Abstract:

To elucidate the unique mechanism of dense planting efficiency in alpine regions with short growing seasons, and to determine the optimal planting density and climatic adaptability of rapeseed in Arxan, this study systematically analyzed the effects of planting density on agronomic traits, yield, and growth duration based on 30 consecutive years (1996-2025) of field observation data. The synergistic effects between planting density and meteorological factors were also investigated. The results demonstrated that with increasing density, individual plant traits, including primary branch number, pod number, and grain weight per plant, significantly improved by 60%-110%, while population yield continuously increased without exhibiting the typical yield decline inflection point observed in classical density studies. The optimal planting density for rapeseed in Arxan ranged from 600,000 to 850,000 plants/hm², achieving a maximum theoretical yield of 6511.4 kg/hm². Dense planting significantly shortened the growth period by 15-16 days, facilitating early maturity and disaster avoidance. Correlation analysis revealed negative associations between density/yield and accumulated temperature ≥10℃ and sunshine hours, whereas positive correlations were observed with precipitation and 10 cm soil temperature, with precipitation showing the strongest correlation with yield (r = 0.68). During 2016-2025, despite unfavorable climatic conditions characterized by slightly reduced accumulated temperature and decreased sunshine hours, substantial yield improvements were achieved through increased planting density and variety enhancement, confirming the enhanced cold tolerance of varieties and the effectiveness of the “compensating for light with density” cultivation strategy. This study provides a scientific foundation for breeding cold-tolerant, high-density rapeseed varieties and establishing intensive high-yield cultivation systems in alpine regions with short growing seasons.

Key words: rapeseed, planting density, agronomic traits, climate adaptability, population optimization, analysis