Development of geospatial model for Metisa plana (Walker) outbreak and outbreak prediction in oil palm plantations in Malaysia

Metisa plana (Walker) is a leaves defoliating insect that is able to cause complete skeletonization and death of the oil palm’s fronds. This insect can cause a loss of USD 2.32 billion for two consecutive years given only 10% of the 5 million hectares of oil palms being infested. Hence, efficient, r...

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Main Author:	Ruslan, Siti Aisyah
Format:	Thesis
Language:	English
Published:	2018
Subjects:	Predatory insects - Malaysia Assassin bugs - Malaysia Oil palm - Diseases and pests
Online Access:	http://psasir.upm.edu.my/id/eprint/82899/1/FP%202019%206%20ir.pdf
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spelling	my-upm-ir.828992022-01-11T07:11:45Z Development of geospatial model for Metisa plana (Walker) outbreak and outbreak prediction in oil palm plantations in Malaysia 2018-11 Ruslan, Siti Aisyah Metisa plana (Walker) is a leaves defoliating insect that is able to cause complete skeletonization and death of the oil palm’s fronds. This insect can cause a loss of USD 2.32 billion for two consecutive years given only 10% of the 5 million hectares of oil palms being infested. Hence, efficient, rigorous control methods should be properly planned. In order to do this, the role of environmental factors on the pests’ population’s fluctuations should be well understood. Nonetheless, the current practices are still leaning towards the conventional approaches that are highly dependent on ineffective, time-consuming in-situ data collection. On the other hand, the utilization of geospatial technologies can be used to obtain data in rapid, harmless, and cost-effective manners. This study utilized the geospatial technologies to i) examine spatial and temporal climatic stresses that cause the outbreak of Metisa plana, ii) to construct the relationship between the geospatial data and Metisa plana outbreak, and iii) to predict the outbreak of Metisa plana in oil palm plantation. Metisa plana census data of larvae instar 1, 2, 3, and 4 were collected approximately biweekly over the period of 2014 and 2015. Moderate Resolution Imaging Spectroradiometer (MODIS) and The Tropical Rainfall Measuring Mission (TRMM) satellite images providing values of land surface temperature (LST), rainfall (RF), relative humidity (RH), and Normalized Difference Vegetation Index (NDVI) were extracted and apportioned to 6 time lags; 1 week (T1), 2 weeks (T2), 3 week (T3), 4 weeks (T4), 5 week (T5) and 6 weeks (T6). Linear relationship between Metisa plana with LST, RF, RH, and NDVI were carried out using the Pearson’s correlation, multiple linear regression (MLR) and multiple polynomial regression analysis (MPR). Artificial neural network (ANN) was then used to develop the best prediction model of Metisa plana’s outbreak. Presence of Metisa plana was influenced by LST, RF and RH, but not NDVI. The LST between 24oC and 28oC showed a strong relationship with Metisa plana, whereby its presence started to decline with LST from 28oC and above. However, the effect of time lag on the presence of Metisa plana was not prominent. The best MLR model was obtained with LST, RF and RH at T4 to T6 with an adjusted R2 = 0.29. The MPR model of LST at T4 to T6 depicted the best fit line with an adjusted R2 = 0.50. The highest accuracy of 95.29% was achieved by models generated by ANN utilizing the relative humidity at T1 to T3. The model generated by combined variables, LST, RF and RH at T4 to T6 was able to predict the presence of Metisa plana with the accuracy by up to 89.95%. Based on the result of this study, the elucidation of Metisa plana’s landscape ecology was possible with the utilization of geospatial technology. Predatory insects - Malaysia Assassin bugs - Malaysia Oil palm - Diseases and pests 2018-11 Thesis http://psasir.upm.edu.my/id/eprint/82899/ http://psasir.upm.edu.my/id/eprint/82899/1/FP%202019%206%20ir.pdf text en public masters Universiti Putra Malaysia Predatory insects - Malaysia Assassin bugs - Malaysia Oil palm - Diseases and pests Muharam, Farrah Melissa
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
advisor	Muharam, Farrah Melissa
topic	Predatory insects - Malaysia Assassin bugs - Malaysia Oil palm - Diseases and pests
