Click on “Download PDF” for the PDF version or on the title for the HTML version.

If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options.

Factors Affecting Soil Phosphorus and Potassium Estimation by Reflectance Spectroscopy

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  131595956,  2013 Kansas City, Missouri, July 21 - July 24, 2013. (doi: @2013
Authors:   Guotian Hu, Kenneth A. Sudduth, D Brenton Myers, Dongjian He, Manjula V. Nathan
Keywords:   Soil spectroscopy, Precision agriculture, Variable-rate fertilization, Soil nutrients, MLRAs, Direct orthogonal signal correction, Sensing.

Abstract. Visible and near infrared (VNIR) diffuse reflectance spectroscopy has potential in site-specific measurement of soil properties. However, previous studies have reported VNIR estimates of plant available soil phosphorus (P) and potassium (K) to be of variable accuracy. In this study, we used a database of over 1500 soil samples to investigate what factors influenced P and K estimation accuracy. Specifically, the effect of classifying soil samples by major land resource areas (MLRAs), cation exchange capacity (CEC) or organic matter (OM) was investigated. Additionally, calibrations using only those samples within the approximate range of interest for fertilizer application to field crops – P from 0 to 27 mg kg -1 and K from 0 to 192 mg kg -1 – were compared to calibrations using the full range of soil samples. Pretreatments of log10(1/reflectance) plus mean normalization plus median filter smoothing with or without direct orthogonal signal correction (DOSC) were investigated. Results from partial least squares regression (PLSR), principal component regression (PCR) and support vector regression (SVR) were compared. Reasonable estimates of P and K were obtained for soil samples from two Missouri MLRAs (109 and 115B) out of the eight analyzed. Model estimates were poor when soil samples were grouped by CEC or OM; however, there was some indication that VNIR estimation of P and K might be possible for soils low in OM. Accuracy was maintained when analyzing a reduced wavelength range from 1100 to 2450 nm, suggesting this narrower sensing range might be used for on-the-go sensors. PLSR provided better accuracy than PCR or SVR for both P and K. The DOSC pretreatment significantly improved P and K estimation accuracy. The results of this research provided some insight into the factors affecting the accuracy of P and K estimation by VNIR models, but additional research is needed to determine if these findings can lead to P and K estimations sufficiently accurate to guide variable-rate fertilization.

(Download PDF)    (Export to EndNotes)