Journal of Agronomy and Crop Science最新文献

Global temperature rises and frequent heat waves increasingly threaten rice production by destabilising canopy and root-zone microclimates. Natural or conventional airflow management techniques often fail to provide precise, repeatable thermal regulation. In this study, we directly compared rotors airflow-engineered microclimates with ambient airflows across diurnal cycles (9:00 a.m., 12:00 p.m., 3:00 p.m.) and rice growth stages (heading, panicle, flowering). A rotor-based Wind Wall (WW) system was deployed to simulate rotors-induced airflow under controlled conditions, and computational fluid dynamics (CFD) validated rotor array performance, turbulence distribution, and wind field uniformity. Relative to ambient airflow, rotors airflow reduced canopy-top temperature variance by up to 48%, maintained peak midday temperature gradients at 0.11°C, and stabilised afternoon gradients to 0.06°C. Mid-canopy wind speed under rotors airflow decreased from 1.817 m s⁻¹ to 0.446 m s⁻¹ (−75.4%) at noon but rebounded to 0.843 m s⁻¹ (+89%) by 3:00 p.m., improving midday canopy stability. Turbulence intensity remained moderate (0.355–0.390), enhancing canopy aeration and gas exchange, while wind shear across plant layers stabilised between −0.12 and 3.91 s⁻¹. Physiologically, rotors airflow-engineered microclimates improved photosynthetic efficiency by 18%, reduced midday root-zone temperature variability by 33%, and decreased water loss by 14% compared with ambient conditions. Grain yield at flowering reached 43.2 g plant⁻¹, a 91% increase over restricted airflow and 23% higher than ambient airflow, with the harvest index rising to 37.24% (+14.8%). Across all growth stages and times of day, rotors-induced airflow consistently mitigated thermal stress, stabilised microclimate conditions, and enhanced nutrient uptake, resulting in more uniform grain filling and superior yield performance. These findings highlight UAV-based microclimate engineering as a precise and scalable strategy for controlling plant thermal and aerodynamic environments, offering a viable approach to climate change adaptation in rice production systems.

Crop-stage-specific deficit irrigation (DI) has been widely applied to achieve the optimum agricultural water use in dryland farming areas. However, the water use characteristics during different crop stages have not been fully investigated, considering ET uncertainties. It may hinder the correct decisions on optimum agricultural water management. This study investigated how the root-zone water budget components varied throughout the growing season in a summer maize field under three different irrigation regimes by using a soil water model, STEMMUS-ET, with the indirect and direct ET methods. Two successive years of crop-stage-specific DI experiments were conducted on a summer maize field in Northwest China to calibrate and evaluate the STEMMUS-ET model. Results indicate that STEMMUS-ET simulated the soil water contents, ET, soil evaporation, and root-zone water budgets well for all irrigation treatments. The influence of using different ET methods on soil moisture content mainly affects shallow soil layers (0–30 cm). The soil evaporation simulation was largely improved by the direct ET method due to the consideration of aerodynamic and surface resistance terms, especially after irrigation. Different irrigation amount has a significant effect on the transpiration but not on the soil evaporation. It is the frequency rather than the amount of irrigation that largely affects soil evaporation. Compared to CK treatment, the DI treatments depleted more soil water storage with less use of irrigation water throughout the growing season. T1, with the reduced irrigation water amount properly at the same irrigation frequency, can significantly improve WUE, increasing it by 9.71% compared to CK. These insights help make reasonable water management in dryland agriculture.

Rice (Oryza sativa L.) straw and roots are the primary sources of soil organic carbon (SOC) of paddies; however, variations in the quantity and quality of these residues under climate change remains unclear. This study investigated the changes in the rice residue biomass and the carbon-to-nitrogen ratio (C/N) under elevated [CO₂] (e[CO₂]) and air temperature (eT_air) for 2 years with naturally varying weather conditions. Rice was cultivated under different [CO₂]–T_air for 2019–2020, with longer sunshine hours and solar radiation (R_solar) during rice growing period in 2019 (675 h and 2079 MJ m⁻², respectively) than in 2020 (589 h and 1929 MJ m⁻², respectively). Rice biomass (grains, straw and roots), C gain and N uptake were measured, and C/N was determined. Compared to the ambient conditions, e[CO₂]–eT_air consistently increased straw and roots biomass for both years by 38.7% and 137.2% in 2019 and by 46.0% and 76.2% in 2020, respectively. However, under e[CO₂]–eT_air, C/N increased in 2019 (by 14.5%–31.6%), but decreased in 2020 (by 10.0%–12.2%) compared to ambient conditions. Comparing both years, straw and roots biomass were lower in 2020 than in 2019 by 19%–31% and by 31%–58%, respectively, with decreased C/N in 2020 by up to 32%. These results indicate that e[CO₂]–eT_air coupled with lower R_solar produces lower-quantity rice residues with high quality (i.e., a lower C/N) compared to those with higher R_solar, thus potentially reducing SOC accrual compared to higher R_solar conditions.

