Spatially varying relationships of soil Se concentration and rice Se concentration in Guangxi, China: A geographically weighted regression approach.

In recent years, the biogeochemical behavior and environmental impact of Selenium (Se) on soil-plant systems have received widespread attention, and traditional statistical methods reveal generally positive correlations between rice Se and soil Se. However, that initial positive relationship may have been obscured by local external factors. Using local scale data from the geochemical evaluation of land quality project, this work employed geographically weighted regression (GWR) to examine the spatial variation of rice Se (as the dependent variable) and soil Se (as the independent variable) in Guangxi. Strong and weak correlation coefficients occur between rice Se and soil Se, thereby indicating that their relationships are spatially varying. Guangxi is characterized by significantly positive correlations in most areas, with weak correlations mostly found in the south-western and central-eastern regions. Areas with weak correlation can be divided into two patterns: high soil Se with low rice Se and high rice Se with low soil Se. The unique patterns are correlated with distinct natural factors, particularly the abundance of Fe-rich soils in the carbonate area; by contrast, sandstone areas in central Guangxi may have been affected by anthropogenic activities. To reveal the spatially varying relationships at the local scale, we employed GWR, an effective tool that allowed us to identify the association between environmental variables and influencing factors and explore spatially varying relationships between them. This study breaks through the existing understanding that soil Se is completely positively correlated with rice Se for the first time, and concludes that their correlation is spatially variable, providing an effective approach for the study of complex relationships.

Identification of the spatial patterns and controlling factors of Se in soil and rice in Guangxi through hot spot analysis.

Selenium (Se) is essential to human health, anti-cancer, possessing antioxidant, and antiviral properties. In this study, the spatial patterns of rice Se and their varying relationship with soil Se on a regional scale were studied using hot spot analysis for the agricultural soils in Guangxi. According to the hot and cold spot maps, rice Se correlates positively with soil Se in Guangxi agricultural soils. High rice Se accompanies high soil Se in the central part of Guangxi (e.g., Liuzhou, Laibin), and low rice Se is in line with low soil Se in the western part (e.g., Baise). However, the hot spot analysis maps indicate that southwestern Guangxi exhibits a special characteristic of low rice Se with high soil Se (e.g., Chongzuo). This special pattern is strongly associated with the high concentrations of Fe2O3 (ferromanganese nodules) in the carbonate rock area. The hot spot analysis proves useful in revealing the spatial patterns of rice Se in Guangxi and identifying the hidden patterns.

A process-based model for describing redox kinetics of Cr(VI) in natural sediments containing variable reactive Fe(II) species.

Sediment-associated Fe(II) is a critical reductant for immobilizing groundwater contaminants, such as Cr(VI). The reduction reactivity of sediment-associated Fe(II) is dependent on its binding environment and influenced by the biogeochemical transformation of other elements (i.e., C, N and Mn), challenging the description and prediction of the reactivity of Fe(II) in natural sediments. Here, anaerobic batch experiments were conducted to study the variation in sediment-associated Fe(II) reactivity toward Cr(VI) in natural sediments collected from an intensive agricultural area located in Guangxi, China, where nitrate is a common surface water and groundwater contaminant. Then, a process-based model was developed to describe the coupled biogeochemical processes of C, N, Mn, Fe, and Cr. In the process-based model, Cr(VI) reduction by sediment-associated Fe(II) was described using a previously developed multirate model, which categorized the reactive Fe(II) into three fractions based on their extractabilities in sodium acetate and HCl solutions. The experimental results showed that Fe(II) generation was inhibited by NO3- and/or NO2-. After NO3- and NO2- were exhausted, the Fe(II) content and its reduction rate toward Cr(VI) increased rapidly. As the Fe(II) content increased, the three reactive Fe(II) fractions exhibited approximately linear correlations with aqueous Fe(II) concentrations ( [Formula: see text] ), which was probably driven by sorptive equilibrium and redox equilibrium between aqueous and solid phases. The model results indicated that the reaction rate constants of the three Fe(II) fractions (kn) significantly increased with incubation time, and log(kn) correlated well with [Formula: see text] [ [Formula: see text] , [Formula: see text] and [Formula: see text] ]. The numerical model developed in this study provides an applicable method to describe and predict Cr(VI) removal from groundwater under dynamic redox conditions.

