The compound effects of drought and high temperature stresses will be the main constraints on maize yield in Northeast China

Cotton under heat stress: a comprehensive review of molecular breeding, genomics, and multi-omics strategies

Cotton is a vital fiber crop for the global textile industry, but rising temperatures due to climate change threaten its growth, fiber quality and yields. Heat stress disrupts key physiological and biochemical processes, affecting carbohydrate metabolism, hormone signaling, calcium and gene regulation and expression. This review article explores cotton's defense mechanism against heat stress, including epigenetic regulations and transgenic approaches, with a focus on genome editing tools. Given the limitations of traditional breeding, advanced omics technologies such as GWAS, transcriptomics, proteomics, ionomics, metabolomics, phenomics and CRISPR-Cas9 offer promising solutions for developing heat-resistant cotton varieties. This review highlights the need for innovative strategies to ensure sustainable cotton production under climate change.

A Maize Calmodulin-like 3 Gene Positively Regulates Drought Tolerance in Maize and Arabidopsis

Drought stress is one of the important abiotic stresses that affects maize production. As an important Ca2+ sensor, calmodulin-like proteins (CMLs) play key roles in plant growth, development, and stress response, but there are a limited number of studies regarding CMLs in response to drought stress. In this study, a Calmodulin-like gene, namely ZmCML3, was isolated from maize (Zea mays L.). The coding sequence (CDS) of ZmCML3 was 474 bp and a protein of 158 aa which contains three EF-hand motifs. ZmCML3 was localized within the nucleus and plasma membrane. The expression of ZmCML3 was induced by polyethylene glycol (PEG) 6000, NaCl, methyl jasmonate (MeJA), and abscisic acid (ABA). Overexpression of ZmCML3 resulted in enhanced drought tolerance in maize through increasing proline (Pro) content and the activity of peroxide (POD) and superoxide dismutase (SOD). Meanwhile, ZmCML3 also positively regulated the expression of drought stress-responsive genes in maize under drought stress treatment. Taken together, ZmCML3 acts as a positive regulator in maize response to drought stress. These results will provide theoretical basis for breeding drought tolerance maize variety.

Assessing the role of genotype by environment interaction as determinants of maize grain yield and lodging resistance

BACKGROUND

The development of superior summer maize hybrids with high-yield potential and essential agronomic traits, such as resistance to lodging, is crucial for ensuring the sustainability of maize cultivation. However, the task of identifying and breeding genotypes that exhibit exceptional performance and stability across multiple environment conditions, while considering a wide range of traits, is challenging. Given the backdrop of global climate change, understanding which climate variables and soil properties most significantly impact environmental similarity is essential for selecting hybrids with improved adaptability to regions with diverse climatic and soil conditions. This study aimed to integrate envirotyping techniques (ETs) with a multi-trait selection approach to carry out a comprehensive evaluation of maize genotypes for performance and stability.

RESULTS

The grain yields of 13 maize hybrids, along with their four critical agronomic parameters, were assessed in the Huang-Huai-Hai Plain of China across 40 locations in eight provinces. By considering 20 years of climatic factors and soil covariates, these 40 locations were divided into six mega-environments (MEs) based on similar long-term weather patterns and soil characteristics. Additive main effects and multiplicative interaction (AMMI) analyses revealed that genotype (G), environment (E), and the GxE interaction had significant effects on all agronomic parameters (P < 0.001). The mean performance and stability of the genotypes in each mega-environment were assessed, allowing for the identification of superior hybrids using the multi-trait stability index (MTSI). In two of the MEs (ME2 and ME3), only two hybrids, HY321 and HY9112, were selected concurrently.

CONCLUSION

Overall, this study provides valuable insights into the effects of ETs on maize hybrids and enhances our understanding of GxE interactions in multi-environment trials. This understanding is essential for improving maize cultivation practices and breeding program in diverse environments.