Abiotic stresses are one of the major factors affecting crop productivity. Among all the abiotic stresses, drought is the most critical and common stress that impedes crop productivity and endangers global food security. Recent developments in the classical omics technologies, that is, genomics, proteomics, metabolomics and phenomics have provided insights into the complex network of genes regulating drought response and adaptation. Genomics facilitates the identification of drought-responsive genes and quantitative trait loci (QTLs), while transcriptomics provides a dynamic view of gene expression under water-deficit conditions. Proteomics and metabolomics reveal the functional proteins and metabolites involved in stress tolerance mechanisms, such as osmoprotectant accumulation, antioxidant activity and signalling pathways. Integrating high-throughput omics data enables the precise characterisation of drought-tolerant phenotypes, bridging the genotype-to-phenotype gap. Advanced bioinformatics tools and systems biology approaches further enhance the interpretation of multi-omics datasets, enabling the identification of key regulatory networks and potential targets for crop improvement. Such comprehensive insights, therefore, will hopefully build a road for developing climate-resilient crops by marker-assisted breeding, genome editing and transgenic technologies. This review explores the transformative potential of omics approaches in mitigating drought stress in crop plants, laying the foundation for sustainable agriculture in the face of escalating climate challenges.

Flower abortion in soybeans is a natural process that intensifies under adverse environmental stress conditions, particularly under high temperatures and water-deficit conditions, leading to significant yield loss. This study aimed to evaluate the extent of flower abortion across a genetically diverse panel (MG III—IV) and quantify flower abortion under two different irrigation regimes. Two field experiments were conducted with a panel of 206 genotypes evaluated under 80% ET in 2023. In 2024, a representative sub-set of 48 genotypes was tested under two irrigation regimes (80% and 40% ET). Flower number, pod number, flower abortion, and grain yield were recorded in both years, while plant height, node number, and seed number per pod per plant were recorded only in 2024. In 2023, atypical extreme heat events (> 40°C) led to elevated flower abortion rates (26%–80%). In contrast, under cooler conditions (< 35°C) in 2024, flower abortion ranged between 25% and 53% (80% ET) and 21%–51% (40% ET). Genotypes were classified on flower abortion and yield to identify high-yielding genotypes with either high or low flower abortion. Soybean genotypes exhibited distinct flowering plasticity strategies, with some compensating for high abortion through increased flower production, while others maintained yield stability through higher flower retention. LG05-4317 and PI506862 were identified as promising candidates having differential mechanisms for breeding high-yielding cultivars with optimised abortion rates. Combined analysis highlighted that phenotypic plasticity in flower number and flower abortion can be exploited to increase soybean yield under diverse environmental conditions.

Climate change has a detrimental impact on the sustainable development of wheat yield and quality. Delaying sowing dates and adjusting sowing rates represent straightforward and effective strategies for mitigating such effects, albeit with their underlying mechanisms remaining poorly characterised. In this investigation, taking the North China Plain (NCP) as an example, we conducted a meta-analysis of 59 studies and proving experiments at two locations. The results indicated that the wheat yield and ecological conditions had significant correlations, and reasonable late sowing and optimised sowing rates could significantly improve yield. In general, the relevant analysis showed that there was a positive correlation of 0.488 between soil organic matter and yield, and the negative correlations of yield on temperature and precipitation were 0.245 and 0.466, respectively. Furthermore, late sowing ≤ 10 days could increase yield by 3.05%–11.80% and the yield raised 1.31%–13.16% at a sowing rate of 201–300 kg/hm² under the precipitation > 600 mm, temperature ≥ 12°C and > 15 g/kg soil organic matter in the study. Late sowing and increasing sowing rates had a negative impact on wheat quality, which requires other management measures to be taken to balance production. In conclusion, our study elucidates the influence of late sowing and sowing rates on wheat yield and quality, providing a theoretical basis for subsequent research on the relationship between climate factors and crop yields–quality trade-offs.

