Application of sonic tomograph for basal stem rot detection in oil palm

• Main Author: Ibrahim, Ishaq
• Format: Thesis
• Language: English
• Published: 2016
• Online Access: http://psasir.upm.edu.my/id/eprint/66830/1/FH%202016%2024%20IR.pdf; http://psasir.upm.edu.my/id/eprint/66830/
• Institution: Universiti Putra Malaysia

Basal stem rot (BSR) has been known as a silent killer to the oil palm industries especially in Malaysia as the disease symptoms can only be observed once the infected tree is highly damaged from the inside. Losses have reached up to millions of ringgit per year due to high reduction of fresh fruit bunch production. The main objective of this study was to improve the BSR disease detection technique by sonic tomography (SoT) assisted by Ganoderma selective medium (GSM). Hence, a sonic tomography was used to measure and to reveal the internal condition of 51 selected oil palm trees, as well as to classify the percentage of damage detected in each selected trees at a measuring level between 0 and 100 cm near the ground level. Eight trees were selected as the focal tree by using purposive sampling, while 43 neighboring trees were selected nearby the focal trees via adaptive sampling. Four sensors were mounted around the circumference of the tree trunk. Then, the measuring points were nailed into the trunk. Next, each measuring points was tapped by an electronic hammer to generate sound waves. Subsequently, the sonic waves were captured by the sensors and were measured to produce tomogram. The tomogram contain information on the percentage of damage and the general location of the decayed area within the scanned tree. The percentage of damages from each selected trees was classified into 0%, 1 to 20%, 21 to 40%, 41 to 60%, and 61 to 100% damage. Afterwards, trunk samples were extracted by using an increment borer from the 51 scanned trees (excluding the three control trees) at the same elevation from four directions of north, south, east, and west by referring to tomogram images. Then, each sample was cut into five portions of 2 mm size each, isolated onto the GSM, and stored inside a closed box under room temperature for five days. Subsequently, the occurrence of Ganoderma mycelium inside the Petri dishes was counted and the percentage of the occurrence was determined and classified into 0%, 1 to 20%, 21 to 40%, 41 to 60%, and 61 to 100% occurrence. Lastly, the tomogram were corroborated with the occurrence of Ganoderma mycelium to determine if the damages found in the trees were caused by Ganoderma, and at the same time, to determine the accuracy of SoT to locate Ganoderma inside the tree trunk. As a result, tomographic images revealed that among the 51 selected trees, two trees had 0% damage, nine trees had between 1 and 20%, 19 trees had between 21 and 40%, 15 trees had between 41 and 60%, and six trees had between 61 and 100%. Other than that, the occurrence of Ganoderma mycelium in the Petri dish had been discovered in 3 trees with 1-20%, 19 trees with 21-40%, 14 trees with 41-60%, and 6 trees with 61-100%. This study concluded that the SoT was able to detect damages caused by Ganoderma at a total percentage of 82%.