Non-Destructive Detection of Asymptomatic Ganoderma boninense Infection of Oil Palm Seedlings Using NIR-Hyperspectral Data and Support Vector Machine

Siti Khairunniza-Bejo,Mahirah Jahari,Aiman Nabilah Noor Azmi,Muhamad Syahir Shahibullah

doi:10.3390/app112210878

Abstract

Breeding programs to develop planting materials resistant to G. boninense involve a manual census to monitor the progress of the disease development associated with various treatments. It is prone to error due to a lack of experience and subjective judgements. This study focuses on the early detection of G. boninense infection in the oil palm seedlings using near infra-red (NIR)-hyperspectral data and a support vector machine (SVM). The study aims to use a small number of wavelengths by using 5, 4, 3, 2, and 1 band reflectance as datasets. These results were then compared with the results of detection obtained from the vegetation indices developed using spectral reflectance taken from the same hyperspectral sensor. Results indicated a kernel with a simple linear separation between two classes would be more suitable for G. boninense detection compared to the others, both for single-band reflectance and vegetation index datasets. A linear SVM which was developed using a single-band reflectance at 934 nm was identified as the best model of detection since it was not only economical, but also demonstrated a high score of accuracy (94.8%), sensitivity (97.6%), specificity (92.5%), and area under the receiver operating characteristic curve (AUC) (0.95).

Highlights

Introduction published maps and institutional affilGanoderma boninense (G. boninense) which causes basal stem rot disease (BSR) has been identified by as the primary pathogen impacting the oil palm tree (Elaeis guineensis) and killing it [1]
G. boninense infection can be detected at an early stage even when no physical signs are present by using support vector machine (SVM) with the optimal number of wavelengths
For single-band reflectance, models developed using a linear kernel demonstrated the best performance among other kernels since it obtained a low coefficient of variance (CV) score which has shown a high consistency in the results and excellent scores in accuracy, sensitivity, and specificity with the percentage value above 90%, respectively

Summary

Introduction

Ganoderma boninense (G. boninense) which causes basal stem rot disease (BSR) has been identified by as the primary pathogen impacting the oil palm tree (Elaeis guineensis) and killing it [1]. G. boninense infection in oil palm seedlings can be seen by the presence of fruiting bodies at the bole, followed by partial yellowing of the leaves or mottling of the basal fronds and necrosis when more than 50% of the stem base has been internally destroyed [5]. The impact of diseases in plants can be reduced through proper management of cultural practices, agronomy, and phytosanitary standards. It should be implemented with the use of planting materials (seedlings) which are resistant to G. boninense [6].

Methods

Results

Discussion

Conclusion