Transferability of heavy metal(loid)s from karstic soils with high geochemical background to peanut seeds.

Globally distributed karstic soils are characterized by the high accumulation of heavy metal(loid)s, such as Cd. Biogeochemistries and transferability of metal(loid)s in such soils are notably different from that in soils of anthropogenic pollution as evidenced by increasing studies about rice and maize. To solve the question about metal(loid) background and transferability in the system of karstic soils and crops with underground fruits, we designedly collected 246 paired soil-peanut seed samples in a world-famous karstic region in Southwestern China covering an area of 98,700 km2. The concentrations of eight regulatory metal(loid)s (Cd, As, Cr, Cu, Hg, Ni, Pb, and Zn) in soil samples exceeded current standards to different degrees, demonstrating a typical high background. However, the transferability of metal(loid)s from soils to peanut seeds is quite low, resulting in a low exceedance rate of metal(loid)s (Cd, 12.2% and Pb, 1.2%) in seeds ("seed metal(loid)s"), in accordance with the results that metal(loid)s in soils mostly distributed in the inert/residual fractions. Based on the distinct response characteristics of peanut seed metal(loid)s to soil status from rice/maize grain metals, a model was further developed for effectively predicting the concentration of Cd in peanut seeds. Collectively, this study provides a basis for the assessment of soil environmental quality and safety zoning of upland field in karst areas.

Zinc concentration prediction in rice grain using back-propagation neural network based on soil properties and safe utilization of paddy soil: A large-scale field study in Guangxi, China.

Zn is an essential nutrient for humans, with crucial biological functions. However, Zn concentration in rice grains is generally low. Therefore, a cereal-based diet may lead to Zn deficiency in people, further leading to a series of health problems, such as immune and brain dysfunction. Previous studies seldom focused on the accumulation of Zn in rice grains based on large-scale field research. In the present study, a large-scale field survey of paddy (n = 40,853) and paired soil-rice samples (n = 1332) was conducted in Guangxi, China. Zn concentration in soil and rice grains was determined, and the associations of its spatial distributions with lithology, soil properties, and Mn nodules were investigated. According to the daily rice intake of different age and sex groups and the values of recommended Zn intake and tolerable Zn upper intake level recommended by National Health Commission of China, the Zn threshold value of the rice grain is 15.47-24.49 mg·kg-1. Moreover, a back-propagation neural network (BPNN) model was used to predict the Zn bioaccumulation factor (BAF) of rice grains with high accuracy. Soil Zn concentration, Mn concentration, pH, and total organic carbon derived from Pearson's correlation analysis were used as input variables in the BPNN model. Compared with the multiple linear regression model, the developed BPNN model using the training (1198 samples) and testing (134 samples) datasets showed better performance in estimating rice Zn BAF, with R2 = 0.93, normalized mean error of 0.009, normalized root mean square error of 0.21. When the BPNN model was applied to the 40,853 paddy soil samples, 85.7% of the agriculture lands were within the rice threshold values. These findings further our understanding of the development and utilization of Zn-rich rice and soil.

Transfer mechanism and bioaccumulation risk of potentially toxic elements in soil-rice systems comparing different soil parent materials.

Although the accumulation of potentially toxic elements in soil and crops has attracted widespread attention, the characteristics of the transfer and accumulation of potentially toxic elements in soil-crop systems with different soil parent materials are still not clear. Soil and crop samples were collected from agricultural regions with different soil parent materials in Guangxi, China. This study analyzed the concentrations of Cd, Zn, and Fe in the roots, straws, and seeds of rice (Oryza sativa L.) and soils with Quaternary sediments and clastic rocks as the parent materials. The concentration of several potentially toxic elements in rice tissue from the two areas followed the order of Croot> Cstraw> Cseed. The transport capability of Cd and Zn from roots to straws is higher than straws to seeds, and Fe showed a strong capability for transport from straws to seeds. In general, the transfer capacity of potentially toxic elements in the soil-rice system in the Quaternary sediments area was stronger than that in the soil-rice system in the clastic rocks area. Soil pH and minerals, which were represented by major elements, were the main factors affecting the transfer of metals from soil to seeds. This approach could help to evaluate the bioaccumulation risk of potentially toxic elements in crops in different areas quantitatively.

