Site-specific management of immature oil palm on peat: GPS, GIS and geostatistical approach / James Lopaz Luhum

• Main Author: Luhum, James Lopaz
• Format: Thesis
• Language: English
• Published: 2004
• Subjects: Analytical chemistry
• Online Access: http://ir.uitm.edu.my/id/eprint/27606/1/TM_JAMES%20LOPAZ%20LUHUM%20AS%2004_5.pdf; http://ir.uitm.edu.my/id/eprint/27606/

Peat is considered as a problem soil in tropical countries due to the very acidic nature, low bulk density, low bearing capacity, high loss of ignition and poor .structure. Comprehensive and sustainable peat management could increase productivity and economic return. Over the past 2-4 years, recent achievements by site-specific management approach significantly foster, spur and sustain price of commodity crops in global market. As a matter of fact, modem technology and good agronomic practices if worked in parallel, can benefit the agriculture industry. In line with current demand for food and environmental constraints, this is the right time to treat crops with precise nutrients and specific treatments. In this study, approximately 310 soil samples were taken at the depth of 0-15 em and 153 plant tissues were collected from the oil palm trees. A geostatistical sampling was conducted along the palms rows (within and in between the palm nucleus). Based on the data analysis, it showed that the coefficient of variations (CV's) for certain parameters indicated an extreme variability within the field i.e. exchangeable potassium, exchangeable magnesium and exchangeable calcium compared to other parameters. Positive correlation coefficients were obtained from the analysis particularly in total nitrogen with organic carbon content, phosphorus with exchangeable potassium, soil pH with exchangeable potassium, soil pH with exchangeable magnesium, soil pH with exchangeable calcium, exchangeable potassium with exchangeable magnesium, exchangeable potassium with exchangeable calcium and exchangeable magnesium with exchangeable calcium. Obviously, the spatial variability for each parameter under study was classified according to the nutrient level in soils and plant tissues. In addition, the best fit model was developed to predict the spatial variability of data. It is understood that, a high variability would result in a considerable amount of nutrients required for oil palm growth whereas low variability would results in lesser amount of nutrient available for the palms. In order to get a precise estimation on field management zone, the spatial maps were digitized from raster to vector image. At the end of the study, this intelligent system (GPS, GIS and Geostatistical) would help modern planters and oil palm growers to apply the input at right amount, time, place and way in the field. Hence, it could help to prevent input wastage particularly fertilizers and minimize the environmental risk.