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Strategies for improving crop comprehensive benefits via a decision-making system based on machine learning in the rice‒rape, rice‒wheat and rice‒garlic rotation systems in Southwest China

Xinrui Li, Xiafei Li, Tao Liu, Huilai Yin, Hao Fu, Yongheng Luo, Yanfu Bai, Hongkun Yang, Zhiyuan Yang, Yongjian Sun, Jun Ma, Zongkui Chen

2024, 23 (9): 2970-2988. DOI: 10.1016/j.jia.2023.10.005

Abstract （157） PDF in ScienceDirect

Rice‒rape, rice‒wheat and rice‒garlic rotations are common cropping systems in Southwest China, and they have played a significant role in ensuring ecological and economic benefits (EB) and addressing the challenges of China’s food security in the region. However, the crop yields in these rotation systems are 1.25‒14.73% lower in this region than the national averages. Intelligent decision-making with machine learning can analyze the key factors for obtaining better benefits, but it has rarely been used to enhance the probability of obtaining such benefits from rotations in Southwest China. Thus, we used a data-intensive approach to construct an intelligent decision‒making system with machine learning to provide strategies for improving the benefits of rice–rape, rice–wheat, and rice–garlic rotations in Southwest China. The results show that raising the yield and partial fertilizer productivity (PFP) by increasing seed input under high fertilizer application provided the optimal benefits with a 10% probability in the rice–garlic system. Obtaining high yields and greenhouse gas (GHG) emissions by increasing the N application and reducing the K application provided suboptimal benefits with an 8% probability in the rice–rape system. Reducing N and P to enhance PFP and yield provided optimal benefits with the lowest probability (8%) in the rice‒wheat system. Based on the predictive analysis of a random forest model, the optimal benefits were obtained with fertilization regimes by reducing N by 25% and increasing P and K by 8 and 74%, respectively, in the rice–garlic system, reducing N and K by 54 and by 36%, respectively, and increasing P by 38% in rice–rape system, and reducing N by 4% and increasing P and K by 65 and 23% in rice–wheat system. These strategies could be further optimized by 17‒34% for different benefits, and all of these measures can improve the effectiveness of the crop rotation systems to varying degrees. Overall, these findings provide insights into optimal agricultural inputs for higher benefits through an intelligent decision-making system with machine learning analysis in the rice–rape, rice‒wheat, and rice–garlic systems.

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Leaf and pod growth affect seed yield after shoot removal and different nitrogen rates of dual-purpose rapeseed (Brassica napus L.)

Xiaoyong Li, Wei Huang, Zhiyuan Yang, Wei Hu, Zhiguo Zhou, Binglin Chen

DOI: 10.1016/j.jia.2025.04.035 Online: 27 April 2025

Abstract （9） PDF in ScienceDirect

As a multifunctional crop, rapeseed provides vegetables by picking shoots. Shoot removal reduced yield, while nitrogen (N) application results in efficiency gains. However, the effect of N rate on pod growth, N use efficiency (NUE) and seed yield after shoot removal is unclear. A 2-year field experiment was set with four N rates (0 [N0], 90 [N1], 180 [N2], and 270 [N3] kg ha^-1) and two shoot treatments (no shoot removal [CK], shoot removal [SR]). Results showed the shoot removal decreased population biomass (PB) at maturity across all N levels. Conversely, N application increased the PB after shoot removal and elevated soluble sugar and protein in shoots. Shoot removal increased the seeds per pod (13.5-26.9%), reduced the pods per plant (33.1-45.8%) and population seed yield (19.5-38.4%). N application effectively increased the yield related index, and led to an increase in population seed yield by 187.2 - 465.0% in the CK group, and by 185.6 - 430.7% in the SR group. Moreover, the seed yield reached its maximum under the N3 in both groups. The leaf N content per area (N_a) and net photosynthetic rate (P_n) were increased, but leaf photosynthetic N use efficiency (PNUE) were decreased at 20 days after shoot removal, which lead to a significant decrease in N use efficiency(NUE). N supply increased the plant organ N content and PB, but decreased the NUE at maturity stage. P_n of the pod wall at 25 days after flowering was elevated due to its optimized chloroplasts ultrastructure and increased rubisco and sucrose synthase activities under shoot removal and more N. However, the greater amino acid/soluble sugar ratio (A/S) of the pod wall significantly increased the seed protein content and decreased the oil content. Though the oil yield was reduced by 63.8-71.0% under SR×N3 treatment compared with CK×N3, it was comparable to that of CK with 90 kg N ha^-1 treatment. The results indicated that N applying improves the carbon metabolism of the pod wall and alleviates yield reduction after shoot removal but reduces NUE and seed oil content of rapeseed. The findings guide the balancing of rapeseed’s vegetable and oil production, and optimize N fertilization for sustainable, efficient rapeseed farming.

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Copyright © Journal of Integrative Agriculture
Sponsored by Chinese Academy of Agricultural Sciences (CAAS)
Co-sponsored by China Association of Agricultural Science Societies (CAASS)
Publishing Service by Elsevier B.V.on behalf of KeAi Communications Co. Ltd.
Full text available online at ScienceDirect

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