TY - JOUR AU - Mohammed Ahmed MohammedZein AU - Adam Csorba AU - Brian Rotich AU - Phenson Nsima Justin AU - Hanaa Tharwat Mohamed AU - Erika Micheli TI - Prediction of some selected soil properties using the Hungarian Mid-infrared spectral library JO - Eurasian Journal of Soil Science VL - 12 IS - 4 PB - Federation of Eurasian Soil Science Societies SN - 2147-4249 UR - http://ejss.fesss.org/10.18393/1309753 DO - 10.18393/1309753 SP , EP - 300 - 309 KW - Mid-infrared spectroscopy, soil information monitoring system, partial least square regression, fourier transform infrared spectrometer, coefficient determination. PY - 2023 AB - Routine soil chemical and physical laboratory analysis provides a better understanding of the soil by evaluating its quality and functions. Demands for the development of national Mid-infrared (MIR) spectral libraries for predicting soil attributes with high accuracy have risen substantially in the recent past. Such MIR spectral library is usually regarded as a fast, cheap and non-destructive technique for estimating soil properties compared to laboratory soil analysis. The main objective of this research was to assess the performance of the Hungarian MIR spectral library in estimating four soil properties namely: Cation Exchange Capacity (CEC), Exchangeable Mg and Ca and pH water at different scenarios. Archived soil samples were scanned and spectra data were saved in the Fourier transform infrared spectrometer OPUS software. Preprocessed filtering, outlier detection and calibration sample selection methods were applied to the spectral library. MIR calibration models were built for soil attributes using partial least square regression method and the models were validated with sample predictions. R2, RMSE and RPD were used to assess the goodness of calibration and validation models. MIR spectral library had the ability to estimate soil properties such as CEC and exchangeable Ca and Mg through various scale models (national, county and soil type). The findings showed that the Hungarian MIR spectral library for estimation of soil properties has the ability to provide good information on national, county and soil type scales at different levels of accuracy. ER -