Relationship between lifespan indicators and elemental background values: A case study in Guangdong Province, China

A total of 260 soil profiles were examined to investigate the spatial distribution of total soil selenium (Se) in Guangdong province, China. In the investigated area, the soil Se concentrations follow an approximately lognormal distribution. The soil Se geometric mean concentration of 0.23 mg kg(-1) is higher than that of Chinese soils; however, Se concentration varies over the study area. The baseline concentration of 0.13 to 0.41 mg kg(-1) indicates that the soil Se concentration is mostly in the range of deficiency to medium level for surface soils in Guangdong province. In A-, B-, and C-horizon, soil Se spatial distribution is correlated with the nature of the parent material, with high Se concentration mainly located in limestone and sandshale areas and low Se concentration associated with purple shale and granite areas. The spatial distribution pattern of soil Se concentrations suggests that potential Se deficiency may be an issue for human health in this province. Moreover, due to soil degradation and erosion, calculated soil Se exported into surrounding waters could reach approximately 23,000 kg yr(-1) in the study area.

Improved methods are required to assess the risks posed by the uptake of potentially toxic elements such as selenium (Se), boron (B), and molybdenum (Mo) by vegetation on contaminated sites. In order to develop such methods and assess risk, vegetation was collected from two sites on a soil-capped coal fly ash landfill near Dunkirk, New York, during June of 1991 and June and August of 1992. The mean concentrations (μg g-1 dry weight) of Se and Mo in the shoots did not exceed, respectively, 0.12 and 18.7 in bird's-foot trefoil (Lotus corniculatus L.), 0.06 and 12.1 in red clover (Trifolium pratense L.), 0.07 and 5.3 in timothy (Phleum pratense L.), and 0.09 and 2.2 in a mixture of grasses. These concentrations were greater than those in the same species harvested concurrently from a non-landfill site. The mean concentrations of B at the landfill ranged from 29 to 53 μg g-1 in the legumes and from 2 to 11 μg g-1 in the grasses, less than those at one non-landfill site but greater than those at another. Within the landfill, the concentration of Se in grasses was not correlated with the concentration of Se in soil and fly ash. The concentration of Se in grasses on both landfill sites was double that of grasses on the non-landfill site despite higher mean concentrations of Se in the upper soil (0–15 cm) on the non-landfill site. Therefore grass roots seem to be accessing Se from the ash by means of mass flow or other mechanisms. Based on our findings of significant variation in trace element uptake among species, harvests, and locations within sites, we recommend that contemporaneous transect sampling of at least two species be used to assess uptake of potentially toxic trace elements on landfills or other sites where contamination may occur.

Stratum affects the distribution of soil selenium bioavailability by modulating the soil physicochemical properties: A case study in a Se-enriched area, China

Selenium (Se) is an essential micronutrient for animals and humans. In the food chain, the intake of Se by animals and humans depends largely on Se content in plants, whereas the major source of Se in plants lies in the soil. Therefore, understanding Se bioavailability in soils for plant uptake and its controlling factors and mechanisms is important. The objective of this thesis is to study the amount, speciation, bioavailability, plant uptake and fertilization of Se in agricultural soils in the Netherlands and underlying controlling factors and mechanisms, to provide guidance for soil testing and fertilization recommendation for efficient Se management in agriculture. The majority of agricultural soils (grassland and arable land) in the Netherlands contains low total Se (i.e. in the range of Se deficient), which is predominantly present as organic Se. Only a small fraction of total Se is present as inorganic Se (mainly as selenite) and residual Se. In this thesis, the evidences of association between Se and soil organic matter in these low Se soils have been shown. The associations include: (1) the total Se content is positively correlated to soil organic matter content; (2) the solubility and extractability of Se in soils follow the solubility and extractability of soil organic C; (3) the majority of Se present in soils is in organic form, both in the soil solution and solid phase; (4) the distributions of Se and organic C in the different fractions of solid organic matter (i.e. humic acids, hydrophobic organic neutral, hydrophilic acids) and dissolved organic matter (i.e. hydrophilic acids and fulvic acids) are comparable; and (5) the Se richness in solid and dissolved organic matter are related to properties of soil organic matter from different land uses. The relatively high soil organic matter content in these low Se soils is likely responsible for these associations. In general, Se content in crops (e.g. grass and wheat) grown on grassland soils and arable land soils, respectively in the Netherlands is low due to low amount of bioavailable Se in the soils. Different soil parameters determine Se plant uptake in these low Se soils with predominantly organic Se, depending on the properties of Se-containing soil organic matter. The intensity parameter of Se-rich dissolved organic matter (DOM) in soil solution (i.e. Se to DOC ratio in 0.01 M CaCl2 extraction) determines Se plant uptake in soils containing Se-rich organic matter (e.g. potato arable land soils), whereas the buffer capacity of labile organic Se to supply Se-rich DOM in soil solution limits Se plant uptake in soils containing Se-poor organic matter (e.g. grassland soils). Further research is needed to confirm the generality of the conclusion above, because the two experiments were carried out under different conditions (pot experiment and field experiment), using different plant species (wheat and grass) and covering different soil types from different land uses (potato fields and grassland). Site-specific properties in the field in addition to soil parameters included in the current study may largely (> 50%) determine Se content in grass under field conditions, which is in contrast with the results of the pot experiment in which the soil parameter explains 88% of Se content in wheat shoots. In general, the content of Se-rich DOM in soils increases with the increase of soil pH (with the decrease of soil C:N ratio), and the amount of labile organic matter in soils that can resupply Se-rich DOM is determined by the amount of clay (and Fe-(hydr)oxide). NPK fertilization, as one of the external factors, can reduce Se plant uptake, especially in organic-rich soils. Selenium (as selenate) fertilization on grassland with N plus cattle slurry or NPK application shows a positive effect to increase Se content in grass grown on different soil types with a large range of total Se, pH, clay content and organic matter content. Selenium content in grass grown on different soil types upon Se fertilization becomes more similar than before the fertilization. The results indicate that the effectiveness of Se fertilization is only weakly modified by soil properties, probably due to the high solubility of selenate in the soils. Nevertheless, the Se fertilization tends to be slightly more effective on sandy soils than on clay and organic rich soils. This thesis has shown that the content and quality of soil organic matter play an important role in determining the amount, speciation and bioavailability of Se in low Se soils with predominantly organic Se. The results in this thesis can be used as guidance to develop soil testing and fertilization recommendation for efficient Se management, especially in low Se soils with predominantly organic Se, such as in Dutch agricultural soils.

