Prediction of Nitrogen Content in Wetland and Dryland Soils of Java Island Using Near-Infrared Spectroscopy and Multivariate Analysis

This study evaluated the potential of near-infrared spectroscopy (NIRS) combined with multivariate analysis to predict soil nitrogen (N) content in both wetland and dryland systems of Java Island, Indonesia. A total of 145 soil samples were collected across four provinces and analysed using a Frontier FT-NIR spectrometer in the 750–2500 nm range. Spectral data were pre-processed using several methods, and partial least squares regression (PLSR) models were calibrated and validated against reference Kjeldahl measurements. Among all approaches, asymmetric least-squares (ALS) baseline correction coupled with PLSR achieved the best predictive performance, with R² = 0.882, RMSE = 0.0401% N, and RPD = 2.84 on the independent validation set. Characteristic wavelengths were identified around 1400, 1900, and 2200–2330 nm, corresponding to overtone and combination bands of N–H and O–H vibrations. The results confirm that NIRS offers a rapid, non-destructive, and cost-effective alternative for soil nitrogen assessment under diverse agroecosystems. This approach can support precision nutrient management in tropical smallholder farming systems and provides a foundation for developing portable, field-ready detection tools.