Development of soil spectroscopy models for the Western Highveld region, South Africa: Why do we need local data?

Abstract The increasing global demand for sustainable agriculture requires accurate and efficient soil analysis methods. Conventional laboratory techniques are often time‐consuming, costly and environmentally damaging. To address this challenge, we developed and validated locally calibrated mid‐infrared (MIR) spectroscopy models for predicting key soil properties pH, phosphorus (P) and exchangeable cations in soil samples from South Africa's Western Highveld region, using a dataset of 979 soil samples and machine learning algorithms Cubist, partial least squares regression (PLSR) and random forest (RF). A subset of spectra was also submitted to the newly developed Open Soil Spectral Library's (OSSL) prediction models to determine whether global prediction models could be used for local soil property prediction. Accurate predictions for pH, calcium (Ca) and magnesium (Mg), with coefficient of determination ( R 2 ) values exceeding 0.76 were obtained with the local calibration algorithms. The predictions for P, potassium (K) and sodium (Na) did not meet the requirements for reliability. Soil spectroscopic prediction models calibrated with local soils outperformed the corresponding global prediction models considered. The OSSL prediction results were inaccurate, with a RPIQ <1, and consistently underpredicted all soil properties. Furthermore, the OSSL collection of prediction models does not include a pH (KCl) model, the routinely used pH measurement method in South Africa. These findings highlight the importance of local calibration for accurate soil property prediction and underscore the need for regional representation in global spectral libraries. This research serves as the first local calibration of MIR spectroscopy models for the Western Highveld region of South Africa and provides a foundation for future local soil property inference model development. It also serves as a potential starting point for a comprehensive South African soil spectral library that can be contributed to global spectral libraries.