Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 7/1/2011
Publication Date: 8/7/2011
Citation: Sheridan, A.H., Sudduth, K.A., Kitchen, N.R., Kremer, R.J. 2011. Estimation of soil quality characteristics using reflectance spectroscopy. ASABE Annual International Meeting, August 7-10, 2011, Louisville, Kentucky. Paper No. 1111544. Interpretive Summary: Rapid estimation of soil quality is needed for determining and mapping soil variability for site-specific management. It is important to track changes in the soil so that the quality and productivity of the soil can be maintained. One technology that can fulfill this need is sensing of light reflected from the soil in the visible and near infrared wavelength bands. Optical sensing has potential to replace traditional laboratory testing, which is often slow and expensive. The goal of this study was to use optical reflectance to detect soil properties which affect soil quality, including soil organic carbon and total nitrogen. Soil samples were taken from plots established to study the effect of topsoil thickness on crop grain and switchgrass biomass production. These samples were scanned with a laboratory spectrometer in a field-moist and oven-dried condition to compare the results of the two methods. Both field-moist and dried soil estimates were quite good for soil organic carbon, total nitrogen, and particulate organic matter carbon and nitrogen, which have been found to be sensitive soil quality indicators. Other factors were not as well estimated. Although field-moist results were not quite as accurate as dried-sample reflectance sensing, results showed that oven-drying could be eliminated without a large decrease in accuracy. These results give an indication that in-situ reflectance sensing may be a viable option for estimating soil quality.
Technical Abstract: Site-specific management is an effective method for optimizing crop production while maintaining soil quality. Management of soil quality requires measurement and mapping of observed variability across fields. One drawback is that understanding soil variability requires a large number of slow, expensive traditional soil tests. Recently, however, sensor-based approaches including reflectance spectroscopy have been proposed as quicker, easier alternatives. This study tested the ability of visible and near-infrared reflectance spectroscopy to estimate total carbon (C), total nitrogen (N), particulate organic matter (POM)-C, POM-N, and other soil quality factors. Samples were taken from 32 plots in Columbia, MO with a wide variation in topsoil depths and assumed differences in soil quality. Soil samples were scanned with a laboratory spectrometer in both field-moist and oven-dried conditions. Statistical calibrations were developed relating reflectance data to conventional lab analysis. Results showed that total C and N models were highly predictive, with R2 as high as 0.97 for C and 0.91 for N. Estimations of other soil quality factors were not as accurate, but estimates of some properties, including Mg and CEC were of good accuracy, with R2 of 0.83 and 0.74, respectively. This research showed that spectroscopic analysis of field-moist soil is a viable option for estimating several important soil quality factors.