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 Ch...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.展开更多
ObjectiveThe aim was to increase farmers’ income and reduce the waste of fertilizer by exploring effects of N, P and K fertilizations on vegetable yields and the accumulation of N, P and K in vegetable and soils. Met...ObjectiveThe aim was to increase farmers’ income and reduce the waste of fertilizer by exploring effects of N, P and K fertilizations on vegetable yields and the accumulation of N, P and K in vegetable and soils. MethodThe fertilization tests were conducted on tomato, cauliflower and celery in greenhouses. ResultWhen N, P and K were not applied in tomato, cauliflower or celery, the yields reduced in 6.0%-13.8% and total annual income reduced by 39 220, 36 902 and 22 023 yuan/hm 2 respectively, suggesting that N, P and K are limiting factors of yield. The absorbed N amounts of tomato and cauliflower were higher compared with celery; the absorbed P amount of cauliflower was higher compared with tomato and celery; the absorbed K amount of tomato was the highest, followed by celery and cauliflower. The absorbed N in tomato fruit was lower than that of cauliflower and the absorbed N amount of other parts of tomato was also lower. Furthermore, the absorbed amounts of P and K by tomato and cauliflower fruits were higher than it absorbed by the other parts, especially the absorbed of K was significantly high. Total absorbed amounts of N, P and K from high to low were cauliflower, tomato and celery. After harvesting of tomato, cauliflower and celery, N, P and K in soils were all higher compared with soils before planting. Influenced by fertilizers, residual N content in soils grown with tomato and residual P content in soils grown with celery both doubled compared with base soils. Cauliflower plants were not applied with organic fertilizer, and residual N and K contents in soils were lower compared with tomato and celery. ConclusionResidual P content in soils is higher, which is a kind of waste and would cause pollution on soils. It is necessary to improve the proportion of organic and inorganic fertilizers in fertilization.展开更多
基金supported by the China Postdoctoral Science Foundation(2022M722301)the Sichuan Province Innovative Talent Funding Project for Postdoctoral Fellows,China(BX202207)the Natural Science Foundation of Sichuan Province,China(2023NSFC0014 and 2024NSFSC1225).
文摘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.
基金Supported by Tianjin Municipal Science and Technology Commission Program(07ZCGYNC00800)International Plant Nutrition Institute Program(Tianjin-2008,Tianjin-2009)Agricultural Eco-protection Program of Ministry of Agriculture(2110402-201258)~~
文摘ObjectiveThe aim was to increase farmers’ income and reduce the waste of fertilizer by exploring effects of N, P and K fertilizations on vegetable yields and the accumulation of N, P and K in vegetable and soils. MethodThe fertilization tests were conducted on tomato, cauliflower and celery in greenhouses. ResultWhen N, P and K were not applied in tomato, cauliflower or celery, the yields reduced in 6.0%-13.8% and total annual income reduced by 39 220, 36 902 and 22 023 yuan/hm 2 respectively, suggesting that N, P and K are limiting factors of yield. The absorbed N amounts of tomato and cauliflower were higher compared with celery; the absorbed P amount of cauliflower was higher compared with tomato and celery; the absorbed K amount of tomato was the highest, followed by celery and cauliflower. The absorbed N in tomato fruit was lower than that of cauliflower and the absorbed N amount of other parts of tomato was also lower. Furthermore, the absorbed amounts of P and K by tomato and cauliflower fruits were higher than it absorbed by the other parts, especially the absorbed of K was significantly high. Total absorbed amounts of N, P and K from high to low were cauliflower, tomato and celery. After harvesting of tomato, cauliflower and celery, N, P and K in soils were all higher compared with soils before planting. Influenced by fertilizers, residual N content in soils grown with tomato and residual P content in soils grown with celery both doubled compared with base soils. Cauliflower plants were not applied with organic fertilizer, and residual N and K contents in soils were lower compared with tomato and celery. ConclusionResidual P content in soils is higher, which is a kind of waste and would cause pollution on soils. It is necessary to improve the proportion of organic and inorganic fertilizers in fertilization.
