Assessing the distribution of cadmium under different land-use types and its effect on human health in different gender and age groups.

Cadmium (Cd) is one of the toxic elements entering the food chain in various ways, including chemical fertilizers. This study aimed to assess different amounts and forms of available Cd in soils under wheat cultivation affected by long-term use of phosphorus chemical fertilizers and also to study the rate of Cd intake by people with age and gender differences. To investigate the Cd status in wheat-cultivated lands, 105 soil samples and also 24 wheat samples were collected from three land uses of rainfed, irrigated, and control one. Phosphorus levels were also measured in soil samples to investigate the relationship between the amount of chemical fertilizer consumption and the amount of Cd. The mean values of available Cd were 0.15, 0.18, and 0.08 (mg/kg) under three land-use types of rainfed, irrigated, and control one, respectively, and the mean values of total Cd were also 1.9, 2.22, and 1.30 in the rainfed land, irrigated land, and control one, respectively. The results showed that the amount of available and total Cd in the irrigated and rainfed lands was higher than the amount of Cd in the control sample. According to the results of Cd fractionation, the highest amounts of Cd were in the residual, carbonate, organic, soluble, and exchangeable fractions, respectively. The amounts of Cd in the three parts of root, stem, and grain were 1.08, 0.65, 0.91 (mg/kg), respectively. Finally, the results showed that the rate of Cd entry into the children's body was higher than that of adults and the elderly.

Soil nutrients status affected by simple and enriched biochar application under salinity conditions.

In order to study the effect of biochar application as simple and enriched, on the soil nutrients status in the salinity conditions, a research was conducted as a factorial arrangement based on completely randomized design (CRD) with three replicates. The biochar (grape pruning residues) was applied in three levels (0, 2% biochar, and 2% enriched biochar by rock phosphate and cow manure). Also, the salinity treatment was considered in three levels (2, 4.5, and 9 dSm-1). After treating the soil, it was incubated in polyethylene containers for a 70-day period at 25 °C and 70% field capacity moisture regime. The results showed that salinity significantly affected the soil pH, electrical conductivity (EC), calcium, magnesium, sodium, basal respiration, and nitrifying bacteria frequency (P < 0.001) and chloride concentration (P < 0.01). Also, the biochar significantly affected the pH, organic carbon, concentration of total nitrogen, phosphorous, solution potassium, sodium, iron, zinc, copper, basal respiration, and nitrifying bacteria frequency (P < 0.001) of the soil. The interaction effect of biochar and salinity levels was significant on soil sodium concentration (P < 0.01) and pH (P < 0.05). In comparison with the control treatment, the enriched biochar, decreased soil pH (about 1.4%) and increased the phosphorous, iron, and zinc up to 36%, 29%, and 36%, respectively and simple biochar increased the Nitrogen and Potassium up to 46% and 48%, respectively. In general, it was concluded that both types of the biochars lowered the sodium concentration of the soil in different salinity levels due to high potential of biochar for sodium absorption which this ability may be considered in saline soils remediation.

Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks.

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55-63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE = 0.13) and PTF18 (RMSE = 0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE = 0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.

Mobility of heavy metals in sandy soil after application of composts produced from maize straw, sewage sludge and biochar: Discussion of Gondek et al. (2018).

Gondek et al. (2018) investigate the mobility of heavy metals in sandy soil after application of composts produced from maize straw, sewage sludge and biochar. The authors made a little attention to role of the soil properties and soil condition on the metals chemical behavior. In different section of the paper, the authors reported that the content of the metals extracted with water or 1 M NH4NO3 was changed compared to the control treatment affected by the mentioned biosolids. Nowadays, different researches have shown that the trace metals nature have an important role in determining their fate in presence of different treatments. In addition to, organic compounds entered to the soil due to biosolids applications have a duplicate role in trace metals mobility. Therefore, it is needed this facts are considered to interpret the measurements in the original paper. Also, whenever effects of different materials are studied on the metals mobility, the metals status in the plant tissues presents valuable information to the scientists and readers for carefully interpreting the measurements, which it is ignored by the authors.

Nutritional (Fe, Mn, Ni, and Cr) and growth responses of rice plant affected by perennial application of two bio-solids.

Trace toxic elements often restrict the land application of different bio-solids in agriculture. In order to evaluate the separate influence of the municipal solid waste compost (MSW), sewage sludge (SS) and combined application with inorganic fertilizers (chemical fertilizer (CF)) on nutritional (Fe, Mn, Ni, and Cr) and growth responses of rice plant, a research was conducted on paddy soil from 2013 to 2015. Obtained results showed that SS levels were superior to MSW in most studied traits. The maximum chlorophyll content (46.52), plant height (162.6 cm), biomass (23.33 t ha-1), soil available Fe (206.26 ppm), Ni concentration in the root (14.41 ppm) and shoots (3.16 ppm), Cr concentration in the root (12.43 ppm) and grain (3.65 ppm), and Mn concentration in grain (66.938 ppm) belonged to SS levels, specially enriched 40 t ha-1, when it was added to the soil for three continuous years. The highest 1000-grain weight (29.89 g), yield (6.86 t ha-1), harvest index (48.17%), and soil available Mn (712.7 ppm), Fe, and Ni concentration in grain (107.92 and 8.79 ppm, respectively) were recorded in 3 years of applying the enriched 40 t ha-1 MSW. Accumulation of Ni in grain in critical levels and negative effects of CF treatments on toxic element entry to soil and plant were two important findings of this research that need management.