Assessment of elemental background values and their relation with lifespan indicators: A comparative study of Jining in Shandong Province and Guanzhong area in Shaanxi Province, northern China

Selenium bioavailability in soil-wheat system and its dominant influential factors: A field study in Shaanxi province, China

Leaf pigments are key elements for plant photosynthesis and growth. Traditional manual sampling of these pigments is labor-intensive and costly, which also has the difficulty in capturing their temporal and spatial characteristics. The aim of this work is to estimate photosynthetic pigments at large scale by remote sensing. For this purpose, inverse model were proposed with the aid of stepwise multiple linear regression (SMLR) analysis. Furthermore, a leaf radiative transfer model (i.e. PROSPECT model) was employed to simulate the leaf reflectance where wavelength varies from 400 to 780 nm at 1 nm interval, and then these values were treated as the data from remote sensing observations. Meanwhile, simulated chlorophyll concentration (C ab ), carotenoid concentration (C ar ) and their ratio (C ab /C ar ) were taken as target to build the regression model respectively. In this study, a total of 4000 samples were simulated via PROSPECT with different C ab , C ar and leaf mesophyll structures as 70% of these samples were applied for training while the last 30% for model validation. Reflectance (r) and its mathematic transformations (1/r and log (1/r)) were all employed to build regression model respectively. Results showed fair agreements between pigments and simulated reflectance with all adjusted coefficients of determination ( R 2 ) larger than 0.8 as 6 wavebands were selected to build the SMLR model. The largest value of R 2 for Cab, Car and Cab/Car are 0.8845, 0.876 and 0.8765, respectively. Meanwhile, mathematic transformations of reflectance showed little influence on regression accuracy. We concluded that it was feasible to estimate the chlorophyll and carotenoids and their ratio based on statistical model with leaf reflectance data.

The influence of freeze-thaw cycles on Se migration and soil microorganisms in northeast paddy soil

Assessment of bioavailability of selenium in different plant-soil systems by diffusive gradients in thin-films (DGT)

SUMMARY: Pharmacokinetic studies were performed in 10 stable kidney transplantation patients who received microemulsion formulation (Neoral®) of cyclosporine A (CsA) twice daily. No agents having pharmacokinetic effects on CsA had been used in these patients. The values of various basic pharmacokinetic parameters were similar to those reported in Western literature. The complete area under the blood concentration–time curve (AUC) of CsA for the duration of 12 h (12‐h AUC) was determined using the linear trapezoidal rule from seven concentrations at 0, 1, 2, 4, 6, 8, and 12 h after CsA administration. The mean values of 12‐h AUC were 4603.63 ± 344.61 ng h/mL. CsA concentrations at 2 h after dosing (not the trough levels) showed the best correlation with the complete AUC (r2 = 0.9322). The abbreviated AUC of CsA was calculated either by stepwise multiple linear regression analysis or by the linear trapezoidal rule from a few sampling time points. Using stepwise multiple linear regression analysis, which was used in calculating abbreviated AUC in all previous studies, the model equation that had the highest correlation and the lowest prediction error with the complete AUC was derived by using CsA concentrations at 2 and 8 h after dosing (12‐h AUC = 4.262C2 + 8.390C8− 669.417; r2 = 0.9808, absolute prediction error = 3.97 ± 0.96). Two model equations derived using the linear trapezoidal rule provided the best correlation with the complete AUC: (1) The two time points selected model equation 12‐h AUC = 4C2 + 5C8; r2 = 0.9780, absolute prediction error = 6.41 ± 1.22). (2) The three time points selected model equation 12‐h AUC = 4C0 + 3C2 + 5C6; r2 = 0.9475, absolute prediction error = 5.00 ± 1.41). When different pharmacokinetic data sets were applied to the model equations derived using regression analysis, the values of coefficients and the constant of the regression equation had changed from the initial equation. Thus, new model equations will emerge every time the new data are applied. In contrast, the values of coefficients in the model equation calculated using trapezoidal rule were unaltered when tested by the new pharmacokinetic data set. Thus, the abbreviated AUC derived using the linear trapezoidal rule would be simpler than and superior to that obtained using stepwise multiple linear regression analysis in prediction of the complete AUC.