Real-time hazard assessment of maize based on the chilling injury process -- Using a standard curve to establish a daily cumulative assessment method

Cold damage caused by low temperatures is known as chilling injury (CI), and it has consistently been one of the primary meteorological disasters affecting maize. With ongoing global climate change, the issue of chilling injury is becoming more prominent, exhibiting new characteristics and presenting new challenges. Consequently, understanding the disaster process and conducting a more refined real-time chilling injury identification have become significant challenges. In this study, we divided maize planting areas into seven maturity types based on the accumulated temperature, constructed a standard curve of the daily accumulated temperature from 1991 to 2020, proposed real-time identification indicators based on the CI process, and developed a real-time CI hazard assessment model. The results indicated that the model can capture independent CI events and rapidly determine the location, intensity, duration and scope of CIs, thereby providing a basis for accurately understanding the impact of chilling injury and taking timely countermeasures. The combination of accumulated temperature standard curves for seven maturity types of maize and the CI curve was used to construct the CI daily scale identification indicator, ΔEAT. Judgment thresholds for the CI identification indicators at various maturity levels were obtained by correlating them with historical disaster data. The frequency and intensity of maize CI gradually increased from the extremely late-maturing zone to the extremely early-maturing zone, with the seeding and emergence periods being the peak periods for CI. The spatiotemporal evolution characteristics of the three different degrees of CI events in 1992, 2004, and 2017 were consistent with the historical disaster records. Northeastern Inner Mongolia and most of Heilongjiang were found to be high-hazard areas for maize CIs. The constructed daily CI identification indicators can accurately and rapidly identify maize CIs, providing practical and targeted guidance for combating these injuries.

Spatiotemporal variations and driving factors of crop productivity in China from 2001 to 2020

Human activities have altered the quantity and distribution of cropland, and climate change profoundly affects crop productivity. However, the spatiotemporal patterns and driving mechanisms of crop productivity remain unclear. Here, we analyze the spatiotemporal evolution of Chinese crop productivity using long-term satellite observation data. We employ the residual trend analysis method to separate the relative contributions of climate change and non-climate factors to crop productivity. Our results indicate the following: (1) from 2001 to 2020, China's crop productivity increased by approximately 0.11 kgCm-2yr-1, which compensated for the decline in crop yields caused by a reduction in cropland area. (2) Crop productivity exhibits significant spatial heterogeneity, with notable differences between the southern and northern regions of China. Both cropland and crop productivity show a northward shift, with the migration distance of the mean center of crop productivity exceeding that of cropland. (3) Agricultural production inputs are closely related to crop productivity, but climate change remains the primary factor influencing changes in Chinese crop productivity. Crop productivity in northern China is more sensitive to climate change, and the dominant factors vary among different agricultural districts. (4) Over the study period, long-term crop cultivation in northern China has benefited the net primary productivity of surface vegetation, though the sustainability of production faces challenges. This study is of great importance for maintaining food security and promoting sustainable agricultural development, offering guidance for cross-regional cropland compensation.

Geographical Distribution Dynamics of Acorus calamus in China Under Climate Change

Acorus calamus, a perennial emergent herb, is highly valued for its ornamental appeal, water purification ability, and medicinal properties. However, there is a significant contradiction between the rapidly increasing demand for A. calamus and the diminishing wild resources. Understanding its geographical distribution and the influence of global climate change on its geographical distribution is imperative for establishing a theoretical framework for the conservation of natural resources and the expansion of its cultivation. In this study, 266 distribution records of A. calamus and 18 selected key environmental factors were utilized to construct an optimal MaxEnt model via the ENMeval package. We simulated the potential geographical distributions under current conditions and under three different climate scenarios (SSP126, SSP370, and SSP585) in the 2050s, 2070s, and 2090s. Additionally, we employed the jackknife method and response curves to identify the environmental factors with the greatest influence on the distribution of A. calamus, and their response intervals. The results indicate that the regularization multiplier (RM) of 3.5 and the feature combinations (FC) of linear (L), quadratic (Q), hinge (H), and product (P) are the optimal model parameter combinations. With these parameters, the model predictions are highly accurate, and the consistency of the results is significant. The dominant environmental factors and their thresholds affecting the distribution of A. calamus are the precipitation of the wettest month (≥109.87 mm), human footprint (≥5.39), annual precipitation (≥388.56 mm), and mean diurnal range (≤12.83 °C). The primary land use types include rivers and channels, reservoirs and ponds, lakes, urban areas, marshes, other constructed lands, rice fields, forested areas, and shrublands. Under current climate conditions, the suitable geographical distribution of A. calamus in China is clearly located east of the 400 mm precipitation line, with high- and low-suitability areas covering 121.12 × 104 km2, and 164.20 × 104 km2, respectively. Under future climate conditions, both high- and low- suitability areas are projected to increase significantly, whereas unsuitable areas are expected to decrease, with the centroid of each suitability zone shifting northward. This study provides a theoretical foundation for sustainable utilization, future production planning, and the development of conservation strategies for wild germplasm resources of A. calamus.

