Participating experts observe field trial results. [Photo/news.hzau.edu.cn]

Spring rapeseed plays a vital role as China's primary oilseed crop, especially in northern high-altitude and cold regions like Inner Mongolia, Qinghai, Gansu, and Xinjiang. These areas offer large-scale operations and wide diurnal temperature variations favoring oil accumulation. However, severe climate challenges — such as short growing seasons, spring droughts, frost risks, and pod shattering — heavily constrain yield potentials.

Addressing these challenges requires comprehensive, full-chain collaboration rather than isolated measures. Since 2024, a research team from Huazhong Agricultural University (HZAU), led by the academician Fu Tingdong, has partnered with local farms and agricultural extension agencies in Inner Mongolia. Together, they have tackled major production bottlenecks through integrated technological demonstrations.

In Enhe, the team established a specialized implementation model tailored for high-latitude cold-arid zones. This integrated model combines variety screening, seed treatment, moderate deep sowing, narrow-row high-density planting, strong-seedling anti-lodging control, pest management, and anti-shattering mechanical harvesting. Rather than simply increasing resource inputs, the approach optimizes population structures to secure robust seedlings, prevent lodging, and minimize harvest losses.

This year, the Enhe Model achieved remarkable results. By integrating high-latitude stress-resistant high-yield technologies, demonstration fields reached an average yield of 209.6 kilograms per mu (0.067 hectares), marking a 38.3 percent increase over non-demonstration areas. Furthermore, applying an anti-shattering adhesive yielded 166.2 kilograms per mu, outperforming the control group by 9.7 percent.

These technical breakthroughs rely heavily on dedicated talent empowerment. Over 10 graduate students participated in the project, with several stationed on-site throughout the growing season to provide continuous guidance from planting to data collection.