Pedotransfer functions for soil organic carbon stock and soil porosity interpretation in diverse palm oil plantation soils - Riris Srigayuh Tegarningtyas Tinuntun; Widyatmani Sih Dewi; Mujiyo Mujiyo; Aktavia Herawati; Ganjar Herdiansyah; Sumani Sumani; Angger Cahyo; Bagus Guritno Widjojo; Bangun Budi Prasetyo; Zsolt Kotroczó (SAINS TANAH - Journal of Soil Science and Agroclimatology, 2025)
The accurate estimation of soil organic carbon stocks (SOCs) is crucial in sustainable oil palm plantation management. Pedotransfer functions (PTFs) serve as an essential predictive tool for enhancing the interpretation and estimation of soil organic carbon stocks (SOCs) and soil porosity. This study aims to improve the precision of SOCs and soil porosity predictions across diverse soil types within oil palm plantations through the application of PTFs. The study was conducted using a survey approach and descriptive exploration in an oil palm plantation in Seruyan District, Central Kalimantan. The study area encompassed four distinct soil types (Alfisols, Inceptisols, Ultisols, and Entisols), with six replicates for each soil type. Soil samples were collected from a depth of 0–60 cm. Statistical analyses included ANOVA, Tukey’s pairwise comparisons, correlation, and stepwise regression. The results indicated that soil types within oil palm plantations did not significantly affect SOCs but significantly impacted soil porosity. SOCs and porosity estimated using PTFs were lower than those estimated without PTFs. Specifically, SOCs analysis with PTFs ranged from 3.4 to 7.1 kg m-²; without PTFs, the range was higher, between 8.1 and 10.9 kg m-². Among the soil types, Entisols exhibited higher porosity with PTFs (51.3%), while Ultisols had the lowest porosity (37.9%). The PTFs provide better predictions for SOCs and porosity, and predictor variables that contribute the most are sand, silt, bulk density (BD), and cation exchange capacity (CEC). PTFs provide an advanced, data-driven approach to assessing SOCs and soil porosity in oil palm plantations, supporting the development of smarter, sustainable, and highly efficient management strategies.