework incorporating optimization approaches to ensure the parsimony of weather index models and the accuracy of crop yield predictions, which can be integrated into the conventional policy design and pricing process. The advantages of this modeling approach and the effectiveness of weather index-based insurance based on this approach in reducing basis risk and revenue risk are demonstrated by applying county-level yield data for mid-season rice in the Anhui province, China.

Interannual variability of heat waves over the Korean Peninsula based on integrated approach

Heat waves can provide detrimental impacts on human society and the environmental system, and thus have received substantial attention in scientific research. Since heat waves are relevant to a wide range of stakeholders, definitions for heat wave events vary in terms of threshold values, durations, and utilized variables. While there is a value in this diversity of perspectives, the various definitions often complicate the assessment of heat wave risk, thereby underscoring the improved utility of a unified definition. In this study, we examine the interannual variability of heat wave patterns by using a proposed copula-based framework. From five observed temperature-related variables, this study first evaluates the individual changes of fifteen previously published heat wave indices focused on heat wave events across the Korean Peninsula for the last 49 years (1973-2021). We then extract the integrated signals to understand the overall trend patterns using the multiple heat wave indices. Results indicate that different heat wave definitions present distinctive attributes (e.g., in the magnitude of temporal changes) depending on the locations, implying that the diversity of heat wave definitions leads to potentially inconsistent conclusions. Using the integrated analysis, we identify that the expected heat wave day has increased across the majority of the regions in the Korean Peninsula. To be specific, substantial increases are shown in North Korea, while rapid increases in heat wave events have been observed after the year 2010 over South Korea. Finally, through the sensitivity analysis, we demonstrate the importance of choosing the heat wave definition in the integrated analysis.

Climate Change and Management Impacts on Soybean N Fixation, Soil N Mineralization, N2O Emissions, and Seed Yield

Limited knowledge about how nitrogen (N) dynamics are affected by climate change, weather variability, and crop management is a major barrier to improving the productivity and environmental performance of soybean-based cropping systems. To fill this knowledge gap, we created a systems understanding of agroecosystem N dynamics and quantified the impact of controllable (management) and uncontrollable (weather, climate) factors on N fluxes and soybean yields. We performed a simulation experiment across 10 soybean production environments in the United States using the Agricultural Production Systems sIMulator (APSIM) model and future climate projections from five global circulation models. Climate change (2020-2080) increased N mineralization (24%) and N₂O emissions (19%) but decreased N fixation (32%), seed N (20%), and yields (19%). Soil and crop management practices altered N fluxes at a similar magnitude as climate change but in many different directions, revealing opportunities to improve soybean systems' performance. Among many practices explored, we identified two solutions with great potential: improved residue management (short-term) and water management (long-term). Inter-annual weather variability and management practices affected soybean yield less than N fluxes, which creates opportunities to manage N fluxes without compromising yields, especially in regions with adequate to excess soil moisture. This work provides actionable results (tradeoffs, synergies, directions) to inform decision-making for adapting crop management in a changing climate to improve soybean production systems.

Rapid Identification of Pollen- and Anther-Specific Genes in Response to High-Temperature Stress Based on Transcriptome Profiling Analysis in Cotton

Anther indehiscence and pollen sterility caused by high temperature (HT) stress have become a major problem that decreases the yield of cotton. Pollen- and anther-specific genes play a critical role in the process of male reproduction and the response to HT stress. In order to identify pollen-specific genes that respond to HT stress, a comparative transcriptome profiling analysis was performed in the pollen and anthers of Gossypium hirsutum HT-sensitive Line H05 against other tissue types under normal temperature (NT) conditions, and the analysis of a differentially expressed gene was conducted in the pollen of H05 under NT and HT conditions. In total, we identified 1111 pollen-specific genes (PSGs), 1066 anther-specific genes (ASGs), and 833 pollen differentially expressed genes (DEGs). Moreover, we found that the late stage of anther included more anther- and pollen-specific genes (APSGs). Stress-related cis-regulatory elements (CREs) and hormone-responsive CREs are enriched in the promoters of APSGs, suggesting that APSGs may respond to HT stress. However, 833 pollen DEGs had only 10 common genes with 1111 PSGs, indicating that PSGs are mainly involved in the processes of pollen development and do not respond to HT stress. Promoters of these 10 common genes are enriched for stress-related CREs and MeJA-responsive CREs, suggesting that these 10 common genes are involved in the process of pollen development while responding to HT stress. This study provides a pathway for rapidly identifying cotton pollen-specific genes that respond to HT stress.

