Optimizing Sunflower Cultivar Selection Under Climate Variability: Evidence from Coupled Meteorological-Growth Modeling in Arid Northwest China

文献类型： 外文期刊

第一作者： Mu, Jianguo

作者： Mu, Jianguo;Ma, Ruiying;Mu, Jianguo;Wang, Jianqin;Lv, Zengshuai;Dong, Hongye;Liu, Yantao;Duan, Wei;Liu, Shengli;Wang, Peng;Ma, Ruiying;Zhang, Xuekun

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关键词： sunflower growth period; meteorological sensitivity; grain quality

期刊名称：AGRONOMY-BASEL （ 影响因子：3.4； 五年影响因子：3.8 ）

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年卷期： 2025 年 15 卷 7 期

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收录情况： SCI

摘要： Under the scenario of global climate warming, meteorological risks affecting sunflower cultivation in Xinjiang's 10th Division were investigated by developing a meteorological-growth coupling model. Field experiments were conducted at three representative stations (A1-A3) during 2023-2024 to assess temperature and precipitation impacts on yield and quality traits among sunflower cultivars with varying maturation periods. The main findings were: (1) Early-maturing cultivar B1 (RH3146) exhibited superior adaptation at low-temperature station A1, achieving 12% higher plant height and an 18% yield increase compared to regional averages. (2) At thermally variable station A2 (daily average temperature fluctuation +/- 8 degrees C, precipitation CV = 25%), the late-maturing cultivar B3 showed enhanced stress resilience, achieving 35.6% grain crude fat content (15% greater than mid-maturing B2) along with 8-10% increases in seed setting rate and 100-grain weight. These improvements were potentially due to optimized photoassimilated allocation and activation of stress-responsive genes. (3) At station A3, characterized by high thermal-humidity variability (CV > 15%) during grain filling, B3 experienced a 15-day delay in maturation and a 3% reduction in ripeness. Two principal mitigation strategies are recommended: preferential selection of early-to-mid maturing cultivars in regions with thermal-humidity CV > 10%, improving yield stability by 23%, and optimization of sowing schedules based on accumulated temperature-precipitation modeling, reducing meteorological losses by 15%. These evidence-based recommendations provide critical insights for climate-resilient cultivar selection and precision agricultural management in meteorologically vulnerable agroecosystems.

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