A deep network prediction model for heavy metal cadmium in the rice supply chain-Reference-Cited by-同舟云学术

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A deep network prediction model for heavy metal cadmium in the rice supply chain

Published:2021-12 Issue:2 Volume:1 Page:196-202
ISSN:2772-5669
Container-title:Journal of Future Foods
language:en
Short-container-title:Journal of Future Foods

Author:

Jin Xuebo,Zhang Jiashuai,Wang Xiaoyi,Zhang Xin,Guo Tianyang,Shi Ce,Su Tingli,Kong Jianlei,Bai Yuting

Funder

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Nutrition and Dietetics,Food Science,Agricultural and Biological Sciences (miscellaneous)

Reference30 articles.

1. The bioconcentration ability of heavy metal research for 50 kinds of rice under the same test conditions;Xie;Environ. Monit. Assess.,2016

2. Review of the distribution and detection methods of heavy metals in the environment;Jin;Anal. Methods,2020

3. Optimising the configuration of food supply chains;Li;Int. J. Prod. Res.,2020

4. Development of a predictive model for lead, cadmium and fluorine soil-water partition coefficients using sparse multiple linear regression analysis;Nakamura;Chemosphere,2017

5. The evaluation on the cadmium net concentration for soil ecosystems;Yao;Int. J. Environ. Res. Public Health,2017

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1. Quantitative Soil Characterization for Biochar–Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization;Toxics;2024-07-24

2. Difference in Cd accumulation among varieties with different growth duration corresponding to typical agro-climate condition in rice ratooning system;Frontiers in Plant Science;2024-05-08

3. An electrochemical aptasensor based on catalytic hairpin self-assembly and co-amplification of AuPd/Fe-MOF and Au/Cu2O for ultrasensitive detection of Cd2+;Chemical Papers;2023-09-25

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