灌溉排水学报2026，Vol.45Issue(6)：27-39,13.DOI:10.13522/j.cnki.ggps.2025361
夏玉米花期高温干旱复合胁迫监测预警与穗粒数响应机制研究
Monitoring and early warning of heat-drought stress at the flowering stage of summer maize and its impact on kernel number per ear
摘要
Abstract
[Objective]Flowering stage is a critical stage for summer maize,during which concurrent heat and drought stress could severely undermine its yield formation.We developed a reliable method for monitoring and assessing the risk of combined heat and drought stress for summer maize during this growth stage.[Method]The study area is Henan Province.Multi-source data,including ground-based agrometeorological observations and CLDAS(China Land Data Assimilation System)grid data,were integrated to construct a comprehensive Heat-Drought Stress Index(HTI)by coupling the Temperature Stress Index(TSI)with soil moisture correction coefficients.Based on the 2025 intelligent grid forecast products of the China Meteorological Administration,an early warning method for heat-drought stress was developed.Field survey data from 28 counties in five regions across the province were used for post-disaster hindcast analysis,and the feasibility of the monitoring indicators for heat-drought stress at the flowering stage,as well as their applicability for early warning,was systematically evaluated.[Result]The Support Vector Machine(SVM)model is optimal for correcting the CLDAS_2mT and CLDAS_20cmRSM data,with the correlation coefficient(R)between observed and grid values reaching 0.999 8-1.0,and the Root Mean Square Error(RMSE)reduced by more than 60%compared with the raw data.The HTIoutperformed the TSIin characterizing heat-drought stress,showing a highly significant negative correlation with kernel number per ear(r=-0.520 2,P＜0.001).Compared with the TSI,the HTI reduced the RMSEof the modelled kernel number per ear by 6.04%and increased the absolute value of Rby 5.5%.The model identified 2017-2019,2022 and 2024 as years with severe heat-drought stress,with the stress intensity in 2025 exceeding previous levels.Risky zones with high stress were mainly in the eastern,southern and central parts of the province.Most regions exhibited a significant synergistic effect of heat and drought,and the kernel numbers per ear in high-risk zones were significantly lower than those in low-risk zones.[Conclusion]The 1-km resolution CLDAS data corrected by the SVM model meet the requirements for regional-scale assessment of heat-drought stress.The HTI can effectively quantify stress intensity and demonstrates that kernel numbers per ear is the key yield-limiting factor.In 2025,high-risky areas were mainly in the eastern,centra and southern parts of the province.The early warning method developed using TSI,soil moisture correction coefficients,and HTI provides a robust support for enhancing stress resilience and ensuring a stable summer maize yield.关键词
夏玉米/高温干旱复合胁迫/穗粒数/多源数据融合/花期/风险预警Key words
summer maize/combined heat and drought stress/kernel number per ear/multi-source data fusion/flowering stage/risk early warning分类
农业科技引用本文复制引用
李军玲,李梦夏,褚荣浩,薛昌颖,马志红,张溪荷,李树岩..夏玉米花期高温干旱复合胁迫监测预警与穗粒数响应机制研究[J].灌溉排水学报,2026,45(6):27-39,13.基金项目
国家重点研发计划项目(2024YFD2301301) （2024YFD2301301）
河南省科技攻关项目(262102111167,242102320028,242102321027) （262102111167,242102320028,242102321027）
河南省自然科学基金项目(252300420288) （252300420288）
中国气象局河南省农业气象保障与应用技术重点开放实验室基金项目(AMF202502) （AMF202502）
