F. Khayamim, H. Khademi, B. Stenberg, J. Wetterlind,
Volume 19, Issue 72 (8-2015)
Abstract
Vis-NIR spectroscopy has been introduced as a non-destructive, fast, and cheap technique, with minimal sample preparation and no loss or damage to the environment. No investigation has yet been carried out to examine the ability of this method to estimate soil properties in Iran. The objective of this research was to investigate the capability of Vis-NIR spectroscopy to predict the amount of organic matter, carbonate and gypsum in surface soils of Isfahan province. A total of 248 surface soil samples were collected from the study area. Soil organic matter content, gypsum and carbonates percentages were measured by standard laboratory methods. Soil spectral analyses were performed by a field spectrometer using 350-2500 nm wavelength range. Different pre-processing methods were evaluated after recording the spectra. Partial least squares regression was used to predict soil parameters. R2 values for organic matter, carbonates and gypsum were 0.61, 0.45 and 0.8, respectively. Based on RPD (Ratio of Prediction to Deviation) values, the precision of prediction model for gypsum was quite good, and acceptable for organic matter, whereas the prediction of the model for soil carbonates was poor. Consequently, vis-NIR spectroscopy is capable of predicting some soil properties simultaneously and the model accuracy is acceptable.
R. Samiei Fard, H. Matinfar,
Volume 21, Issue 4 (2-2018)
Abstract
Reflectance spectroscopy is a fast and safe method to predict soil physicochemical and biological properties in low cost ways. Traditional methods to determine soil properties require spending a lot of time and money so that farmers are generally reluctant to use the results of laboratory measurements in soil and water management. Reflectance spectroscopy in the spectral range of 400-2500 nm (VNIR) is an alternative method for estimating the soil properties. The aim of this study was to evaluate the results of laboratory spectrometer to estimate the concentration of Lead (Pb) and Nickel (Ni) in soils irrigated with water from treatment of urban sewage sludge of Rey city and finally to compare these results with the results of measurements of atomic absorption spectrometry. In this study, the Partial Linear Square Regression (PLSR) model was used to estimate the concentration of heavy metals and Residual Mean Square Error (RMSE) was used to evaluate the performance of this model. In this research, after spectral corrections related to elimination of the water absorption bands as well as elimination of the inefficient spectrum from heavy metals estimations, the methods of estimating these elements were studied through mathematical derivation of spectral values and also the acquisition of the continuum removal spectra. The results show that the estimated values from first derivate spectra are more consistent with the results of atomic absorption spectrometers.
