The Effect of Sample Grinding on Color-based Predictions of Soil Organic Carbon

Authors

Mason Rutgers, University of Nebraska - LincolnFollow

Date of this Version

4-2024

Document Type

Thesis

Citation

Rutgers, M. 2024. The Effect of Sample Grinding on Color-based Predictions of Soil Organic Carbon. Undergraduate Honors Thesis. University of Nebraska-Lincoln.

Comments

Copyright Mason Rutgers 2024

Abstract

Measurements of soil color are widely accessible and can be used as indirect measures of soil organic carbon (SOC). Sensor-based soil color measurements, frequently used in quantitative studies to predict SOC, often use ground and sieved soil samples for color analysis. However, it is unknown whether the extra steps of drying, crushing, and sieving a sample improve the quantitative relationship between color and SOC. This study was conducted to evaluate color-based predictions of SOC using intact, sieved (<2 mm), and fine-ground soil samples from northwest Oklahoma. Moist soil color was measured using Munsell color charts (MCCs) and a Nix Mini 3™ portable color sensor (PCS). The color of the soil samples was measured before processing, after crushing to pass through a 2-mm sieve, and after mechanical grinding to less than 0.25-mm. Using Munsell value (from the MCC) and CIEL* (from the PCS) as predictor variables, regression analyses were conducted to develop SOC predictive functions for each physical state. The resulting coefficients of determination (R2) and root mean squared errors (RMSE) were used to assess model fits for predicting SOC. Model contrasts were calculated to evaluate significant differences between each predictive model. All models exhibited strong relationships (0.56 < R2 < 0.70, 0.20 < RMSE < 0.25) between soil lightness and predicted SOC. Models built using aggregated samples measured with both MCCs (R2= 0.70, RMSE= 0.20) and the PCS (R2= 0.69, RMSE= 0.21) produced the best results. Models built using intact samples measured using the PCS did perform significantly better on samples dark in color (CIEL* < 30). These results suggest that grinding soil samples does not improve color-based predictions of SOC using MCCs and the PCS.