Exploring laboratory-based spectroscopy for estimating NPK content in the hutton soils of Syferkuil Farmlands, South Africa

Abstract

This study seeks to identify the key wavelengths and spectral transformation techniques that may be used to accurately estimate soil nitrogen, phosphorus, and potassium (NPK) concentration in the Hutton soils. For this purpose, the reflectance spectra of 74 soil samples were measured in the laboratory, and the chemical properties of the soil were analysed. Pearson correlation (r), stepwise multiple linear regression (SMLR), and Partial Least Square Regression were used to model the relationships between the selected variables under study. The study findings revealed that moderate to weak correlations (r = −0.2 − 0.6) exist between wavelengths (400 − 2500 nm) and soil NPK content. Important wavelengths for accurately predicting Soil NPK content were found within visible (400 nm − 729nm), near-infrared (805 nm − 1200nm) and mid-infrared region (1375 nm to 2462 nm). The PLSR model coupled with different spectral transformations was found to be the optimal model for estimating soil NPK (RPD > 2). The introduction of the first and second derivate spectral transformation approach markedly improved all the models investigated in this study. The results retrieved from the study provide a high-accuracy prediction of soil nutrient contents, which is critical for soil fertility management and sustainable food production.

Keywords:

• Soil spectroscopy
• laboratory reflectance spectra
• NPK estimation
• soil fertility management

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author, [FM], upon reasonable request.

Additional information

Funding

The authors acknowledge the Risk and Vulnerability Science Center and department of Geography and Environmental studies, University of Limpopo for providing equipment’s and financial assistance for fieldwork and laboratory data analysis.