Innovative Digital Mapping of Soil Organic Matter Content in Oil Palm Using Image Analysis

Ida Ratna Nila (Geophysics Study Program, Faculty of Science and Technology, Samudra University, Aceh 24416, Indonesia)
Rahmawati Rahmawati (Physics Study Program, Faculty of Science and Technology, Samudra University, Aceh 24416, Indonesia)
Muhammad Ari Fahril (Geophysics Study Program, Faculty of Science and Technology, Samudra University, Aceh 24416, Indonesia)
Sabrian Tri Anda (Geophysics Study Program, Faculty of Science and Technology, Samudra University, Aceh 24416, Indonesia)
Rachmad Almi Putra (Geophysics Study Program, Faculty of Science and Technology, Samudra University, Aceh 24416, Indonesia)
Fajriani Fajriani (Geophysics Study Program, Faculty of Science and Technology, Samudra University, Aceh 24416, Indonesia)
Afrahun Naziah (Geophysics Study Program, Faculty of Science and Technology, Samudra University, Aceh 24416, Indonesia)

Jurnal Ilmu Pertanian Indonesia
Vol. 31 No. 2 (2026): Jurnal Ilmu Pertanian Indonesia

The goal of this study is to use image processing technology to map the organic matter content of soil in oil palm plantations. The data set comprises photos of oil palms and bare land, as well as field measurements of pH, humidity, temperature, total dissolved solids, and electrical conductivity. Correlation analysis revealed a strong link between picture spectral components (particularly in the blue channel, r = 0.3640) and soil organic matter content. The distribution of organic matter content ranges from 4.5 to 5.5%, with an average of around 5%. The image processing-based predictive model successfully mapped the spatial variation of organic matter content with high accuracy. The mapping results demonstrate spatial variability, which can be exploited to support precision agriculture in oil palm areas. Keywords: soil organic matter, image processing, oil palm, mapping, precision agriculture