This study was conducted to examine the school culture and climate dimensions as contribution factors of school effectiveness. Stepwise multiple linear regression analysis was used to test the school effectiveness contribute factors. Three hundred fifty-three (353) teachers from 84 primary schools in Peninsular Malaysia from Sekolah Kebangsaan (SK) participated in this study. Data were collected using the School Culture Survey (Gruenert, 1998, School Climate Instrument (Ross and Lowther, 2003) and School Effectiveness Instrument (Lezotte & Snyder, 2011). The results of the stepwise multiple linear regression analysis show that the dimension of school culture collaborative leadership, unity of purpose, learning partnership and teacher's collaboration contributed for 47.0% variance changes of school effectiveness. The dimension of school climate which is leadership, instruction, expectations and environment contributed 54.8% variance changes of school effectiveness. The overall results of stepwise multiple linear regression analysis showed that the school climate influence more compare the school culture. Both combination significantly contributed 52.5% variance changes of school effectiveness. The cross-sectional method limits data collection to one point in time. This study adds to a better understanding of how the combinations of school culture and climate dimensions contribute in interrelated to improve school effectiveness among primary schools. The overall thrust of this empirical study, which is to investigate the contribution of both school culture and climates dimension as influence factor of school effectiveness. This study highlights to which extent the both constructs dimensions contribute in helping to improve school effectiveness indirectly in school management. To examine the dominant of school culture and climate as contributing factor of school effectiveness.

In order to find out the influencing factors of soil selenium （Se） and bioavailability of Se, 1985 soil samples and 120 sets of crop and root soil samples were collected in the hinterland of the Hetao Plain, and the characteristics of soil Se, different forms of Se, and crop Se and heavy metal content were analyzed. The results showed that approximately 5.59% of soil samples exceeded the risk screening values for soil contamination of agricultural land of GB15618-2018 standard, but the heavy metal content in crops was much lower than the standard value, suggesting that the overall risk of heavy metal pollution was low. Se had significant autocorrelation in soil and appeared enriched locally, which were mainly related to natural factors. The content of different forms of Se in root soil was ranked as： residue state > humic acid state > water soluble state ≈ strong organic state > carbonate state > ion exchange state > iron and manganese oxidation state, this result showed that the characteristics of Se in root soil were high availability state, high potential availability state, and low unavailability state compared with those of most areas in China. At the same time, the results showed that water-soluble, ion exchange, and carbonate Se of root soil were significantly correlated with Se of crops,indicating that they were effective forms that could be absorbed and utilized by plants. According to the Se content and bioconcentration factor, different crops were ranked as： white melon seeds > sunflowers > corn. By means of cluster analysis and correlation analysis, the factors affecting the total Se and bioavailability of Se in soil were studied. It was concluded that soil texture, organic matter, and pH had opposite effects on Se and bioavailability of Se in soil. Factors such as clay soil, high organic matter, and low pH degree could promote the accumulation of Se in soil but also limited the activity of available Se. Based on crop and root soil sample data, the soil Se enrichment threshold was discussed. The results demonstrated that using "ω（total Se）≥0.222 mg·kg-1" as the threshold, the proportion of soil Se enrichment was closer to the Se enrichment level of crops than others.

Diagnosis of selenium status in grazing dairy goats on the Mexican plateau

Herbage selenium (Se) concentration is generally low in Norway. It is unknown whether feeding practices on Norwegian organic farms fulfil the dietary needs of Se and vitamin E for sheep and dairy cattle. Therefore we analysed Se in soil and herbage, and Se and vitamin E in animal blood in the indoor feeding season at 14 organic dairy and 14 organic sheep farms. The herbage Se concentration was low. Approximately 50 and 35% of all samples in the first and second cut, respectively, had Se concentrations below the detection limit of 0.01 mg/kg dry matter (DM). The median (10th, 90th percentile) Se concentrations were <0.01 (<0.01, 0.03) and 0.02 (<0.01, 0.06) mg/kg DM in the first and second cuts, respectively. Whole blood Se concentrations were 0.10 (0.04, 0.15) μg/g in dairy cattle and 0.14 (0.03, 0.26) μg/g in sheep. Vitamin E concentrations were 4.2 (2.7, 8.4) mg/l in dairy cattle and 1.3 (0.9, 2.4) mg/l in sheep. None of the soil or plant variables explained the variation in herbage Se concentration, although Se in soil and plant tended to be correlated. Herbage Se concentration was inadequate to meet the dietary Se requirements. Vitamin E requirement was only met in dairy herds. We recommend Se and vitamin E supplementation to ruminants on organic farms.

Influence of Long-Term Fertilization on Selenium Accumulation in Soil and Uptake by Crops