Dynamic evolution characteristics and hazard assessment of compound drought/waterlogging and low temperature events for maize

Hazard assessment is fundamental in the field of disaster risk management. With the increase in global warming, compound water and temperature events have become more frequent. Current research lacks risk assessments of low temperatures and their compound events, necessitating relevant hazard assessment work to improve the accuracy and diversity of maize disaster prevention and mitigation strategies. This study comparatively analyzed the dynamic evolution characteristics and hazards of compound drought/waterlogging and low temperature events (CDLEs and CWLEs) for maize in the Songliao Plain during different growth periods from 1981 to 2020. First, composite drought/waterlogging and low temperature magnitude indices (CDLMI and CWLMI) were constructed to quantify the intensity of CDLEs and CWLEs by fitting non-exceedance probabilities. Next, static and dynamic hazard assessment models were developed by fitting probability density and cumulative probability density curves to CDLMI and CWLMI. The results showed that the correlations between SPRI and LTI across different decades were mainly negative during the three growth periods. The hazard ratings for both CDLEs and CWLEs were relatively high in the northern part of the study area, consistent with the higher occurrence, duration, and severity of both CDLEs and CWLEs at higher latitudes. Relative to 2001-2010, the center of gravity of hazard shifted southward for CDLEs and northward for CWLEs in 2011-2020. The mean duration, frequency, and hazard were generally higher for CWLEs, but CDLEs were associated with more severe maize yield reductions. This study provides new insights into compound disaster risk assessment, and the research methodology can be generalized to other agricultural growing areas to promote sustainable development of agricultural systems and food security.

Reduced actual vapor pressure exerts a significant influence on maize yield through vapor pressure deficit amid climate warming

Understanding the impact of climate warming on crop yield and its associated mechanisms is paramount for ensuring food security. Here, we conduct a thorough analysis of the impact of vapor pressure deficit (VPD) on maize yield, leveraging a rich dataset comprising temporal and spatial observations spanning 40 years across 31 maize-growing locations in Northeast and North China. Our investigation extends to the influencing meteorological factors that drive changes in VPD during the maize growing phase. Regression analysis reveals a linear negative relationship between VPD and maize yield, demonstrating diverse spatiotemporal characteristics. Spatially, maize yield exhibits higher sensitivity to VPD in Northeast China (NEC), despite the higher VPD levels in North China Plain (NCP). The opposite patterns reveal that high VPD not invariably lead to detrimental yield impacts. Temporal analysis sheds light on an upward trend in VPD, with values of 0.05 and 0.02 kPa/10yr, accompanied by significant abrupt changes around 1996 in NEC and 2006 in NCP, respectively. These temporal shifts contribute to the heightened sensitivity of maize yield in both regions. Importantly, we emphasize the need to pay closer attention to the substantial the impact of actual vapor pressure on abrupt VPD changes during the maize growing phase, particularly in the context of ongoing climate warming.

TrG2P: A transfer-learning-based tool integrating multi-trait data for accurate prediction of crop yield

Yield prediction is the primary goal of genomic selection (GS)-assisted crop breeding. Because yield is a complex quantitative trait, making predictions from genotypic data is challenging. Transfer learning can produce an effective model for a target task by leveraging knowledge from a different, but related, source domain and is considered a great potential method for improving yield prediction by integrating multi-trait data. However, it has not previously been applied to genotype-to-phenotype prediction owing to the lack of an efficient implementation framework. We therefore developed TrG2P, a transfer-learning-based framework. TrG2P first employs convolutional neural networks (CNN) to train models using non-yield-trait phenotypic and genotypic data, thus obtaining pre-trained models. Subsequently, the convolutional layer parameters from these pre-trained models are transferred to the yield prediction task, and the fully connected layers are retrained, thus obtaining fine-tuned models. Finally, the convolutional layer and the first fully connected layer of the fine-tuned models are fused, and the last fully connected layer is trained to enhance prediction performance. We applied TrG2P to five sets of genotypic and phenotypic data from maize (Zea mays), rice (Oryza sativa), and wheat (Triticum aestivum) and compared its model precision to that of seven other popular GS tools: ridge regression best linear unbiased prediction (rrBLUP), random forest, support vector regression, light gradient boosting machine (LightGBM), CNN, DeepGS, and deep neural network for genomic prediction (DNNGP). TrG2P improved the accuracy of yield prediction by 39.9%, 6.8%, and 1.8% in rice, maize, and wheat, respectively, compared with predictions generated by the best-performing comparison model. Our work therefore demonstrates that transfer learning is an effective strategy for improving yield prediction by integrating information from non-yield-trait data. We attribute its enhanced prediction accuracy to the valuable information available from traits associated with yield and to training dataset augmentation. The Python implementation of TrG2P is available at https://github.com/lijinlong1991/TrG2P. The web-based tool is available at http://trg2p.ebreed.cn:81.