The scarcity of good-quality irrigation water has driven farmers to use saline water for crop production, which can adversely affect soil fertility and plant growth. Therefore, a long-term (2006–2025) field experiment was conducted to investigate the effects of saline water application by different irrigation methods on cotton seedling emergence and growth, and to promote safe saline water use. The field experiment employed two irrigation methods, namely border irrigation (B) and furrow irrigation with channels (F), with each irrigation method paired with six salt concentration levels (1.3, 3.4, 7.1, 10.6, 14.1, 17.7 dS·m⁻¹; 1.3 dS·m⁻¹ was the freshwater control). Observations showed that compared with furrow irrigation, the soil moisture contents and salinity levels under border irrigation increased by 0.9%–4.1% and 0.1%–27.7%, respectively. Additionally, soil moisture content and salinity rose as irrigation water salinity increased in both irrigation methods. Topsoil (0–20 cm) moisture content and salinity exhibited significant interannual fluctuations, with no steady salinity accumulation due to precipitation and associated climatic conditions. The seedling establishment rate declined with increasing water salinity under both methods; border irrigation was superior at water salinity ≤ 8.3 dS·m⁻¹, while furrow irrigation performed better above this threshold. Stability and sustainability of the establishment rate decreased markedly at water salinity ≥ 10.6 dS·m⁻¹. The relative establishment rate over the years (referenced to the freshwater treatments with an electrical conductivity of 1.3 dS·m⁻¹) exhibited a significant quadratic relationship with irrigation water salinity. When the seedling establishment rate began to decline and reached a 10% reduction, the corresponding irrigation water salinity thresholds for border irrigation were 2.2 dS·m⁻¹ and 10.0 dS·m⁻¹, and for furrow irrigation were 1.9 dS·m⁻¹ and 10.4 dS·m⁻¹, respectively. High salinity significantly delayed cotton emergence and reduced seedling growth parameters (plant height, leaf area, and dry matter weight). Seedling growth was better under border irrigation than under furrow irrigation at irrigation water salinity ≤ 10.6 dS·m⁻¹. This study provides a scientific basis and practical reference for cotton cultivation using local saline water resources.

The impact of climate change, as evidenced by increasingly higher temperatures and decreasing precipitation, presents a substantial threat to wheat crops globally. In the Indo-Gangetic Plains (IGP), which is the breadbasket of India, it is evolving as the biggest threat to food security and livelihoods for the farming fraternity. A 3-year field study evaluated the effects of drought and heat stress on wheat yield and how these effects interact with morphophysiological traits. This study deployed staggered sowing and controlled irrigation to simulate droughts synchronising with vegetative and reproductive stages of the crop across 13 wheat cultivars selected based on their prevalence among farmers. Principal component analysis (PCA) and Pearson's correlation matrices were used to reduce data dimensionality for shortlisting independent morphophysiological variables before measuring average treatment effects. Findings highlighted a decline in levels of relative water content (RWC), chlorophyll and carotenoid under stress treatments. A sharp reduction of almost 50% in grain yield was observed when the crop encountered drought and heat stress simultaneously. Another finding revealed that RWC, chlorophyll content and proline accumulation were strongly associated with resilience to these stresses. The study identified two wheat cultivars (HD 2967 and HI 1531) that demonstrated superiority in coping with stress conditions consistently under both timely and late sowing conditions. These findings are insightful for wheat breeders, highlighting potential plant traits for climate-resilient breeding programmes. The study also generated important evidence that can potentially inform policy makers around sowing time, irrigation scheduling and seed systems of wheat in eastern India and similar agroecological regions.

Heat stress severely impairs wheat yields and poses significant challenges to food security. In the present investigation, 72 diverse bread wheat genotypes were evaluated in the completely randomised block design with two replicates at four locations under normal and heat stress conditions during Rabi, 2022–23. The mean maximum temperature was above congenial (> 25°C) at 27.9°C, 28.8°C, 33.4°C and 33.3°C at Karnal, Hisar, Niphad and Pune locations, which imposed adverse effects at the heading and grain filling stages. Under heat stress, the pooled mean grain yield varied from 294.8 g (DHTW60) to 660.2 g/plot (RWP2017-21). The genotype DBW173 showed an 8.07% yield reduction under heat stress, followed by DBW187 (9.51%), PBW826 (10.25%), 29^th SAWYT-303 (10.36%), Raj3765 (11.41%), and RWP2017-21 (11.54%). The 1000 grain weight (TKW) reduction was also low for these genotypes, except for 29^th SAWYT-303 (19.80%). Here, the yield stability index (YSI) and heat susceptibility index (HSI) ranged from 0.56 to 1.02 and −0.09 to 1.95, respectively. In contrast, the relative heat index (RHI) and percent yield reduction (PYR) varied from 0.73 to 1.31 and −1.99 to 43.63, respectively. The low HSI values (< 0.60) were recorded for NIAW1342, HI1605, DBW173, DBW187, PBW826, 29^th SAWYT-303, 20^th HTWYT-2, Raj3765, RWP2017-21, K7903 and K9465. PCA clustered 13 heat stress indices into three clusters, where TOL, HSPI, HSI and PYR were grouped into a single segment. The genotypes DBW173, DBW187, HI1531, HI1605, NIAW1342, PBW826, Raj3765, RWP2017-21, 20^th HTWYT-2, 20^th HTWYT-13, 20^th HTWYT-41, 29^th SAWYT-303 and WAP96 appeared as heat tolerant. The higher TKW, grains/spike, coupled with higher NDVI values, can be used as selection criteria under heat stress breeding. The indices HSI, PYR, HRI, YI and YSI can be employed effectively in future studies.