Journal of Oil Palm Research Vol. 33 (3) September 2021, p. 425-435



Received: 13 July 2020   Accepted: 24 September 2020   Published Online: 12 November 2020

The bagworm is one of main and serious leaf eating insect pest threats of the oil palm plantations in Malaysia. The economic impact from a moderate bagworm attack of 10%-50% leaf damage may cause 43% yield loss. The population of bagworms without control often increases to above its threshold limits, thereby causing a serious outbreak. Monitoring and detection of the oil palm bagworm population is required to ensure proper planning of any control actions in the infested areas. Hence, a study on the determination of the spectral signature of the bagworm species of Metisa plana Walker was initiated by using Visible/Near Infrared (Vis/NIR) spectroscopy. Live and dead bagworm spectral properties were determined under the Vis/ NIR wavelength regions, 350-1050 nm to provide specific infrared detector and band filter for development of an automated counter of the bagworms. The results showed that the live and dead bagworms had specific reflectance spectra at a specific wavelength in the NIR range spectral, ranging from 1032-1051 nm and these were statistically confirmed using the Student’s t-Test with two tailed distributions. A principal component analysis (PCA) resulted that the first two principal components, F1 and F2 have eigenvalues greater than 1, at 2.11 and 1.24, respectively. Using a Boxplot Quantiles, the results showed that the lowest and highest means of the reflectance spectra observed for the live bagworms were approximately 3.43% and 26.42%, respectively. Meanwhile, for the dead bagworms, the lowest and highest reflectance spectra observed were 4.02% and 34.29%, respectively. These spectral data were important to determine the suitable infrared (IR) instrumentation for detection of every stage of the live and dead bagworms. This information will be useful, important and crucial for development of an automated detector of insect pest in the future.



1 Malaysian Palm Oil Board, 6 Persiaran Institusi,
Bandar Baru Bangi, 43000 Kajang, Selangor, Malaysia.

2 Faculty of Engineering, Universiti Putra Malaysia,
43400 UPM Serdang, Selangor, Malaysia.

* Corresponding author e-mail:

Aaron, M and Michael, A K (2011). Quantification and statistical significance analysis of group separation in NMR-based metabonomics studies. Chemometrics and Intelligent Laboratory Systems, 109: 162-170.

Anielle, C R; Renan, A R and Aida, B M (2017). Evaluation of the nutritional changes caused by Huanglongbing (HLB) to citrus plants using laser- induced breakdown spectroscopy. Appl. Spectrosc., 71(7): 1471-1480.

Baker, J E; Dowell, F E and Throne, J E (1999). Detection of parasitized rice weevils in wheat kernels with near-infrared spectroscopy. Bio . Control, 16: 88-90.

 Baker, J E; Woo, S Nelson, D R and Fatland, C L (1984). Olefins as major components of epicuticular lipids of three Sitophilus weevils. Comp. Biochem. Physiol. B., 77: 877-884.

Basri, M W and Kevan, P G (1995). Life history and feeding behaviour of the oil palm bagworm, Metisa plana Walker (Lepidopt r : Psychidae). Elaeis, 7(1): 18-35.

Burks, C S; Dowell, F E and Xie, F (2000). Measuring fig quality using near-infrared spectroscopy. J. Stored Prod. Res., S6: 289-296.

Chambers, J; Cowe, I A; Van Wyk, C B; Wilkin, D R and Cuthbertson, D C (1992). Detection of insects in stored oducts by NIR. Near- nfra-Red Spectroscopy: Bridging the Gap between Data Analysis and NIR Applications (Hildrum, K I; Isaaks n, T; Naes, T and Tandberg, A eds.). Ellis Horwood, New York. p. 203-208.

Cheong, Y L and Tey, C C (2012). Understanding pest biology an beha iour for eͿective control of oil palm bagworm. The Planter, 88: 699-715.

Dowell, F E; Throne, J E; Wang, D and Baker, J E (1999). Identifying stored-grain insects using near infrared spectroscopy. J. Econ. Entomol., 92(1): 165- 169.

Hyndman, R J and Fan, Y (1996). Sample quantiles in statistic packages. The Amer. Statisticians, 50(4): 161-165.

Izzuddin, M A (2009). Early detection of Ganoderma disease in oil palms using hyperspectral remote sensing. M.Sc thesis, Universiti Putra Malaysia.

Jia, F; Maghirang, E; Dowell, F; Abel, C and Ramaswamy, S (2014). DiͿerentiating tobacco budworm and corn earworm using   near- infrared spectroscopy. J. Econ. Entomol., 100(3): 759-764.

Liu, J; Li, X; Li, P; Wang, W; Zhang, J; Zhou, W and Zhou, Z (2011). Non-destructive measurement of sugar content in chestnuts using near-infrared spectroscopy. Comput. Comput. Technol. Agric. IV., S47: 246-254.