Future climate projection across Tanzania under CMIP6 with high-resolution regional climate model

Climate change is one of the most pressing challenges faced by developing countries due to their lower adaptive capacity, with far-reaching impacts on agriculture. The mid-century period is widely regarded as a critical moment, during which adaptation is deemed essential to mitigating the associated impacts. This study presents future climate projections across Tanzania using the latest generation of global climate models (CMIP6) combined with a high-resolution regional climate model. The findings indicate that, the trends in temperature and precipitation in Tanzania from 1991 to 2020, minimum temperatures showed the highest variability with a trend of 0.3 °C, indicating significant fluctuations in minimum temperature over the decades. Maximum temperatures also showed high variability with a trend of 0.4 °C. There is a range of variability in precipitation per decade for different regions in Tanzania, with some regions experiencing significant decreases in precipitation of up to - 90.3 mm and - 127.6 mm. However, there were also regions that experienced increases in precipitation, although these increases were generally less than 4.8 mm over the decades. The projections of minimum and maximum temperatures from 2040 to 2071 under the Shared Socioeconomic Pathways (SSP) 2-4.5 and SSP 5-8.5 are projected to increase by 0.14 °C to 0.21 °C per decade, across different regions. The average projected precipitation changes per decade vary across regions. Some regions are projected to experience increases in precipitation. Other regions are projected to show decreases in precipitation within the range of - 0.6 mm to 15.5 mm and - 1.5 mm to 47.4 mm under SSP2-4.5 and SSP5-8.5 respectively. Overall, both scenarios show an increase in projected temperatures and precipitation for most regions in Tanzania, with some areas experiencing more significant increases compared to others. The changes in temperatures and precipitation are expected to have significant impacts on agriculture and water resources in Tanzania.

Mesophyll conductance limits photosynthesis in fluctuating light under combined drought and heat stresses

Drought and heat stresses usually occur concomitantly in nature, with increasing frequency and intensity of both stresses expected due to climate change. The synergistic agricultural impacts of these compound climate extremes are much greater than those of the individual stresses. However, the mechanisms by which drought and heat stresses separately and concomitantly affect dynamic photosynthesis have not been thoroughly assessed. To elucidate this, we used tomato (Solanum lycopersicum) seedlings to measure dynamic photosynthesis under individual and compound stresses of drought and heat. Individual drought and heat stresses limited dynamic photosynthesis at the stages of diffusional conductance to CO2 and biochemistry, respectively. However, the primary limiting factor for photosynthesis shifted to mesophyll conductance under the compound stresses. Compared with the control, photosynthetic carbon gain in fluctuating light decreased by 38%, 73%, and 114% under the individual drought, heat, and compound stresses, respectively. Therefore, compound stresses caused a greater reduction in photosynthetic carbon gain in fluctuating light conditions than individual stress. These findings highlight the importance of mitigating the effects of compound climate extremes on crop productivity by targeting mesophyll conductance and improving dynamic photosynthesis.