Soil Threshold Values for Zn Based on Soil-Rice System and Health Risk Assessment in a Typical Carbonate Area of Guangxi.

Zinc (Zn) is enriched in carbonate area related to geological genesis. To ensure safety of rice, soil threshold values of Zn in soil-rice systems were assessed based on analysis of soil-rice Zn concentration in relation to human health risk. Models for the prediction of Zn concentration of early-season and late-season rice grain were accurately established on the basis of significant partial correlations between log10 (BAFs) and log10 (soil properties). The rice threshold value ranged from 10.67 to 37.90 mg/kg, which might not suitable for male and urban residents. The soil safety threshold of early-season rice and late-season rice in carbonate area ranged from 148-200 mg/kg, 119-200 mg/kg with pH below 6.5, 148-250 mg/kg, 119-250 mg/kg with pH ranging from 6.5 to 7.5; 148-300 mg/kg, 119-300 mg/kg with pH above 7.5, respectively.

Geogenic cadmium pollution in multi-medians caused by black shales in Luzhai, Guangxi.

Cadmium (Cd) concentration was investigated in parent rocks, surrounding soil of black shales outcrop, stream water, stream sediments, paddy soil as well as rice plants. Leaching test and sequential extraction procedure were applied to evaluate Cd mobility and bioavailability in soil samples. This study aims to emphasize ecological risk of Cd induced by black shales by combining various natural medias in black shales area and control area. The black shales parent rocks have elevated Cd concentration and act as a source of Cd. The liberated Cd from black shales outcrop temporarily accumulated in the acidized surrounding soil and could arise potential adverse impacts on environment due to rainfall. Although high concentration of Cd was not detected in stream water, Cd concentrated stream sediment was a hidden toxin for surface water system. Cd in paddy soil was primarily from geogenic source and effected little by anthropogenic source. The concentration as well as mobility and bioavailability of Cd were high in paddy soil in black shales area, which lead to elevated Cd concentration in roots, shoots and grains of rice. As a result, residents in black shales area suffer increased non-carcinogenic risk of Cd via food chain.

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

Evaluating the bioavailability of Cd to rice (Oryza sativa L.) was essential in the karst region, Southwestern China, where the soils have previously been shown to be anomalously enriched in Cd through geogenic processes. In this research, we examined the bioavailability of Cd to rice samples collected from 278 sites in Guangxi province, where rice is the most widely cultivated cereal crop that is responsible for the largest human dietary exposure to Cd. Both soil chemical extraction and soil-plant transfer modelling approaches were used to predict the bioavailability to rice. Some of the soil types were highly enriched in Cd, but their bioavailability was low, since the soil carbonates raised soil pH and remarkably reduced Cd bioavailability. In contrast, acidic soils (Ca was largely leached) with relatively low total Cd, the grown rice plants accumulated higher Cd in their grains. Results from CaCl2 extraction experiments provided good predictions for Cd in rice grain grown in soils of different types. Stepwise multiple regressions revealed soil pH and soil Ca content were the dominant factors that control the transfer of Cd from soil to rice. An extended Freundlich-type model and a polynomial surface model provided good prediction for Cd in rice grains. The diffusive gradients in thin films (DGT) technique gave the best estimation of soil Cd bioavailability, whereas water-extracted soil solution Cd provided relatively poor fits. Regional soil threshold that derived using the models, can avoid exceedance of Cd in rice and thereby enable local agricultural practitioners or authorities to develop appropriate management for croplands with high Cd background.