The effect of land use on soil quality in Giriwoyo Sub-district, Wonogiri Regency
Mujiyo Mujiyo, Yosua Yoga Setyawan, Aktavia Herawati, Hery Widijanto
Abstract
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Mujiyo Mujiyo, Yosua Yoga Setyawan, Aktavia Herawati, Hery Widijanto
Abstract
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Determination of soil quality in Giriwoyo Sub-district, Wonogiri Regency, will generate a Soil Quality Index which can be used as a reference for soil cultivation for optimal productivity. This research was a descriptive exploratory with a survey approach. The survey area consisted of 12 land mapping units (LMU) with 3 replications for each LMU. Determination of LMU based on soil type, land use, slope and rainfall. The parameters used were BD (bulk density), porosity, organic C, pH, CEC (cation exchange capacity), BS (base saturation), available P, available K, total N, and MBC (microbial biomass carbon) that represented the physical, chemical and biological properties of the soil. Principal Component Analysis (PCA) analysis was performed to obtain the Minimum Data Set (MDS). The Soil Quality Index (SQI) at each LMU was calculated by multiplying the PCA result score (Wi) with the score for each selected indicator (Si). The result showed that the Soil Quality Index at each LMU was low. The highest Soil Quality Index was found in fields land use with an SQI of 0.34. The soil indicator that limited the soil quality was available P.
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Determination of soil quality in Giriwoyo Sub-district, Wonogiri Regency, will generate a Soil Quality Index which can be used as a reference for soil cultivation for optimal productivity. This research was a descriptive exploratory with a survey approach. The survey area consisted of 12 land mapping units (LMU) with 3 replications for each LMU. Determination of LMU based on soil type, land use, slope and rainfall. The parameters used were BD (bulk density), porosity, organic C, pH, CEC (cation exchange capacity), BS (base saturation), available P, available K, total N, and MBC (microbial biomass carbon) that represented the physical, chemical and biological properties of the soil. Principal Component Analysis (PCA) analysis was performed to obtain the Minimum Data Set (MDS). The Soil Quality Index (SQI) at each LMU was calculated by multiplying the PCA result score (Wi) with the score for each selected indicator (Si). The result showed that the Soil Quality Index at each LMU was low. The highest Soil Quality Index was found in fields land use with an SQI of 0.34. The soil indicator that limited the soil quality was available P.
Key concepts: Bulk density, Soil quality, Cation-exchange capacity, Environmental science, Soil test, Soil science, Index (typography), Soil pH