Citation
Esa, Nurnadiah
(2016)
Preliminary study on detection of Basal Stem Rot disease at oil palm trunk using electrical resistance.
Masters thesis, Universiti Putra Malaysia.
Abstract
Basal Stem Rot (BSR) disease is one of the most crucial diseases that attacks oil palm tree in
Malaysia. It is caused by the wood-rotting fungus known as Ganoderma boninense. Early
detection is important in managing BSR disease spreads as this disease wills ultimately results
with the destruction of the basal tissues of the plant where it can lead to the decrease in the
production of Fresh Fruit Bunch (FFB) yield. This study was conducted to detect BSR disease at
oil palm tree by using electrical resistance (ER). Ten samples of trees at the age of 25 years
were investigated. LandMapper ERM-2 was used in detecting the disease by collecting ER
values at eight positions surrounding the trunk at three different heights (0 cm, 60 cm and 120
cm) based on Wenner array principle. Kriging was conducted to interpolate the ER values inside
the trunk as well as to classify the level of severity, which were identified as T1 (non-infected), T2
(mild level) and T3 (moderate level). Classification technique of geometrical interval with 2
classes was used to differentiate between the decay and non-decay area .Spatial analysis was
then performed to calculate and compared between two areas. Healthy positions give higher ER
values of more than 30Ω while the infected positions give less than 30Ω. Moreover, healthy tree
had a higher mean values than the infected tree. Destruction of the basal tissues and presence of
fruiting bodies were only seen at the height of 0 cm in severity level T2 and T3. By using Kriging,
interpolation of decayed area was approximately having the same position with the origin of the
decay area captured by DSLR camera. Descriptive statistics for the infected tree at 0 cm showed
that the highest mean was 50.54Ω which was at level T1 while levels T2 and T3 had mean of
30.80Ω and 29.25Ω respectively. For Duncan test, it only differentiates between healthy tree and
infected tree due to small differences between levels T2 and T3. Therefore, this approach sounds
to be feasible in detecting BSR disease to prevent the loss of the oil palm tree stands.
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