Identification of Ganoderma boninense Infection Levels on Oil Palm Using Vegetation Index

Dhimas Wiratmoko (Indonesian Oil Palm Research Institute, Medan 20158, Indonesia.)
Agus Eko Prasetyo (Indonesian Oil Palm Research Institute, Medan 20158, Indonesia.)
Retnadi Heru Jatmiko (Universitas Gadjah Mada, Yogyakarta 55281, Indonesia.)
Muhammad Arif Yusuf (Indonesian Oil Palm Research Institute, Medan 20158, Indonesia.)
Suroso Rahutomo (Indonesian Oil Palm Research Institute, Medan 20158, Indonesia.)

International Journal of Oil Palm
Vol. 1 No. 3 (2018): September 2018

Basal stem rot (BSR) is known as a deathly disease in oil palm. It can immediately cause a significant decrease in the population of oil palm per hectare. BSR is associated with infection of Ganoderma boninense. The identification of infected palms at an early stage is the key to control the disease. Manual identification by observing an individual palm in the field is the most common method; however, it is time consuming as well as laborious and expensive. A faster, less laborious, and less expensive method is by analyzing multispectral aerial photograph from unmanned aerial vehicle (UAV). A study to test this method was conducted in an oil palm plantation in Batubara region, North Sumatera. The plantation was acknowledged as an endemic area of G. boninense. The objectives of this study were to identify levels of G. boninense infection in oil palm based on spectral difference by counting the vegetation index from the multispectral image of UAV and mapping the distribution of BSR infection. Four methods were used to transform vegetation index, i.e. simple ratio (SR), normalized different vegetation index (NDVI), enhanced vegetation index (EVI) and atmospherically resistance vegetation index (ARVI). The results show that the index transformation of SR, NDVI, EVI and ARVI was able to identify the infection level of G. boninese.