Abstract

Understanding soil properties is an essential pre-requisite for sustainable land management. Assessment of soil properties has long been done through conventional laboratory analysis, which is costly and time consuming. Therefore, there is a need to develop alternative cheaper and faster techniques for soil analysis. In recent years, special attention has been given to Infrared Reflectance Spectroscopy and chemometrics. Near Infrared Reflectance (NIR) and mid-infrared (MIR) spectroscopy techniques are rapid, convenient and simple non-destructive techniques for quantifying several soil properties. This study aims to characterized soil based on based on infrared spectroscopy. This method were to predict soil pH, soil organic C, total N, exchangeable Al, Ca, Mg, and K, CEC and soil texture for soil samples collected in Sud-Kivu province, Democratic Republic of Congo. A total of 530 composite soil samples were taken from two locations (Burhale and Luhihi) at two depths (0-20 and 20- 40 cm) using a spatially-stratified random sampling design within an area of 100 km2. After minimal sample preparation, the MIR spectrum of a soil takes about two minutes for the analyses. Ddifferences in characteristics were evaluated between the two locations, land use (cultivated vs. non-agricultural land) and soil depth. A random subset of the samples (10%) were analyzed using standard wet chemistry methods, and calibration models developed using MIR data to estimate soil properties for the full soil sample set. Partial least squares regression (PLS) method gave acceptable coefficients of determination between 0.71 and 0.93 for all parameters hence good prediction. Though IR is cheap for analyzing soil properties it requires high investment at the beginning. There is therefore need of technical and material support to make this technology useful in developing countries.

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