Evaluation of various approaches to predict cadmium bioavailability to rice grown in soils with high geochemical background in the karst region, Southwestern China

Wen, Yubo; Li, Wei; Yang, Zhongfang; Zhuo, Xiaoxiong; Guan, Dong-Xing; Song, Young-Chae; Guo, Chao; Ji, Junfeng

doi:10.1016/j.envpol.2019.113645

Cited by 145 publications

(45 citation statements)

References 49 publications

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“…High amounts of Cd in the extractable fractions reflect not only high bioavailability but also high levels of anthropogenic pollution (Zhong et al, 2011). Compared with the results of a previous investigation in an area with naturally occurring Cd backgrounds in a karst region (Wen et al, 2020), the results showed much higher Cd solubility and availability in the soil. These findings could be attributed to the anthropogenic input of Cd into the soil in addition to the soil properties, especially the long‐term intensive smelting activities that had occurred there (Briki et al, 2015; X. D. Wei et al, 2020; Zhou et al, 2020).…”

Section: Resultscontrasting

confidence: 90%

“…The geochemical behavior of carbonate bedrock relative to other soil parent rocks (e.g., clastic rock) is characterized by rocks with higher content of Ca (C. Li et al, 2021;Samecka-Cymerman et al, 2011;. The release of Ca ion during the natural process of weathering and pedogenesis of carbonate rocks can result in a competitive effect, which inhibits the migration of soluble Cd in soils and, thus, hampers Cd uptake by crops (Wen et al, 2020). Apart from the soil CEC and Ca soil , other soil factors, such as DOC, SOM, Fe 2 O 3 , and Al 2 O 3 , failed to significantly improve the model fit and were therefore excluded.…”

Section: Factors Affecting CD Accumulation In Maize Grainmentioning

confidence: 99%

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Evaluation of Cadmium Transfer from Soil to the Human Body Through Maize Consumption in a Cadmium Anomaly Area of Southwestern China

Duan

Zheng

Luo

et al. 2021

Enviro Toxic and Chemistry

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Evaluating the bioavailability, bioaccessibility, and transferability of cadmium (Cd) in soil-grain-human systems is essential in areas with a Cd anomaly in the karst region of southwestern China. In the present study, the main controlling factors and prediction models for Cd transfer in a soil-grain-human system were investigated in a typical area where natural processes and anthropogenic activities interact in the karst region of southwestern China. The environmental availability of Cd (diethylenetriaminepentaacetic acid-and CaCl 2 -extractable Cd [Cd CaCl2 ]) in the soil varies significantly because of the diversity of soil properties. However, Cd concentrations in the maize grain were significantly related only to the Cd CaCl2 concentrations in the soil (r = 0.595, p < 0.01), indicating that soil Cd CaCl2 is a good indicator for evaluating Cd uptake by maize grain. Of all the measured soil properties, the soil cation exchange capacity (CEC) and the soil calcium (Ca soil ) were the most important factors influencing Cd accumulation in the soil-maize grain system. A transfer model combining Cd CaCl2 , soil CEC, and Ca soil was sufficiently reliable for predicting Cd accumulation in the maize grain (R 2 = 0.505). Although there is room for improvement regarding the prediction performance of the chain model combining soil Cd CaCl2 with Ca soil to predict the bioaccessible Cd concentration in maize grain (R 2 = 0.344 for the gastric phase and R 2 = 0.356 for the gastrointestinal phase), our findings provide a useful reference to further explore a model that can be used for a relatively rapid and reliable estimation of dietary Cd exposure for specific regions prior to crop harvest.

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Section: Resultscontrasting

confidence: 90%

Section: Factors Affecting CD Accumulation In Maize Grainmentioning

confidence: 99%

Evaluation of Cadmium Transfer from Soil to the Human Body Through Maize Consumption in a Cadmium Anomaly Area of Southwestern China

Duan

Zheng

Luo

et al. 2021

Enviro Toxic and Chemistry

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“…Finally, in our current study, the model was built using the total PTE content as one of the core covariates. However, the available form of PTEs in soil was reported to be more closely related to the PTEs absorbed by crops from the soil [39,[107][108][109][110]. Therefore, future studies should employ the available form of PTEs in soil for constructing the model, instead of the total PTE content.…”