Biofilms formation in plant growth-promoting bacteria for alleviating agro-environmental stress

Biofilm formation represents a pivotal and adaptable trait among microorganisms within natural environments. This attribute plays a multifaceted role across diverse contexts, including environmental, aquatic, industrial, and medical systems. While previous research has primarily focused on the adverse impacts of biofilms, harnessing their potential effectively could confer substantial advantages to humanity. In the face of escalating environmental pressures (e.g., drought, salinity, extreme temperatures, and heavy metal pollution), which jeopardize global crop yields, enhancing crop stress tolerance becomes a paramount endeavor for restoring sufficient food production. Recently, biofilm-forming plant growth-promoting bacteria (PGPB) have emerged as promising candidates for agricultural application. These biofilms are evidence of microorganism colonization on plant roots. Their remarkable stress resilience empowers crops to thrive and yield even in harsh conditions. This is accomplished through increased root colonization, improved soil properties, and the synthesis of valuable secondary metabolites (e.g., ACC deaminase, acetin, 2,3-butanediol, proline, etc.). This article elucidates the mechanisms underpinning the role of biofilm-forming PGPB in bolstering plant growth amidst environmental challenges. Furthermore, it explores the tangible applications of these biofilms in agriculture and delves into strategies for manipulating biofilm formation to extract maximal benefits in practical crop production scenarios.

The heat stress during anthesis and the grain-filling period of spring maize in Northeast China is projected to increase toward the mid-21st century

BACKGROUND

Against the background of global warming, heat stress has become more frequent, which adversely affects the growth and development of spring maize plants in Northeast China. To adapt the regional maize production to climate change, it is imperative to understand the spatio-temporal characteristics of heat stress. In the present study, we analyzed three of the indices for heat stress, including the number of heat stress days, heating degree days (HDD, the total heat degree-days during critical stages), and the percentage of stations with heat stress.

RESULTS

From 1981 to 2019, the number of heat stress days varied greatly among the study years, ranging from 0 to 14 and 27 days, respectively. The average HDD was 7.8 and 5.0 °C day from 1981 to 2000, respectively, and the main hot-spots of heat stress occurred in the southwest regions. Moreover, compared with 1981-2000, the region of HDD during anthesis higher than 10 °C day in 2041-2060 under the SSP1-2.6 and SSP5-8.5 climate scenarios increased by 9.1-50.1% and 0.1-28.6%. The average HDD during the critical stages from 2041 to 2060 increased under the SSP5-8.5 climate scenario, being 1.5 times higher than that during 1981-2000. HDD during maize anthesis and the grain-filling period showed an overall increasing trend with years. About 19% and 58% of the study locations showed heat stress during the past 39 years, respectively.

CONCLUSION

Heat stress during anthesis and the grain-filling period for spring maize in Northeast China is projected to increase toward the mid-21st century. © 2023 Society of Chemical Industry.

Morphological and physio-biochemical responses under heat stress in cotton: Overview

Cotton is an important cash crop in addition to being a fiber commodity, and it plays an essential part in the economies of numerous nations. High temperature is the most critical element affecting its yield from fertilization to harvest. The optimal temperature for root formation is 30 C -35 °C; however, root development ends around 40 °C. Increased temperature, in particular, influences different biochemical and physiological processes associated with cotton plant, resulting in low seed cotton production. Many studies in various agroecological zones used various agronomic strategies and contemporary breeding techniques to reduce heat stress and improve cotton productivity. To attain desired traits, cotton breeders should investigate all potential possibilities, such as generating superior cultivars by traditional breeding, employing molecular techniques and transgenic methods, such as using genome editing techniques. The main objective of this review is to provide the recent information on the environmental factors, such as temperature, heat and drought, influence the growth and development, morphology and physio-chemical alteration associated with cotton. Furthermore, recent advancement in cotton breeding to combat the serious threat of drought and heat stress.

A twenty-year dataset of high-resolution maize distribution in China

China is the world's second-largest maize producer, contributing 23% to global production and playing a crucial role in stabilizing the global maize supply. Therefore, accurately mapping the maize distribution in China is of great significance for regional and global food security and international cereals trade. However, it still lacks a long-term maize distribution dataset with fine spatial resolution, because the existing high spatial resolution satellite datasets suffer from data gaps caused by cloud cover, especially in humid and cloudy regions. This study aimed to produce a long-term, high-resolution maize distribution map for China (China Crop Dataset-Maize, CCD-Maize) identifying maize in 22 provinces and municipalities from 2001 to 2020. The map was produced using a high spatiotemporal resolution fused dataset and a phenology-based method called Time-Weighted Dynamic Time Warping. A validation based on 54,281 field survey samples with a 30-m resolution showed that the average user's accuracy and producer's accuracy of CCD-Maize were 77.32% and 80.98%, respectively, and the overall accuracy was 80.06% over all 22 provinces.

