Optimizing Sunflower Cultivar Selection Under Climate Variability: Evidence from Coupled Meteorological-Growth Modeling in Arid Northwest China - Jianguo Mu; Jianqin Wang; Ruiying Ma; Zengshuai Lv; Hongye Dong; Yantao Liu; Wei Duan; Shengli Liu; Peng Wang; Xuekun Zhang (Agronomy)
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 °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.