数字农科院2.0

Predicting cadmium enrichment in crops/vegetables and identifying the effects of soil factors based on transfer learning methods

文献类型： 外文期刊

作者： Rui Chen;Zean Liu;Jingyan Yang;Tiantian Ma;Aihong Guo;Rongguang Shi

作者机构：

关键词： Crop;Heavy metals;Soil available cadmium;Transfer learning;Vegetable

期刊名称： Ecotoxicology and Environmental Safety

ISSN： 0147-6513

年卷期： 2025 年 291 卷

页码：

收录情况： SCIE（2025版）

摘要： Cadmium (Cd) is present in soils and can easily migrate into plants due to its various forms. This mobility allows it to be absorbed by plant roots and accumulate in edible parts, entering the food chain and posing health risks. In some regions, insufficient sampling and research, or the limited cultivation of specific vegetables and crops, make it challenging to gather adequate data for modeling. A total of 353 pairs of soil and crop/vegetable samples were collected across three regions using a unified measurement method. These samples were utilized to build predictive models to study the relationship between soil factors and cadmium (Cd) absorption in six different crops/vegetables, followed by a unified comparison. This study compares regression and probability models and determines the best feature combination, which can retain enough information to accurately predict and prevent over-fitting caused by too many features. The best feature combination is used to apply transfer learning to cadmium enrichment in crops/vegetables. The results show that the best accuracy of the random forest probability model in the rice dataset is 0.89. The best feature combination of prediction results was found by feature optimization. This feature combination has a very good effect on the prediction of cadmium in corn / vegetables by transfer learning. The accuracy of corn, rape and radish is 0.93,0.89 and 0.81, respectively. In the case of good prediction effect of transfer learning, available Cd is the most critical function, and available Cd is positively correlated with Cd in plants. It suggests that available heavy metal significantly influence predictions in crops/vegetables. In areas with less sampling and research, selecting relevant features and using transfer learning methods is more appropriate for constructing predictive models.

分类号：

  • 相关文献

[1]蔬菜育种的基因组学. 黄三文. 2012

[2]Seasonal variation and exposure risk assessment of pesticide residues in vegetables from Xinjiang Uygur Autonomous Region of China during 2010-2014. Wu, Lipeng,Zhou, Xiaolong,Zhao, Duoyong,Feng, Ting,Zhou, Jun,Sun, Tao,Wang, Jianmei,Wang, Cheng.

[3]Outlook for Vegetable Industry in China 2014-2023. Kong, Fantao,Liang, Danhui,Shen, Chen,Wang, Shengwei,Xu, Ke,Xiong, Lu. 2015

[4]Research Scheme for Vegetable Price Transmission and the Early Warning based on Associations with Non-target Areas. Kong, Fantao,Wu, Jianzhai,Zhang, Jianhua,Han, Shuqing,Li, Huishang. 2016

[5]Research Progress of Transmission, Analysis and Early Warning of Vegetable Price. Shen, Chen. 2016

[6]Cadmium Accumulation in Vegetable Plantation Land Soils under Protected Cultivation: A Case Study. Li, Lian-Fang,Zeng Xi-Bai,Bai Ling-Yu,Mei Xu-Rong,Yang Jia-Bo,Hu Liu-Jie. 2009

[7]Residue Analysis of Forchlorfenuron in Fruit and vegetable by RP-HPLC. Zhang, Hua,Yang, Xin,Dong, Ai Jun,Ma, Ying,Wang, Zhen Yu,Yang, Lin,Zhang, Ying Chun,Yang, Xin,Wang, Jing. 2010

[8]Rapid Analysis of Tetraconazole Residues in Fruits and Vegetables using Ethyl Acetate Extraction and Gas Chromatography-tandem Mass Spectrometry. Doug, Fengshou,Liu, Xingang,Li, Jing,Li, Yuanbo,Zheng, Yongquan,Shan, Weili.

[9]Dynamic change of pH and EC value in substrate culture using directly solid fertilizers instead of nutrient solution. Jiang, WJ,Liu, W,Yu, HJ,Zhu, DW. 2003

[10]Determination of cyantraniliprole and its major metabolite residues in vegetable and soil using ultra-performance liquid chromatography/tandem mass spectrometry. Liu, Xingang,Xu, Jun,Li, Jing,Li, Yuanbo,Zheng, Yongquan,Shan, Weili,Song, Wencheng.

[11]Rapid Screening and Simultaneous Confirmation of 64 Pesticide Residues in Vegetable Using Solid Phase Extraction-comprehensive Two-dimensional Gas Chromatography Coupled with Time-of-Flight Mass Spectrometer. Jiang Jun,Li Pei-Wu,Xie Li-Hua,Ding Xiao-Xia,Li Ying,Wang Xiu-Pin,Wang Xue-Fang,Zhang Qi,Guan Di,Li Pei-Wu,Ding Xiao-Xia,Jiang Jun,Li Pei-Wu,Li Ying,Wang Xiu-Pin,Wang Xue-Fang,Zhang Qi,Guan Di. 2011

[12]Rapid Analysis of Indoxacarb Residues in Vegetable by QuEChERS and LC-MS/MS. Shao, Hua,Jin, Mao-Jun,Jin, Fen,Huang, Yu-Ting,Wang, Jing,Li, Ying.

[13]A Comparative Study Of Biochar, M.ultiwalled Carbon Nanotubes And G raphitized Carbon Black As Quechers Absorbents For The Rapid Determination Of Six Triazole Fungicides By Uplc-Ms/Ms. Liu, Xingang,Zheng, Yongquan,Zheng, Yunxi,Wu, Xiaohu,Xu, Jun,Cao, Junli,Dong, Fengshou,Kaium, Abdul,Cao, Junli. 2019

[14]A spatial network analysis of vegetable prices based on a partial granger causality approach. Shen C.,Chi L.,Wang X.,Han S.,Zhang J.,Zhu M.. 2022

[15]Vegetable biology and breeding in the genomics era. Li, Hongbo,Yang, Xueyong,Shang, Yi,Zhang, Zhonghua,Huang, Sanwen. 2022

[16]A Circular Arc Approximation Algorithm For Cucumber Classification With Image Analysis. Jin, CQ, Cai, ZY. 2020

[17]Large differences in ammonia emission factors between greenhouse and open-field systems under different practices across Chinese vegetable cultivation. Miao T.,Wang B.,Cai A.,Ren T.,Wan Y.,Meng Y.,Li Y.. 2022

[18]Chromosome-level genome of a leaf vegetable Glebionis coronaria provides insights into the biosynthesis of monoterpenoids contributing to its special aroma. Sen Wang,Anqi Wang,Hengchao Wang,Fan Jiang,Dong Xu,Wei Fan. 2022

[19]Mitigation effects and microbial mechanism of two ecological earthworms on the uptake of chlortetracycline and antibiotic resistance genes in lettuce. Side Yang,Chenxi Lu,Cheng Qin,Chang Lu,Zheng Pan,Lixia Zhao,Mohan Bai,Xiaojing Li,Yang Sun,Liping Weng,Yongtao Li. 2023

[20]Editorial: Growth and quality formation regulated by light in horticulture plants. Houcheng Liu,Jung Eek Son,Genhua Niu,Qingming Li. 2024

作者其他论文 更多>>