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Uptake of zinc from the soil to the wheat grain: Nonlinear process prediction based on artificial neural network and geochemical data.

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Title: Uptake of zinc from the soil to the wheat grain: Nonlinear process prediction based on artificial neural network and geochemical data.
Authors: Lv KN; School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China; State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Beijing 100083, China., Huang Y; Beijing Institute of Ecological Geology, Beijing 100120, China., Yuan GL; School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China; State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Beijing 100083, China. Electronic address: yuangl@cugb.edu.cn., Sun YC; School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China., Li J; School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China., Li H; School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China; Beijing Institute of Ecological Geology, Beijing 100120, China., Zhang B; Beijing Institute of Ecological Geology, Beijing 100120, China.
Source: The Science of the total environment [Sci Total Environ] 2024 Oct 15; Vol. 947, pp. 174582. Date of Electronic Publication: 2024 Jul 10.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0330500 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-1026 (Electronic) Linking ISSN: 00489697 NLM ISO Abbreviation: Sci Total Environ Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Uptake of zinc from the soil to the wheat grain: Nonlinear process prediction based on artificial neural network and geochemical data.
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  Data: <searchLink fieldCode="AU" term="%22Lv+KN%22">Lv KN</searchLink>; School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China; State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Beijing 100083, China.<br /><searchLink fieldCode="AU" term="%22Huang+Y%22">Huang Y</searchLink>; Beijing Institute of Ecological Geology, Beijing 100120, China.<br /><searchLink fieldCode="AU" term="%22Yuan+GL%22">Yuan GL</searchLink>; School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China; State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Beijing 100083, China. Electronic address: yuangl@cugb.edu.cn.<br /><searchLink fieldCode="AU" term="%22Sun+YC%22">Sun YC</searchLink>; School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China.<br /><searchLink fieldCode="AU" term="%22Li+J%22">Li J</searchLink>; School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China.<br /><searchLink fieldCode="AU" term="%22Li+H%22">Li H</searchLink>; School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China; Beijing Institute of Ecological Geology, Beijing 100120, China.<br /><searchLink fieldCode="AU" term="%22Zhang+B%22">Zhang B</searchLink>; Beijing Institute of Ecological Geology, Beijing 100120, China.
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  Data: <searchLink fieldCode="JN" term="%220330500%22">The Science of the total environment</searchLink> [Sci Total Environ] 2024 Oct 15; Vol. 947, pp. 174582. <i>Date of Electronic Publication: </i>2024 Jul 10.
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        Value: 10.1016/j.scitotenv.2024.174582
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      – TitleFull: Uptake of zinc from the soil to the wheat grain: Nonlinear process prediction based on artificial neural network and geochemical data.
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              Text: 2024 Oct 15
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