Lockey, K H (1988). Lipids of the insect cuticle: Origin, composition and function. Comp. Biochem. Physiol. B., 89: 595-645.

Manickavasagan, A and Jayasuriya, H (2014). Imaging with Electromagnetic Spectrum. Springer- Verlag Berlin Heidelberg, Germany. 209 pp.

Manley, M; Downey, G and Baeten, V (2008). Spectroscopic technique: Near-infrared (NIR) spectroscopy. Modern Techniques for Pood Authentication (Sun, D W ed.). First edition. Academic Press, New York. p. 65-115.

Moscetti, R; HaͿ, R P; Saranwong, S; Monarco, D; Cecchini, M and Massantini, R (2014). Nondestructive detection of insect infested chestnuts based on NIR spectroscopy. Postharvest Biol. Technol., 87: 88-94.

Murray, M I and Williams, P C (1987). Chemical principles of near-infrared technology. Near Infrared Technology in the Agricultural and Pood Industries (Williams, P and Norris, K eds.). First edition. American Association of Cereal Chemists Inc, St. Paul, Minnesota. p. 17-34.

Najib, M A; Rashid, A M S; Ishak, A; Izhal, A H and Ramle, M (2018). Monitoring insect pest infestation via diͿerent spectroscopy techniques. Appl. Spectrosc. Rev., 53(10): 836-853.

Norman, K and Basri, M W (2007). Status of common oil palm insect pests in relation to technology adoption. The Planter, 8S: 371-385.

Pasquini, C (2003). Near infrared spectroscopy: Fundamentals, practical aspects and analytical applications. J. Braz. Chem. Soc., 14: 198-219.

Peshlov, B N; Dowelt, F E; Drummond, F A and Donahue, D W (2009). Comparison of three near infrared spectrophotometers for infestation detection in wild blueberries using multivariate calibration models. J. Near Infrared Spectrosc., 17: 203-212.

Rajendran, S (2005). Detection of insect infestation in stored foods. Adv. Pood Nutr. Res., 49: 163-232.

Siegwart, M; Bouvier, F; Maugin, S; Lecomte, A and Lavigne, C (2015). DiͿerentiating oriental fruit moth and codling moth (Lep doptera: Tortricidae) larvae using NIR spectroscopy. J. Econ. Entomol., 108(1): 219-227.

Sirisomboon, P; Hashimoto, Y and Tanaka, M (2009). Study on non-destructive evaluation methods for defect pods for green soybean processing by near- infrared spectroscopy. J. Pood Eng., 9S: 502-512.

Tigabu, M and Odén, P C (2002). Multivariate classification of sound and insect infested seeds of a tropical multipurpose tree, Cordia africana, with near ed reflectance spectroscopy. J. Near Infrared Spectrosc., 10: 45-51.

Tigabu, M and Odén, P C (2004). Simultaneous detection of filled, empty and insect infested seeds of three Larix species with single seed near-infrared transmittance spectroscopy. New Por., 27: 39-53.

Tigabu, M; Odén, P C and Shen, T Y (2004). Application of near-infrared spectroscopy for the detection of internal insect infestation in Picea abies seed lots. Can. J. Por. Res., S4: 76-84.

Wang, J; Nakano, K and Ohashi, S (2011). Non- destructive detection of internal insect infestation in jujubes using visible and near-infrared spectroscopy. Postharvest Biol. Technol., 59(S): 272-279.

Wang, J; Nakano, K; Ohashi, S; Takizawa, K and He, J G (2010). Comparison of diͿerent modes of visible and near-infrared spectroscopy for detecting internal insect infestation in jujubes. J. Pood Engineering, 101(1): 78-84.

Wilkin, D R; Cowe, I A; Thind, B B; McNicol, J W and Cuthbertson, D C (1986). The detection and measurement of mite infestation in animal feed using near infra-red reflectance. J. Agric. Sci., 107(2): 439-448.

Wood, B J and Nesbit, D P (1969). Caterpillar outbreak on oil palms in Eastem Sabah. The Planter, 45: 285-299.

Wood, B J (1976). Pest – Introduction and ecological consideration. Oil Palm Research (Corley, R H V; Hardon, J J and Wood, B J eds.). Amsterdam. Elsevier, 17: 333-345.

Xing, J and Guyer, D (2008). Comparison of transmittance and reflectance to detect insect infestation in Montmorency tart cherry. Comput. Electron. Agric., 64(2): 194-220.

Xing, J; Guyer, D; Ariana, D and Lu, R (2008). Determining optimal wavebands using genetic algorithm for detection of internal insect infestation in tart cherry. Sens Instr. Pood Qual. Saf.,