The Classification of Land Quality Index Using Minimum Data Set – Study in a Tropical Agroecosystem of East Java

Abstract

This study aimed to identify the factors influencing land quality in a tropical agroecosystem of Jember Regency, East Java, Indonesia, using a minimum data set approach. A principal component analysis (PCA) approach was employed to derive a minimum data set from various land parameters, including soil texture, bulk density, soil depth, pH, CEC, SOC, available P, available K, drainage, slope, surface rock, irrigation infrastructure, erosion hazard, flood hazard, annual temperature, and climate type. Data from 105 sampling locations were analysed to calculate the Land Quality Index (LQI). The study found that six parameters significantly represent land quality: SOC (30.4%), effective soil depth (19.8%), available P (17.0%), available K (13.0%), erosion hazard (10.7%), and pH (8.9%). Long-term use of organic fertiliser can enhance land quality and prevent degradation. The study was limited to the Jember Regency and may not apply directly to other regions without adaptation. The findings can guide sustainable agricultural practices and land management in tropical regions, particularly in areas facing similar climatic and soil conditions. This study provides a quantitative assessment of land quality using a minimum data set in a tropical agroecosystem, filling a gap in the literature and offering a model for other regions to adopt.

Keywords

• tropical agroecosystem
• land quality assessment
• principal component analysis
• soil health indicators
• sustainable agriculture