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Machine learning methods to predict cadmium (Cd) concentration in rice grain and support soil management at a regional scale
Boyang Huang, Qixin Lü, Zhi-Xian Tang, Zhong Tang, Hongping Chen, Xinping Yang, Fang-jie Zhao, Peng Wang (2023). Machine learning methods to predict cadmium (Cd) concentration in rice grain and support soil management at a regional scale. Fundamental Research, 4(5), pp. 1196-1205, DOI: 10.1016/j.fmre.2023.02.016.
Article125 days agoRapid identification of high and low cadmium (Cd) accumulating rice cultivars using machine learning models with molecular markers and soil Cd levels as input data
Zhong Tang, Ting-Ting You, Yafang Li, Zhi-Xian Tang, Miao-Qing Bao, Ge Dong, Zhong-Rui Xu, Peng Wang, Fang-jie Zhao (2023). Rapid identification of high and low cadmium (Cd) accumulating rice cultivars using machine learning models with molecular markers and soil Cd levels as input data. Environmental Pollution, 326, pp. 121501-121501, DOI: 10.1016/j.envpol.2023.121501.
Article125 days agoSoil amendments with ZnSO4 or MnSO4 are effective at reducing Cd accumulation in rice grain: An application of the voltaic cell principle
Hui Huang, Zhi-Xian Tang, Hong-Yuan Qi, Xiao-Tong Ren, Fang-jie Zhao, Peng Wang (2021). Soil amendments with ZnSO4 or MnSO4 are effective at reducing Cd accumulation in rice grain: An application of the voltaic cell principle. Environmental Pollution, 294, pp. 118650-118650, DOI: 10.1016/j.envpol.2021.118650.
Article125 days agoInterpretable machine learning models to predict cadmium in wheat for safe production and soil management
Qixin Lü, Zhi-Xian Tang, Zhong Tang, Ge Dong, Zhong-Rui Xu, Fang-jie Zhao, Peng Wang (2025). Interpretable machine learning models to predict cadmium in wheat for safe production and soil management. Fundamental Research, DOI: 10.1016/j.fmre.2025.05.001.
Article125 days ago