Assessment of Soil Quality Variation Under Different Land Use Practices Using Principal Component Analysis in Nigeria’s Derived Savannah
Keywords:
Soil quality; Minimum data set (MDS); Land use type; Principal component analysis (PCA)Abstract
Soil quality assessment is essential for evaluating agroecosystem sustainability, monitoring soil degradation, and identifying effective land management practices. This study assessed the effects of different land use practices on soil quality in a derived savannah zone of Nigeria. Soil samples were collected from two depths (0–15 cm and 15–30 cm) across four land use types: arable land (AR), cashew plantation (CA), Gmelina plantation (GM), and grassland (GR). Variations in soil quality indicators among land uses and soil depths were analysed, and a minimum data set (MDS) of key indicators was selected using principal component analysis (PCA) to compute the soil quality index (SQI). Results showed that gravel content, sand, silt, total porosity, water holding capacity, exchangeable acidity, and base saturation varied significantly (P < 0.001) with the interaction of land use and soil depth. Soil quality was categorized as intermediate (0.55 < SQI < 0.70) in AR and high (SQI > 0.70) in CA, GM, and GR. The SQI values were 0.581 for AR, 0.712 for CA, 0.820 for GR, and 0.923 for GM. The primary factors limiting soil quality in arable land were low exchangeable bases, organic matter depletion, and increased bulk density. These findings suggest that intensive agricultural activities reduce soil quality, while tree-based and grassland systems promote better soil conditions. Sustainable soil management practices, including proper fertiliser use, organic amendments, and conservation-oriented land use, are recommended to enhance soil quality and long-term productivity in the region.
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