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  1. 15 de abr. de 2023 · Rapid and accurate prediction of metal bioaccumulation in crops are important for assessing metal environmental risks. We aimed to incorporate machine learning modeling methods to predict heavy metal contents in rice crops and identify influencing factors. We conducted a field study in Jiangsu province, China, collecting 2123 pairs ...

  2. 23 de mar. de 2023 · Long-term consumption of rice containing heavy metal(loid)s poses significant risks to public health, which can be scientifically evaluated through food safety assessment.

  3. 1 de jul. de 2023 · The study was conducted to characterize heavy metal translocation from soil to rice at the filling, doughing and maturing stages, and influencing factors of their accumulation in rice. The distribution and accumulation patterns varied for metal species and growth stages.

  4. 15 de feb. de 2022 · In summary, we strongly recommend sustained supervision of heavy metals in rice, actively reducing their contents by management strategies, and timely adjusting the dietary intake of the residents to guarantee food safety and human health.

  5. 1 de jul. de 2022 · In the present study, the concentration and accumulation abilities of five heavy metals (Cd, Hg, As, Pb, Cr) in rice were assessed and their human health risk to local citizens had been evaluated. Soil and rice samples (125 samples) were collected from Guiyang (GY), Qiannan (QN), Bijie (BJ), Tongren (TR), and Zunyi (ZY) in Guizhou ...

  6. 8 de feb. de 2018 · This finding provides scientific evidence for combining rice phenology and physiological characteristics in time and space, and the method is useful to monitor heavy metal stress in rice. Heavy metal pollution of croplands is a major environmental problem worldwide.

  7. 26 de ene. de 2023 · Focused supervision and early warning of heavy metal (HM)-contaminated rice areas can effectively protect people’s livelihood security and maintain social stability. To improve the accuracy of risk prediction, an Informer-based safety risk prediction model for HMs in rice is constructed in this paper.