Water in the West: Trends, production efficiency, and a call for open data

Climate change is projected to transform US agriculture, particularly in places reliant on limited irrigation water resources. As water demand and scarcity increase simultaneously over the coming decades, water managers and growers will need to optimize water use on their irrigated lands. Understanding how growers maintain high yields in arid, water stressed places, while conserving water, is of key importance for the future of US agriculture in the West. We explore water use management and trends in irrigated agriculture in the Western US using operator-level USDA-NASS Farm and Ranch Irrigation Survey/Irrigation and Water Management Survey data aggregated for the first time to the county-scale. In this exploration, we build the first county-level, openly accessible dataset linking farm(er) characteristics to irrigation behaviors in the West. We find notable spatial and temporal variability in Western irrigation practices, with neighboring counties exhibiting large differences in efficiency, water use, and crop yields, as well as in the sources of information, scheduling methods, and technological improvements employed. To produce effective management initiatives in the West, we call for the express and open dissemination of USDA irrigation data at sub-state scales. These data will contribute to our understanding of irrigated production and could support a pathway that will prepare growers for a more resilient agricultural future.

Ethylene involvement in the regulation of heat stress tolerance in plants

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

Interplay between Ca2+/Calmodulin-Mediated Signaling and AtSR1/CAMTA3 during Increased Temperature Resulting in Compromised Immune Response in Plants

Changing temperatures are known to affect plant–microbe interactions; however, the molecular mechanism involved in plant disease resistance is not well understood. Here, we report the effects of a moderate change in temperature on plant immune response through Ca²⁺/calmodulin-mediated signaling. At 30 °C, Pst DC3000 triggered significantly weak and relatively slow Ca²⁺ influx in plant cells, as compared to that at 18 °C. Increased temperature contributed to an enhanced disease susceptibility in plants; the enhanced disease susceptibility is the result of the compromised stomatal closure induced by pathogens at high temperature. A Ca²⁺ receptor, AtSR1, contributes to the decreased plant immunity at high temperatures and the calmodulin-binding domain (CaMBD) is required for its function. Furthermore, both salicylic acid biosynthesis (ICS) and salicylic acid receptor (NPR1) are involved in this process. In addition to stomatal control, AtSR1 is involved in high temperature-compromised apoplastic immune response through the salicylic acid signaling pathway. The qRT-PCR data revealed that AtSR1 contributed to increased temperatures-mediated susceptible immune response by regulating SA-related genes in atsr1, such as PR1, ICS1, NPR1, as well as EDS1. Our results indicate that Ca²⁺ signaling has broad effects on the molecular interplay between changing temperatures as well as plant defense during plant–pathogen interactions.

Data Driven Explanation of Temporal and Spatial Variability of Maize Yield in the United States

Maize yield has demonstrated significant variability both temporally and spatially. Numerous models have been presented to explain such variability in crop yield using data from multiple sources with varying temporal and spatial resolutions. Some of these models are data driven, which focus on approximating the complex relationship between explanatory variables and crop yield from massive data sets. Others are knowledge driven, which focus on integrating scientific understanding of crop growth mechanism in the modeling structure. We propose a new model that leverages the computational efficiency and prediction accuracy of data driven models and incorporates agronomic insights from knowledge driven models. Referred to as the GEM model, this model estimates three independent components of (G)enetics, (E)nvironment, and (M)anagement, the product of which is used as the predicted crop yield. The aim of this study is to produce not only accurate crop yield predictions but also insightful explanations of temporal and spatial variability with respect to weather, soil, and management variables. Computational experiments were conducted on a data set that includes maize yield, weather, soil, and management data covering 2,649 counties in the U.S. from 1980 to 2019. Results suggested that the GEM model is able to achieve a comparable prediction performance with state-of-the-art machine learning models and produce meaningful insights such as the estimated growth potential, effectiveness of management practices, and genetic progress.