Developing a novel framework to re-examine half a century of compound drought and heatwave events in mainland China

Compound drought and heatwave events (CDHEs) are more devastating than single drought or heatwave events and have gained widespread attention. However, previous studies have not investigated the impacts of the precipitation attenuation effect (PAE) (i.e., the effect of previous precipitation on the dryness and wetness of the current system is attenuated) and event merging (EM) (i.e., merging two CDHEs with short intervals into a single event). Moreover, few studies have assessed short-term CDHEs within monthly scales and their variation characteristics under different background temperatures. Here we propose a novel framework for assessing CDHEs on a daily scale and considering the PAE and EM. We applied this framework to mainland China and investigated the spatiotemporal variation of the CDHE indicators (spatial extent (CDHE_spa), frequency (CDHE_fre), duration (CHHE_dur), and severity (CDHE_sev)) from 1968 to 2019. The results suggested that ignoring the PAE and EM led to significant changes in the spatial distribution and magnitude of the CDHE indicators. Daily-scale assessments allowed for monitoring the detailed evolution of CDHEs and facilitated the timely development of mitigation measures. Mainland China experienced frequent CDHEs from 1968 to 2019 (except for the southwestern part of Northwest China (NWC) and the western part of Southwest China (SWC)), whereas, hotspot areas of CDHE_dur and CDHE_sev had a patchy distribution in different geographical subregions. The CDHE indicators were higher in the warmer 1994-2019 period than in the colder 1968-1993 period, but the rate of increase of the indicators was lower or there was a downward trend. Overall, CDHEs in mainland China have been in a state of remarkable continuous strengthening over the past half a century. This study provides a new quantitative analysis approach for CDHEs.

Application of molecular dynamics simulation for exploring the roles of plant biomolecules in promoting environmental health

Understanding the dynamic changes of plant biomolecules is vital for exploring their mechanisms in the environment. Molecular dynamics (MD) simulation has been widely used to study structural evolution and corresponding properties of plant biomolecules at the microscopic scale. Here, this review (i) outlines structural properties of plant biomolecules, and the crucial role of MD simulation in advancing studies of the biomolecules; (ii) describes the development of MD simulation in plant biomolecules, determinants of simulation, and analysis parameters; (iii) introduces the applications of MD simulation in plant biomolecules, including the response of the biomolecules to multiple stresses, their roles in corrosive environments, and their contributions in improving environmental health; (iv) reviews techniques integrated with MD simulation, such as molecular biology, quantum mechanics, molecular docking, and machine learning modeling, which bridge gaps in MD simulation. Finally, we make suggestions on determination of force field types, investigation of plant biomolecule mechanisms, and use of MD simulation in combination with other techniques. This review provides comprehensive summaries of the mechanisms of plant biomolecules in the environment revealed by MD simulation and validates it as an applicable tool for bridging gaps between macroscopic and microscopic behavior, providing insights into the wide application of MD simulation in plant biomolecules.

Effects of drought stress on water content and biomass distribution in summer maize(Zea mays L.)

The resource allocation of different component organs of crops under drought stress is a strategy for the coordinated growth of crops, which also reflects the adaptability of crops to drought condition. In this study, maize variety namely 'Denghai 618', under the ventilation shed, two treatment groups of light drought (LD) and moderate drought (MD), and the same rehydration after drought are set, as well as the normal water supply for control in shed (CS). The drought experiment was conducted in the jointing-tasseling stage in 2021. The effects of different drought stress on the water content and biomass allocation of each component organ were analyzed. The results showed that (1) during the drought period, the water content of each component organ of summer maize decreased in general, but the Water content distribution ratio (WCDR) of the root increased by 1.83%- 2.35%. The WCDR of stem increased by 0.52%- 1.40%. (2) Under different drought treatments, the root biomass (RB) increased 33.94% ~ 46.09%, and fruit biomass (FB) increased 1.46% ~ 2.49%, the leaf biomass (LB) decreased by 8.2% and 1.46% respectively under LD and MD. (3) The allometric growth model constructed under sufficient water is not suitable for drought stress; the allometric exponent α under drought stress is lower than that of the CS: CS (α=1.175) > MD (α = 1.136) > LD (α = 1.048), which also indicates that the impact of existing climate change on grain yield may be underestimated. This study is helpful to understand the adaptive strategies of the coordinated growth of maize component organs under drought stress and provide a reference for the prediction of grain yield under climate change.

