Abstract
Northeast China is known as the “Corn Belt” of China. Long-term conventional tillage has led to severe soil degradation, threatening the food production and China’s food security. Regenerative farming practices such as no-tillage and deep ploughing have proven effective in protecting soil and promoting sustainable agriculture. However, the effects of no-tillage and deep ploughing on corn yield are hotly debated, and their regional suitability in Northeast China remains unclear. As a solution, a regional machine learning aided meta-analysis was performed to assess the effects of field management practices, climate conditions, and soil properties on crop productivity of no-tillage and deep ploughing versus conventional tillage, and to evaluate the probability of yield increase under no-tillage and deep ploughing across Northeast China. The results showed that the overall effect of no-tillage and deep ploughing significantly increased corn yield by 5.1% and 6.4%, respectively, compared to conventional tillage. Climate conditions had the greatest importance on crop yield under no-tillage, while management practices were the most explainable variable under deep ploughing. Data driven models reveled that the probabilities of yield increase under no-tillage and deep ploughing had large geographical differences. No-tillage performed better in warm arid regions with alkaline soil and low initial soil organic matter. In cold and humid areas with neutral soil and high soil organic matter content, deep ploughing had the greatest possibility of increasing yield. Our study revealed the effects and importance of factors affecting crop productivity of no-tillage and deep ploughing, which helps to optimize these practices. Furthermore, our results provide a reference for agricultural managers to select appropriate tillage practices that simultaneously contribute to food production and sustainable agricultural goals in specific regions of Northeast China.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
