Spectral prediction of soil salinity and alkalinity indicators using visible, near-, and mid-infrared spectroscopy.

Drought and the impacts of climate change have led to an escalation in soil salinity and alkalinity across various regions worldwide, including Iran. The Chahardowli Plain in western Iran, in particular, has witnessed a significant intensification of this phenomenon over the past decade. Consequently, modeling of soil attributes that serve as indicators of soil salinity and alkalinity became a priority in this region.

Modeling the spatial variation of calcium carbonate equivalent to depth using machine learning techniques.

Inorganic carbon is the largest source of carbon in terrestrial surface, particularly in arid and semiarid regions, including the Chahardowli Plain in western Iran. Inorganic carbon plays an equal or greater role than organic soil carbon in these areas, although less attention has been paid in quantifying their variability. The objective of this study was to model and map calcium carbonate equivalent (CCE) presenting inorganic carbon in soil using machine learning and digital soil mapping techniques.

Assessment of spatial distribution of soil heavy metals using ANN-GA, MSLR and satellite imagery.

This study aims to assess and compare heavy metal distribution models developed using stepwise multiple linear regression (MSLR) and neural network-genetic algorithm model (ANN-GA) based on satellite imagery. The source identification of heavy metals was also explored using local Moran index. Soil samples (n = 300) were collected based on a grid and pH, organic matter, clay, iron oxide contents cadmium (Cd), lead (Pb) and zinc (Zn) concentrations were determined for each sample.

The influences of selected soil properties on Pb availability and its transfer to wheat (Triticum aestivum L.) in a polluted calcareous soil.

Accumulated anthropogenic heavy metals in the surface layer of agricultural soils may be transferred through the food chain via plant uptake processes. The objectives of this study were to assess the spatial distribution of lead (Pb) in the soils and wheat plants and to determine the soil properties which may affect the Pb transferring from soil to wheat plants in Zanjan Zinc Town area, northwestern Iran. A total of 110 topsoil samples (0-20 cm) were systematically collected from an agricultural area near a large metallurgical factory for the analyses of physico-chemical properties and total and bioavailable Pb concentrations.