Quantifying the Relationship between Soil Organic Carbon and Soil Color in Nebraska

Authors

Aldi J. Airori, University of Nebraska-LincolnFollow

Date of this Version

12-2022

Document Type

Thesis

Citation

Airori, A. J 2022, ‘Quantifying the Relationship between Soil Organic Carbon and Soil Color in Nebraska’, Master thesis, University of Nebraska, Lincoln.

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Natural Resource Sciences, Under the Supervision of Professor Judith K. Turk. Lincoln, Nebraska: December, 2022

Copyright © 2022 Aldi J. Airori

Abstract

Soil color is easily measured in the field and holds potential to be used as an indirect measurement of soil organic carbon (SOC). The main limitation to this approach is knowledge about the specific color-SOC relationship in a region, which often varies in relation to parent material, soil texture, climate, and land use. Furthermore, the Munsell color data is subjective in nature. The objectives of this study are: 1) to develop and evaluate the accuracy of pedotransfer functions (PTFs) for the prediction of SOC based on soil color and texture in the state of Nebraska and 2) to evaluate digital based color measurements methods as field predictors of SOC in Nebraska. To address the first objective, data were obtained from the National Soil Information System (NASIS) database. The dataset consisted of 1576 soil pedon descriptions and samples of various soil textures, Munsell color, and SOC. The second objective was addressed using digital color measurements of 50 soil samples from Kellogg Soil Survey Laboratory archive. Methods used included a portable color sensor (PCS) and smartphone cameras (SPCs). Regressions of moist Munsell value versus SOC using the NASIS data had R² = 0.23 to 0.69 for individual MLRAs. Regression developed using the PCS for three selected MLRAs had R² = 0.49 to 0.81. Various PTFs based on the NASIS data resulted in RMSE of prediction = 0.795 to 2.1. The results indicate the potential of using soil color as a predictor for SOC, especially when PCS are used to measure soil color.

Advisor: Judith Turk