{"title":"通过机器学习和结构方程建模,揭示不同水管理制度对糙米镉的影响因素和途径。","authors":"Yingxia Liu, Jinchuan Ma, Junjie Chu, Wanchun Sun, Qiang Wang, Yangzhi Liu, Ping Zou, Junwei Ma","doi":"10.1016/j.scitotenv.2024.176033","DOIUrl":null,"url":null,"abstract":"<p><p>Excessive cadmium (Cd) in brown rice has detrimental effects on rice growth and human health. Water management is a cost-effective, eco-friendly measure to suppress Cd accumulation in rice. However, there is no acknowledged water management regime that reduces Cd accumulation in brown rice without compromising the yield. Meanwhile, the major factors affecting brown rice Cd and the pathways of water management affecting rice Cd are not clear. This study explored major factors affecting brown rice Cd using machine learning (ML) and examined the pathways of water management affecting rice Cd using a structural equation model (SEM). Three water management systems were set up, namely flooding, water-saving, and wetting irrigation. Results showed that water-saving irrigation increased dry matter and reduced Cd content and translocation. Root uptake during the grain filling stage and Cd remobilization before the grain filling stage contributed 36 % and 64 % of the Cd accumulation in brown rice, respectively. ML explained 97 % of the variance, suggesting that crop covariates were the most important (e.g., the brown rice bioconcentration factor (12 %), stem Cd (9 %), root-to-stem translocation factor (7 %)), followed by soil covariates (e.g., reducing substances 12 %) and water management (3 %). All SEM explanatory variables collectively explained 94 % of the variation, with a predictive power of 76 %. Water treatments indirectly affected soil available Fe and Mn (indirect effect coefficient = 0.909), iron plaques (indirect effect coefficient = 0.866), soil available Cd (indirect effect coefficient = -0.671), and Cd intensity of xylem sap (BI<sub>Cd</sub>, indirect effect coefficient = -0.664) via pH and reducing substances. BI<sub>Cd</sub> significantly positively affected stem Cd (path coefficient = 0.445). These findings provide insight into the agronomic and environmental effects of water management on brown rice Cd and influence pathways in soil-rice systems, suggesting that water-saving irrigation may alleviate Cd contamination in the paddy soil.</p>","PeriodicalId":422,"journal":{"name":"Science of the Total Environment","volume":" ","pages":"176033"},"PeriodicalIF":8.2000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machine learning and structural equation modeling for revealing the influence factors and pathways of different water management regimes acting on brown rice cadmium.\",\"authors\":\"Yingxia Liu, Jinchuan Ma, Junjie Chu, Wanchun Sun, Qiang Wang, Yangzhi Liu, Ping Zou, Junwei Ma\",\"doi\":\"10.1016/j.scitotenv.2024.176033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Excessive cadmium (Cd) in brown rice has detrimental effects on rice growth and human health. Water management is a cost-effective, eco-friendly measure to suppress Cd accumulation in rice. However, there is no acknowledged water management regime that reduces Cd accumulation in brown rice without compromising the yield. Meanwhile, the major factors affecting brown rice Cd and the pathways of water management affecting rice Cd are not clear. This study explored major factors affecting brown rice Cd using machine learning (ML) and examined the pathways of water management affecting rice Cd using a structural equation model (SEM). Three water management systems were set up, namely flooding, water-saving, and wetting irrigation. Results showed that water-saving irrigation increased dry matter and reduced Cd content and translocation. Root uptake during the grain filling stage and Cd remobilization before the grain filling stage contributed 36 % and 64 % of the Cd accumulation in brown rice, respectively. ML explained 97 % of the variance, suggesting that crop covariates were the most important (e.g., the brown rice bioconcentration factor (12 %), stem Cd (9 %), root-to-stem translocation factor (7 %)), followed by soil covariates (e.g., reducing substances 12 %) and water management (3 %). All SEM explanatory variables collectively explained 94 % of the variation, with a predictive power of 76 %. Water treatments indirectly affected soil available Fe and Mn (indirect effect coefficient = 0.909), iron plaques (indirect effect coefficient = 0.866), soil available Cd (indirect effect coefficient = -0.671), and Cd intensity of xylem sap (BI<sub>Cd</sub>, indirect effect coefficient = -0.664) via pH and reducing substances. BI<sub>Cd</sub> significantly positively affected stem Cd (path coefficient = 0.445). These findings provide insight into the agronomic and environmental effects of water management on brown rice Cd and influence pathways in soil-rice systems, suggesting that water-saving irrigation may alleviate Cd contamination in the paddy soil.</p>\",\"PeriodicalId\":422,\"journal\":{\"name\":\"Science of the Total Environment\",\"volume\":\" \",\"pages\":\"176033\"},\"PeriodicalIF\":8.2000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science of the Total Environment\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1016/j.scitotenv.2024.176033\",\"RegionNum\":1,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/9/24 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science of the Total Environment","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1016/j.scitotenv.2024.176033","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/24 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Machine learning and structural equation modeling for revealing the influence factors and pathways of different water management regimes acting on brown rice cadmium.
Excessive cadmium (Cd) in brown rice has detrimental effects on rice growth and human health. Water management is a cost-effective, eco-friendly measure to suppress Cd accumulation in rice. However, there is no acknowledged water management regime that reduces Cd accumulation in brown rice without compromising the yield. Meanwhile, the major factors affecting brown rice Cd and the pathways of water management affecting rice Cd are not clear. This study explored major factors affecting brown rice Cd using machine learning (ML) and examined the pathways of water management affecting rice Cd using a structural equation model (SEM). Three water management systems were set up, namely flooding, water-saving, and wetting irrigation. Results showed that water-saving irrigation increased dry matter and reduced Cd content and translocation. Root uptake during the grain filling stage and Cd remobilization before the grain filling stage contributed 36 % and 64 % of the Cd accumulation in brown rice, respectively. ML explained 97 % of the variance, suggesting that crop covariates were the most important (e.g., the brown rice bioconcentration factor (12 %), stem Cd (9 %), root-to-stem translocation factor (7 %)), followed by soil covariates (e.g., reducing substances 12 %) and water management (3 %). All SEM explanatory variables collectively explained 94 % of the variation, with a predictive power of 76 %. Water treatments indirectly affected soil available Fe and Mn (indirect effect coefficient = 0.909), iron plaques (indirect effect coefficient = 0.866), soil available Cd (indirect effect coefficient = -0.671), and Cd intensity of xylem sap (BICd, indirect effect coefficient = -0.664) via pH and reducing substances. BICd significantly positively affected stem Cd (path coefficient = 0.445). These findings provide insight into the agronomic and environmental effects of water management on brown rice Cd and influence pathways in soil-rice systems, suggesting that water-saving irrigation may alleviate Cd contamination in the paddy soil.
期刊介绍:
The Science of the Total Environment is an international journal dedicated to scientific research on the environment and its interaction with humanity. It covers a wide range of disciplines and seeks to publish innovative, hypothesis-driven, and impactful research that explores the entire environment, including the atmosphere, lithosphere, hydrosphere, biosphere, and anthroposphere.
The journal's updated Aims & Scope emphasizes the importance of interdisciplinary environmental research with broad impact. Priority is given to studies that advance fundamental understanding and explore the interconnectedness of multiple environmental spheres. Field studies are preferred, while laboratory experiments must demonstrate significant methodological advancements or mechanistic insights with direct relevance to the environment.