Abstract
Basal stem rot disease (BSR) in oil palm plants is caused by the Ganoderma boninense (G. boninense) fungus. BSR is a major disease that affects oil palm plantations in Malaysia and Indonesia. As of now, the only available sustaining measure is to prolong the life of oil palm trees since there has been no effective treatment for the BSR disease. This project used an ALOS PALSAR-2 image with dual polarization, Horizontal transmit and Horizontal receive (HH) and Horizontal transmit and Vertical receive (HV). The aims of this study were to (1) identify the potential backscatter variables; and (2) examine the performance of machine learning (ML) classifiers (Multilayer Perceptron (MLP) and Random Forest (RF) to classify oil palm trees that are non-infected and infected by G. boninense. The sample size consisted of 55 uninfected trees and 37 infected trees. We used the imbalance data approach (Synthetic Minority Over-Sampling Technique (SMOTE) in these classifications due to the differing sample sizes. The result showed backscatter variable HV had a higher correct classification for the G. boninense non-infected and infected oil palm trees for both classifiers; the MLP classifier model had a robust success rate, which correctly classified 100% for non-infected and 91.30% for infected G. boninense, and RF had a robust success rate, which correctly classified 94.11% for non-infected and 91.30% for infected G. boninense. In terms of model performance using the most significant variables, HV, the MLP model had a balanced accuracy (BCR) of 95.65% compared to 92.70% for the RF model. Comparison between the MLP model and RF model for the receiver operating characteristics (ROC) curve region, (AUC) gave a value of 0.92 and 0.95, respectively, for the MLP and RF models. Therefore, it can be concluded by using only the HV polarization, that both the MLP and RF can be used to predict BSR disease with a relatively high accuracy.
Highlights
IntroductionOil palm (Elaeis guineensis) from the Palmae family, is a major crop in Indonesia and Malaysia, which are the main export products of these countries in the agricultural sector
There has been no effective treatment for the Basal Stem Rot (BSR) disease and the current sustaining measures can only extend the life of oil palm trees [5,6,7]
The success rate (%), balanced accuracy (BCR) (%) and AUC of the non-infected and infected by G. boninense are illustrated in a heat map shown in Figures 4–6, respectively
Summary
Oil palm (Elaeis guineensis) from the Palmae family, is a major crop in Indonesia and Malaysia, which are the main export products of these countries in the agricultural sector. Oil palm trees in SouthEast Asian countries, such as Malaysia, are exposed to various fungi attacks, with the most common fungus being the G. boninense, which results in the Basal Stem Rot (BSR) disease [2]. The G. boninense attack results in a reduction of production yield that can eventually lead to tree mortality [3]. This disease has been one of the major culprits in the palm oil yield reduction throughout most of the production areas in the country [4]. There has been no effective treatment for the BSR disease and the current sustaining measures can only extend the life of oil palm trees [5,6,7]
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