Silicon-mediated heat tolerance in higher plants: A mechanistic outlook

Heat stress, resulting from global warming, is considered one of the major challenges to be addressed for increasing plant survival and productivity worldwide. Although plants have a built-in defense mechanism against heat stress, such strategy seems to be insufficient to counteract heat adversities under extreme temperature regimes. Hence, increasing heat tolerance in plants for sustainable yields is one of the biggest challenges for researchers in the coming decades. Conventional plant breeding approach to enhance heat tolerance has gained some successes; however, more efforts are needed to make plants resilient to heat stress for increasing crop production during ongoing climate change. Thus, exploring 'heat stress mitigation strategies' using cost-effective and eco-friendly approaches may be quick and sustainable alternatives. The use of silicon (Si) and Si-nanoparticles (Si-NPs) in enhancing heat tolerance in plants has recently gained much attention. Application of Si and Si-NPs can assist plants to overcome heat-induced oxidative stress through the acceleration of reactive oxygen species detoxification by modulating the antioxidant systems and regulating transcription of key genes associated with heat stress responses. In fact, molecular rationale behind Si-mediated heat tolerance in plants is largely unknown. In this minireview, we made efforts to understand the mechanistic aspects of heat-induced responses and damages in plants, and possible molecular dynamics of Si-induced heat tolerance in plants. We also highlighted recent advances on how Si induces heat tolerance potential in plants and future perspectives on how Si can contribute to sustainable crop production under the increasing threat of global climate change.

Stronger temperature-moisture couplings exacerbate the impact of climate warming on global crop yields

Rising air temperatures are a leading risk to global crop production. Recent research has emphasized the critical role of moisture availability in regulating crop responses to heat and the importance of temperature-moisture couplings in driving concurrent heat and drought. Here, we demonstrate that the heat sensitivity of key global crops depends on the local strength of couplings between temperature and moisture in the climate system. Over 1970-2013, maize and soy yields dropped more during hotter growing seasons in places where decreased precipitation and evapotranspiration more strongly accompanied higher temperatures, suggestive of compound heat-drought impacts on crops. On the basis of this historical pattern and a suite of climate model projections, we show that changes in temperature-moisture couplings in response to warming could enhance the heat sensitivity of these crops as temperatures rise, worsening the impact of warming by -5% (-17 to 11% across climate models) on global average. However, these changes will benefit crops where couplings weaken, including much of Asia, and projected impacts are highly uncertain in some regions. Our results demonstrate that climate change will impact crops not only through warming but also through changing drivers of compound heat-moisture stresses, which may alter the sensitivity of crop yields to heat as warming proceeds. Robust adaptation of cropping systems will need to consider this underappreciated risk to food production from climate change.

A combination of genome-wide and transcriptome-wide association studies reveals genetic elements leading to male sterility during high temperature stress in cotton

Global warming has reduced the productivity of many field-grown crops, as the effects of high temperatures can lead to male sterility in such plants. Genetic regulation of the high temperature (HT) response in the major crop cotton is poorly understood. We determined the functionality and transcriptomes of the anthers of 218 cotton accessions grown under HT stress. By analyzing transcriptome divergence and implementing a genome-wide association study (GWAS), we identified three thermal tolerance associated loci which contained 75 protein coding genes and 27 long noncoding RNAs, and provided expression quantitative trait loci (eQTLs) for 13 132 transcripts. A transcriptome-wide association study (TWAS) confirmed six causal elements for the HT response (three genes overlapped with the GWAS results) which are involved in protein kinase activity. The most susceptible gene, GhHRK1, was confirmed to be a previously uncharacterized negative regulator of the HT response in both cotton and Arabidopsis. These functional variants provide a new understanding of the genetic basis for HT tolerance in male reproductive organs.