Replication Data for: Soil Properties and Vis–NIR Reflectance Dataset in Andean Highland and Rainforest Agroecosystems

This dataset corresponds to a study that evaluated the use of visible and near-infrared (Vis–NIR) spectroscopy combined with machine learning (ML) algorithms to predict soil fertility-related properties in two contrasting agroecological regions of Peru: the Highlands and the Rainforest. A total of 297 soil samples were analyzed using portable spectroradiometers covering a spectral range of 350–2500 nm. Spectral preprocessing techniques, including Savitzky–Golay smoothing, first derivative transformation, and band depth normalization, were applied.