Effects of high air temperature, drought, and both combinations on maize: A case study

High air temperature (HAT) and natural soil drought (NSD) have seriously affected crop yield and frequently take place in a HAT-NSD combination. Maize (Zea mays) is an important crop, thermophilic but not heat tolerant. In this study, HAT, NSD, and HAT-NSD effects on maize inbred line Huangzao4 -were characterized. Main findings were as follows: H₂O₂ and O^- accumulated much more in immature young leaves than in mature old leaves under the stresses. Lateral roots were highly distributed near the upper pot mix layers under HAT and near root tips under HAT-NSD. Saccharide accumulated mainly in stressed root caps (RC) and formed a highly accumulated saccharide band at the boundary between RC and meristematic zone. Lignin deposition was in stressed roots under NSD and HAT-NSD. Chloroplasts increased in number and formed a high-density ring around leaf vascular bundles (VB) under HAT and HAT-NSD, and sparsely scattered in the peripheral area of VBs under NSD. The RC cells containing starch granules were most under NAD-HAT but least under HAT. Under NSD and HAT-NSD followed by re-watering, anther number per tassel spikelet reduced to 3. These results provide multiple clues for further distinguishing molecular mechanisms for maize to tolerate these stresses.

Preliminary Expression Analysis of the OSCA Gene Family in Maize and Their Involvement in Temperature Stress

Hyperosmolality-gated calcium-permeable channels (OSCA) are characterized as an osmosensor in plants; they are able to recognize and respond to exogenous and endogenous osmotic changes, and play a vital role in plant growth and adaptability to environmental stress. To explore the potential biological functions of OSCAs in maize, we performed a bioinformatics and expression analysis of the ZmOSCA gene family. Using bioinformatics methods, we identified twelve OSCA genes from the genome database of maize. According to their sequence composition and phylogenetic relationship, the maize OSCA family was classified into four groups (Ⅰ, Ⅱ, Ⅲ, and Ⅳ). Multiple sequence alignment analysis revealed a conserved DUF221 domain in these members. We modeled the calcium binding sites of four OSCA families using the autodocking technique. The expression profiles of ZmOSCA genes were analyzed in different tissues and under diverse abiotic stresses such as drought, salt, high temperature, and chilling using quantitative real-time PCR (qRT-PCR). We found that the expression of twelve ZmOSCA genes is variant in different tissues of maize. Furthermore, abiotic stresses such as drought, salt, high temperature, and chilling differentially induced the expression of twelve ZmOSCA genes. We chose ZmOSCA2.2 and ZmOSCA2.3, which responded most strongly to temperature stress, for prediction of protein interactions. We modeled the calcium binding sites of four OSCA families using autodocking tools, obtaining a number of new results. These results are helpful in understanding the function of the plant OSCA gene family for study of the molecular mechanism of plant osmotic stress and response, as well as exploration of the interaction between osmotic stress, high-temperature stress, and low-temperature stress signal transduction mechanisms. As such, they can provide a theoretical basis for crop breeding.

Metabolomic and transcriptomic analyses reveal that sucrose synthase regulates maize pollen viability under heat and drought stress

Maize pollen is highly sensitive to heat and drought, but few studies have investigated the combined effects of heat and drought on pollen viability. In this study, pollen's structural and physiological characteristics were determined after heat, drought, and combined stressors. Furthermore, integrated metabolomic and transcriptomic analyses of maize pollen were conducted to identify potential mechanisms of stress responses. Tassel growth and spikelet development were considerably suppressed, pollen viability was negatively impacted, and pollen starch granules were depleted during anthesis under stress. The inhibitory effects were more significant due to combined stresses than to heat or drought individually. The metabolic analysis identified 71 important metabolites in the combined stress compared to the other treatments, including sugars and their derivatives related to pollen viability. Transcriptomics also revealed that carbohydrate metabolism was significantly altered under stress. Moreover, a comprehensive metabolome-transcriptome analysis identified a central mechanism in the biosynthesis of UDP-glucose involved in reducing the activity of sucrose synthase SH-1 (shrunken 1) and sus1 (sucrose synthase 1) that suppressed sucrose transfer to UDP-glucose, leading to pollen viability exhaustion under stress. In conclusion, the lower pollen viability after heat and drought stress was associated with poor sucrose synthase activity due to the stress treatments.