Section: Limitations and Perspectivesmentioning

confidence: 99%

Predicting Bioaccumulation of Potentially Toxic Element in Soil–Rice Systems Using Multi-Source Data and Machine Learning Methods: A Case Study of an Industrial City in Southeast China

Xie

Zhu³

et al. 2021

Land

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Potentially toxic element (PTE) pollution in farmland soils and crops is a serious cause of concern in China. To analyze the bioaccumulation characteristics of chromium (Cr), zinc (Zn), copper (Cu), and nickel (Ni) in soil-rice systems, 911 pairs of top soil (0–0.2 m) and rice samples were collected from an industrial city in Southeast China. Multiple linear regression (MLR), support vector machines (SVM), random forest (RF), and Cubist were employed to construct models to predict the bioaccumulation coefficient (BAC) of PTEs in soil–rice systems and determine the potential dominators for PTE transfer from soil to rice grains. Cr, Cu, Zn, and Ni contents in soil of the survey region were higher than corresponding background contents in China. The mean Ni content of rice grains exceeded the national permissible limit, whereas the concentrations of Cr, Cu, and Zn were lower than their thresholds. The BAC of PTEs kept the sequence of Zn (0.219) > Cu (0.093) > Ni (0.032) > Cr (0.018). Of the four algorithms employed to estimate the bioaccumulation of Cr, Cu, Zn, and Ni in soil–rice systems, RF exhibited the best performance, with coefficient of determination (R2) ranging from 0.58 to 0.79 and root mean square error (RMSE) ranging from 0.03 to 0.04 mg kg−1. Total PTE concentration in soil, cation exchange capacity (CEC), and annual average precipitation were identified as top 3 dominators influencing PTE transfer from soil to rice grains. This study confirmed the feasibility and advantages of machine learning methods especially RF for estimating PTE accumulation in soil–rice systems, when compared with traditional statistical methods, such as MLR. Our study provides new tools for analyzing the transfer of PTEs from soil to rice, and can help decision-makers in developing more efficient policies for regulating PTE pollution in soil and crops, and reducing the corresponding health risks.

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“…One of the most prominent applications is the comparison of the amount of metal uptake by plants vs the amount of this metal in adjacent soil by DGT devices, since understanding the metal bioavailability in agricultural soils is key for food security purposes. In this context, the studies developed in foods are outstanding, such as rice (Tian et al 2008;Liu et al 2012;Williams et al 2012;Li et al 2018;Ma et al 2020;Peng et al 2020;Wen et al 2020), potatoes (Pérez and Anderson 2009a), spinach (Almås et al 2006), onions (Yi et al 2020) and lettuce (Koster et al 2005;Cornu and Denaix 2006;Agbenin and Welp 2012;Turull et al 2019b).…”

Section: Studies In Aquatic Systems Mercury Speciesmentioning

confidence: 99%

Diffusive gradients in thin films for the measurement of labile metal species in water and soils: a review

et al. 2021

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The determination of the concentration of an environmental pollutant is not sufficient to assess the related health risk because this pollutant may not be bioavailable. Therefore, methods to determine pollutant bioavailability are more relevant to assess toxicity than measuring the total concentration. For instance, the diffusive gradient in thin films (DGT) is an in situ dynamic technique used to measure the concentration of labile compounds in the environment. Here we review the latest developments achieved in speciation and bioavailability of metals and metalloids using this technique. We detail the technique, common binding agents and diffusive gels. We give laboratory procedures to prepare the gels, and we explain calculations using the DGT-induced fluxes in soils (DIFS) modeling. DIFS models can predict the resupply capacities from soils to porewater, and the uptake of trace elements by plants. Procedures for in situ field deployments, including issues of biofilm growth, are also discussed.

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Evaluation of various approaches to predict cadmium bioavailability to rice grown in soils with high geochemical background in the karst region, Southwestern China

Cited by 145 publications

References 49 publications

Evaluation of Cadmium Transfer from Soil to the Human Body Through Maize Consumption in a Cadmium Anomaly Area of Southwestern China

Evaluation of Cadmium Transfer from Soil to the Human Body Through Maize Consumption in a Cadmium Anomaly Area of Southwestern China

Predicting Bioaccumulation of Potentially Toxic Element in Soil–Rice Systems Using Multi-Source Data and Machine Learning Methods: A Case Study of an Industrial City in Southeast China

Diffusive gradients in thin films for the measurement of labile metal species in water and soils: a review

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