فهرست مطالب n. rasooli

Soil classification is useful to better understand and manage soils. The objective of the present research was to compare the capability of Soil Taxonomy (2014) and WRB (2015) systems to describe and classify soils in Lut Desert. Marginal and central parts of Lut with typical aridic/thermic and extreme aridic/hyperthermic soil moisture/temperature regimes were selected. Twelve representative pedons on alluvial fan, plain, rock pediment, Gandom Beryan lava plateau, and playa were described and sampled. Results of the study clearly showed that the WRB system was more capable to reflect soil forming processes. However, it is recommended that anhydritic qualifier to Solonchaks, Solonetz, and Gypsisols; aquatic qualifier to Solonchaks and Solonetz; and abruptic, leptic, and paralithic qualifiers to Solonchaks be added. The ST system has not been successful in expressing soil forming processes because this classification system considers only two great groups for saline soils and gives priority to Salids in comparison to the other suborders of Aridisols. That is why Petrosalids, Gypsisalids, Natrisalids, and Argisalids great groups and Anhydritic Natrisalids, Anhydritic Argisalids, Anhydritic gypsisalids, Anhydritic Petrosalids, Calcic Natrisalids, Calcic Argisalids, Calcic Gypsisalids, Natric Petrosalids, Natric Haplosalids, Natric Gypsisalids, Petrogypsic Petrosalids, and Epipetrosalic Aquisalids subgroups are suggested to be added to Soil Taxonomy system. Meanwhile, definition of anhydritic horizon, considering textural difference in strongly contrasting particle size classes of family level, and aquic conditions in playa were among the strong points of Soil Taxonomy. It is also suggested to remove (or adopt) colour (Hue) requirement of anhydritic horizon in ST system.

Soil spectroscopy in the visible and near infrared (Vis-NIR) range has widely been used as a rapid, cost-effective, and non-destructive technique to predict soil properties. Since little data is available about soil properties determined by using this technique, the present research was carried out to evaluate the efficiency of Vis-NIR spectroscopy to estimate several soil properties in Bardsir area, Kerman Province. About 150 complex surface soil samples were collected from four different land uses from depth of 0-20 cm. Soil organic carbon, equivalent calcium carbonate, pH, and the amount of silt, clay and sand particles were measured by routine laboratory methods. Reflectance spectra were obtained from air-dried samples under controlled laboratory conditions using an ASD FieldSpec Pro spectroradiometer in 350-2500 nm wavelength range. Partial least squares regression was used for calibration of spectral and laboratory data using cross validation. Coefficient of variation for organic carbon, equivalent calcium carbonate, sand, silt, clay, and pH values were 0.68, 0.62, 0.64, 0.66, 0.3, and 0.01, respectively. Based on RPD values (Ratio of Prediction to Deviation), the precision of the prediction model for sand and silt contents was quite suitable, and for organic carbon and equivalent calcium carbonate it was suitable. [H1] However, the predictions of the model for clay content and pH were poor.Furthermore, standard normal variate (SNV) was the best pre-processing method to predict organic carbon, whereas, first derivative with SG smoothing (FD-SG) showed better estimation for carbonate, sand, and silt. Consequently, Vis-NIR spectroscopy is capable of predicting several soil properties at the same time. As the model accuracy is acceptable, it has the potential to substitute conventional laboratory analyses of selected soil properties.