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dc.contributor.authorISHAQ, I.-
dc.contributor.authorALIAS, M. S.-
dc.contributor.authorKADIR, J.-
dc.contributor.authorKASAWANI, I.-
dc.date.accessioned2017-10-04T04:26:17Z-
dc.date.available2017-10-04T04:26:17Z-
dc.date.issued2014-
dc.identifier.issn18238556-
dc.identifier.urihttp://hdl.handle.net/123456789/7034-
dc.description.abstractGanoderma boninense cause basal stem rot (BSR) disease to oil palm in Malaysia. It is the most serious disease of oil palm in Malaysia where 3.5% of plantation areas infected render lost in revenue of RM 1 billion/year. Detection of BSR is challenging because the external symptoms do not appear at early stages of infection. To date, common methods used to detect BSR disease are morphological and molecular techniques. These techniques are costly and time-consuming. This study aims to identify, quantify and classify BSR lession using tomography. A total of 51 palms with BSR visual symptoms and neighbouring palms were selected and scanned using PiCUS Sonic Tomograph. Samples from the trunks were digged-out using increment borer and tested on Ganoderma selective medium (GSM) for detection purposes.Tomograph result revealed that there were two trees with 0% damaged, nine trees with 1-20% damaged, 19 trees with 21-40% damaged, 15 trees with 41-60% damaged and six trees with 61-100% damaged. In addition, Ganoderma selective medium reconfrms that 49 out of 51 trees have been infected with BSR disease indicating tomogram accuracy of detecting BSR is 96%. Accuracy assessment also revealed that tomography is able to determine BSR severity level at 82%. Hence, the application of tomography in detecting Ganoderma infection is pertinent for oil palm plantation management to treat the oil palm accurately and effectively.en_US
dc.language.isoenen_US
dc.publisherJournal of Sustainability Science and Managementen_US
dc.subjectTomography analysisen_US
dc.subjectoil palmen_US
dc.subjectbasal stems roten_US
dc.subjectGanodermaen_US
dc.subjectdetectionen_US
dc.titleDETECTION OF BASAL STEM ROT DISEASE AT OIL PALM PLANTATIONS USING SONIC TOMOGRAPHYen_US
dc.typeArticleen_US
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