Quantitative soil color dataset for prediction of labile and persistent organic carbon in Peruvian soils.

Soil organic carbon plays a key role in climate change mitigation and exists in both labile and persistent forms. Standard quantification of both pools involves the total or partial destruction of soil samples through chemical oxidation, resulting in significant waste production and processing requirements. Given the strong association between soil organic carbon and its soil color, optical sensors offer a non-destructive and efficient alternative for its quantification. This dataset provides the analysis of labile and persistent organic carbon fractions, along with soil color data, from 329 samples randomly collected across diverse regions of Peru. Labile carbon was determined via potassium permanganate oxidation, while soil organic carbon was measured using the Walkley & Black wet combustion method. Persistent carbon was calculated as the difference between total and labile carbon. Soil colorimetric attributes were acquired with a Nix Pro 2.0 handheld spectrometer, providing comprehensive measurements in the RGB, CIELab, CIELCh, CIEXYZ, and CMYiK systems. This dataset is particularly suitable for developing pedotransfer functions that enable the preliminary estimation of labile and persistent organic carbon fractions using soil color as a rapid and cost-effective predictor.