Utilizing the infrared technology to characterize soil qualities in the Democratic Republic of the Congo's South Kivu province

Abstract

A fundamental prerequisite for effective land management is an understanding of soil properties. Conventional laboratory analysis has long been used to evaluate soil qualities, but it is expensive and time-consuming. As a result, alternative, quicker, and less expensive methods for soil analysis must be developed. Particular focus has been placed on chemometrics and infrared reflectance spectroscopy in recent years. Mid-infrared (MIR) and near-infrared reflectance (NIR) spectroscopy methods are quick, easy, and non-destructive ways to measure a variety of soil characteristics. The purpose of this study is to use infrared spectroscopy to characterize soil. For soil samples taken in the Democratic Republic of the Congo's Sud-Kivu province, this approach was used to forecast the soil's pH, soil organic C, total N, exchangeable Al, Ca, Mg, and K, CEC, and texture. Using a spatially-stratified random sampling design, 530 composite soil samples were collected from two sites (Burhale and Luhihi) at two depths (0–20 and 20–40 cm) over a 100 km2 area. It takes roughly two minutes to analyze a soil's MIR spectrum after minimal sample preparation. Disparities in soil depth and land use (cultivated versus non-agricultural) were assessed between the two sites. Standard wet chemistry techniques were used to evaluate a random subset of the samples (10%), and calibration models were created utilizing MIR data to estimate the soil parameters for the entire collection of soil samples. The partial least squares regression (PLS) approach produced solid predictions for all parameters with acceptable coefficients of determination ranging from 0.71 to 0.93. IR demands a large initial expenditure, despite being inexpensive for assessing soil parameters. Therefore, in order to make this technology usable in underdeveloped nations, technical and material help is required.