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.

Compound events and associated impacts in China

Owing to amplified impacts on human society and ecosystems, compound events (or extremes) have attracted ample attention in recent decades. China is particularly vulnerable to compound events due to the fast warming rate, dense populations, and fragile ecological environment. Recent studies have demonstrated tangible effects of climate change on compound events with mounting impacts on the economy, agriculture, public health, and infrastructure in China, posing unprecedented threats that are increasingly difficult to manage. Here, I synthesize recent progress in studies of compound events and associated impacts in China. Several lines of evidence indicate an increase in the frequency and intensity of multiple types of compound events across China. Future directions in studying compound events in China are suggested, including investigating extremes from a compound perspective, modeling compound events in the Anthropocene, quantitative evaluations of risks, and holistic adaptation measures of compound events.

The impact of high temperature and drought stress on the yield of major staple crops in northern China

The study of the impact of high temperature and drought on the yield of major staple crops can provide important scientific support for the decision-making of agricultural sustainable development. Based on the temperature and precipitation data of the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA 5 for northern China, this paper calculates three indexes, the standard precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI) and the extreme degree-day (EDD), from 1979 to 2017. Monthly SPI and monthly SPEI were calculated at 1 - to - 12 month lags, and EDD was calculated per crop growth season. The yield of winter wheat, spring wheat and summer maize in each province of the study area from 1979 to 2017 was de-trended, and the relative fluctuation of the yield of the three crops was calculated. The change trends of SPI, SPEI and EDD were analysed using the Mann-Kendall test and Sen's slope. The single and interactive effects of high temperature and drought on crop yield were studied using multidimensional Copula function. The results show that: 1) Both high temperature and drought stress in northern China show an increasing trend. The drought trend in the study area detected based on SPEI was greater than the drought trend detected by SPI. The difference between SPEI and SPI in the winter wheat growing season was smaller than that in the spring wheat and maize growing seasons. 2) With the increase in EDD and the decrease of SPI/SPEI values, the probability of negative yield fluctuation gradually increased, and the probability of positive yield fluctuation gradually decreased. Under the same drought and high temperature conditions, the probability of yield fluctuation varies among different crops and different provinces. Drought has a greater impact on crop yield than high temperature. Both the single and interactive effects of drought and high temperature on yield are nonlinear. 3) Irrigation can effectively alleviate the impact of drought and high temperature on yield. In heavily irrigated provinces, the effects of both high temperature and drought on crop yield are not obvious.

Increased heat stress risk for maize in arid-based climates as affected by climate change: threats and solutions

Heat stress in combination with drought has become the biggest concern and threat for maize yield production, especially in arid and hot regions. Accordingly, different optimal solutions should be considered in order to maintain maize production and reduce the risk of heat stress under the changing climate. In the current study, the risk of heat stress across Iranian maize agro-ecosystems was analyzed in terms of both intensity and frequency. The study areas comprised 16 provinces and 24 locations classified into five climate categories: arid and hot, arid and temperate, semi-arid and hot, semi-arid and temperate, and semi-arid and cold. The impact of heat stress on maize under a future climate was based on a 5-multi-model ensemble under two optimistic and pessimistic emission scenarios (RCP4.5 and RCP8.5, respectively) for 2040-2070 using the APSIM crop model. Simulation results illustrated that in the period of 2040-2070, intensity and the frequency of heat stress events increased by 2.37 °C and 79.7%, respectively, during maize flowering time compared to the baseline. The risk of heat stress would be almost 100% in hot regions in the future climate under current management practices, mostly because of the increasing high-risk window for heat stress which will result in a yield reduction of 0.83 t ha^-1. However, under optimal management practices,farmers will economically obtain acceptable yields (6.6 t ha^-1). The results also indicated that the high-risk windows in the future will be lengthening from 12 to 33 days in different climate types. Rising temperatures in cold regions as a result of global warming would provide better climate situations for maize growth, so that under optimistic emission scenarios and optimal management practices, farmers will be able to boost grain yield up to 9.2 t ha^-1. Overall, it is concluded that farmers in hot and temperate regions need to be persuaded to choose optimal sowing dates and new maize cultivars which are well adapted to each climate to reduce heat stress risk and to shift maize production to cold regions.