Early detection of basal stem rot disease (Ganoderma) in oil palms based on hyperspectral reflectance data using pattern recognition algorithms

Abstract

Basal stem rot (BSR) is a fatal fungal (Ganoderma) disease of oil palm plantations and has a significant impact on the production of palm oil in Malaysia. Because there is no effective treatment to control this disease, early detection of BSR is vital for sustainable disease management. The limitations of visual detection have led to an interest in the development of spectroscopically based detection techniques for rapid diagnosis of this disease. The aim of this work was to develop a procedure for early and accurate detection and differentiation of Ganoderma disease with different severities, based on spectral analysis and statistical models. Reflectance spectroscopy analysis ranging from the visible to near infrared region (325-1075 nm) was applied to analyse oil palm leaf samples of 47 healthy (G0), 55 slightly damaged (G1), 48 moderately damaged (G2), and 40 heavily damaged (G3) trees in order to detect and quantify Ganoderma disease at different levels of severity. Reflectance spectra were preprocessed, and principal component analysis (PCA) was performed on different preprocessed datasets including the raw dataset, first derivative, and second derivative datasets. The classification models: linear and quadratic discrimination analysis, k-nearest neighbour (kNN), and Naïve-Bayes were applied to PC scores for classifying four levels of stress in BSR-infected oil palm trees. The analysis showed that the kNN-based model predicted the disease with a high average overall classification accuracy of 97% with the second derivative dataset. Results confirmed the usefulness and efficiency of the spectrally based classification approach in rapid screening of BSR in oil palm.

A review of remote sensing applications for oil palm studies

“…The spectral data (ranging from 325 to 1040 nm) were normalized and smoothed before processed by a principal component analysis to detect and diagnose basal stem rot (BSR) and Ganoderma in oil palms. It was found that the k-nearest-neighbors (kNN)-based model as the best classification model (Liaghat et al 2014). Both studies show positive results where the healthy and Ganodermainfected oil palms are classified and segmented with adequate accuracy (82% and 97%, respectively).…”

“…relationship of remotely sensed data with aGB of oil palm. diagnosis of the diseases or pest infestation based on the symptoms shown at specific spots (Shafri and Hamdan 2009;Santoso et al 2011;Liaghat et al 2014). Based on the hypothesis that Ganoderma-infected oil palm shows observable symptoms at an early stage, various studies were conducted to discriminate the Ganodermainfected oil palms.…”

“…Ganoderma boninensis is a notorious disease in the oil palm industry. It is a fungal disease that rots oil palms from the inside, causing it to be structurally vulnerable and tumble during strong wind (Liaghat et al 2014). The disease is highly contagious.…”

Hyperspectral Analysis of Soil Total Nitrogen in Subsided Land Using the Local Correlation Mazimization-Complementary Superiority Method

“…Derivative processing helps to reduce the influence of low-frequency noise (Ghiyamat et al, 2013;Liaghat et al, 2014). In the reciprocal logarithm mode, spectra differences of the visible-light region can be highlighted and the influence of changes in illumination can be minimized (Wang et al, 2009) …”

Application of Ground-Based LiDAR for Analysing Oil Palm Canopy Properties on the Occurrence of Basal Stem Rot (BSR) Disease

“…Detecting BSR infection in its early stage allows palms to be treated, avoiding more extensive damage to the tree. Specific BSR disease symptoms include the canopy hanging downward (known as "skirting"), yellowing colour of the fronds, wilting green fronds and reducing frond production that causes the small size of the canopy, appearance of unopened young leaves (known as spears), fractured old fronds and fungal fruiting bodies on the oil palm trunk [14][15][16][17] . According to Balduzzi 6 the damages caused by fungal diseases have a visual impact on the plants and the damaging factor changes a tree's geometry.…”