Abstract
The analysis of soil organic matter (OM), total carbon (TC), and total nitrogen (TN) using traditional methods is quite time-consuming and involves the use of hazardous chemical reagents. Absorbance spectroscopy, especially near-infrared (NIR), is becoming more popular for soil analysis. This method requires little sample preparation, no chemicals, and a single spectral analysis to evaluate soil properties. Thus, this research aimed to develop an NIR spectroscopy method for the analysis of OM, TC, and TN in agricultural soils. These findings can provide a good concept of using PLS regression with NIR techniques. The method is as follows:•Topsoil (0-20 cm) samples were collected from various agricultural fields. OM, TC, and TN were analyzed using traditional methods and NIR spectroscopy.•NIR spectra were obtained using an FT-NIR spectrometer, original spectral including with Savitzky-Golay smoothing, standard normal variate (SNV) and multiplicative scatter correction (MSC) preprocessing method were used to create a predicted model through Partial Least Squares (PLS) regression with 65 % calibration, and the rest 35 % for validation.•The results showed significant relationships between measured soil properties (SOM and TC) and NIR absorbance spectra in agricultural soil (R (2) of calibration and validation higher than 0.80).