spellingShingle	Predatory insects - Malaysia Assassin bugs - Malaysia Oil palm - Diseases and pests Ruslan, Siti Aisyah Development of geospatial model for Metisa plana (Walker) outbreak and outbreak prediction in oil palm plantations in Malaysia
description	Metisa plana (Walker) is a leaves defoliating insect that is able to cause complete skeletonization and death of the oil palm’s fronds. This insect can cause a loss of USD 2.32 billion for two consecutive years given only 10% of the 5 million hectares of oil palms being infested. Hence, efficient, rigorous control methods should be properly planned. In order to do this, the role of environmental factors on the pests’ population’s fluctuations should be well understood. Nonetheless, the current practices are still leaning towards the conventional approaches that are highly dependent on ineffective, time-consuming in-situ data collection. On the other hand, the utilization of geospatial technologies can be used to obtain data in rapid, harmless, and cost-effective manners. This study utilized the geospatial technologies to i) examine spatial and temporal climatic stresses that cause the outbreak of Metisa plana, ii) to construct the relationship between the geospatial data and Metisa plana outbreak, and iii) to predict the outbreak of Metisa plana in oil palm plantation. Metisa plana census data of larvae instar 1, 2, 3, and 4 were collected approximately biweekly over the period of 2014 and 2015. Moderate Resolution Imaging Spectroradiometer (MODIS) and The Tropical Rainfall Measuring Mission (TRMM) satellite images providing values of land surface temperature (LST), rainfall (RF), relative humidity (RH), and Normalized Difference Vegetation Index (NDVI) were extracted and apportioned to 6 time lags; 1 week (T1), 2 weeks (T2), 3 week (T3), 4 weeks (T4), 5 week (T5) and 6 weeks (T6). Linear relationship between Metisa plana with LST, RF, RH, and NDVI were carried out using the Pearson’s correlation, multiple linear regression (MLR) and multiple polynomial regression analysis (MPR). Artificial neural network (ANN) was then used to develop the best prediction model of Metisa plana’s outbreak. Presence of Metisa plana was influenced by LST, RF and RH, but not NDVI. The LST between 24oC and 28oC showed a strong relationship with Metisa plana, whereby its presence started to decline with LST from 28oC and above. However, the effect of time lag on the presence of Metisa plana was not prominent. The best MLR model was obtained with LST, RF and RH at T4 to T6 with an adjusted R2 = 0.29. The MPR model of LST at T4 to T6 depicted the best fit line with an adjusted R2 = 0.50. The highest accuracy of 95.29% was achieved by models generated by ANN utilizing the relative humidity at T1 to T3. The model generated by combined variables, LST, RF and RH at T4 to T6 was able to predict the presence of Metisa plana with the accuracy by up to 89.95%. Based on the result of this study, the elucidation of Metisa plana’s landscape ecology was possible with the utilization of geospatial technology.
format	Thesis
qualification_level	Master's degree
author	Ruslan, Siti Aisyah
author_facet	Ruslan, Siti Aisyah
author_sort	Ruslan, Siti Aisyah
title	Development of geospatial model for Metisa plana (Walker) outbreak and outbreak prediction in oil palm plantations in Malaysia
title_short	Development of geospatial model for Metisa plana (Walker) outbreak and outbreak prediction in oil palm plantations in Malaysia
title_full	Development of geospatial model for Metisa plana (Walker) outbreak and outbreak prediction in oil palm plantations in Malaysia
title_fullStr	Development of geospatial model for Metisa plana (Walker) outbreak and outbreak prediction in oil palm plantations in Malaysia
title_full_unstemmed	Development of geospatial model for Metisa plana (Walker) outbreak and outbreak prediction in oil palm plantations in Malaysia
title_sort	development of geospatial model for metisa plana (walker) outbreak and outbreak prediction in oil palm plantations in malaysia
granting_institution	Universiti Putra Malaysia
publishDate	2018
url	http://psasir.upm.edu.my/id/eprint/82899/1/FP%202019%206%20ir.pdf
_version_	1747813327604547584

Development of geospatial model for Metisa plana (Walker) outbreak and outbreak prediction in oil palm plantations in Malaysia

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