PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

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• Akul, Y., Kumar, V., & Chong, K. P. (2018). Designing primers for loop-mediated isothermal amplification (LAMP) for detection of Ganoderma boninense. Bulgarian Journal of Agricultural Science, 24(5), 854-859.
  
  Azahar, T. M., Mustapha, J. C., Mazliham, S., & Boursier, P. (2011). Temporal analysis of basal stem rot disease in oil palm plantations: An analysis on peat soil. International Journal of Engineering & Technology, 11(3), 96–101.
  
  Azmi, A. N. N., Bejo, S. K., Jahari, M., Muharam, F. M., Yule, I., & Husin, N. A. (2020). Early detection of Ganoderma boninense in oil palm seedlings using support vector machines. Remote Sensing, 12(23), Article 3920. https://doi.org/10.3390/rs12233920
  
  Azmi, A. N. N., Khairunniza-Bejo, S., Jahari, M., Muharram, F. M., & Yule, I. (2021). Identification of a suitable machine learning model for detection of asymptomatic Ganoderma boninense infection in oil palm seedlings using hyperspectral data. Applied Sciences, 11(24), Article 11798. https://doi.org/10.3390/app112411798
  
  Azuan, N. H., Khairunniza-Bejo, S., Abdullah, A. F., Kassim, M. S. M., & Ahmad, D. (2019). Analysis of changes in oil palm canopy architecture from basal stem rot using terrestrial laser scanner. Plant Disease, 103(12), 3218-3225. https://doi.org/10.1094/PDIS-10-18-1721-RE
  
  Bharudin, I., Wahab, A. F. F. A., Samad, M. A. A., Yie, N. X., Zairun, M. A., Bakar, F. D. A., & Murad, A. M. A. (2022). Review update on the life cycle, plant–microbe interaction, genomics, detection and control strategies of the oil palm pathogen Ganoderma boninense. Biology, 11(2), Article 251. https://doi.org/10.3390/biology11020251
  
  Bornaz, L., & Rinaudo, F. (2004). Terrestrial laser scanner data processing. XXth ISPRS Congress Istanbul, 123(123006), 1–4.
  
  Buja, I., Sabella, E., Monteduro, A. G., Chiriacò, M. S., De Bellis, L., Luvisi, A., & Maruccio, G. (2021). Advances in plant disease detection and monitoring: From traditional assays to in-field diagnostics. Sensors, 21(6), Article 2129. https://doi.org/10.3390/s21062129
  
  Cabo, C., Ordóñez, C., López-Sánchez, C. A., & Armesto, J. (2018). Automatic dendrometry: Tree detection, tree height and diameter estimation using terrestrial laser scanning. International Journal of Applied Earth Observation and Geoinformation, 69, 164-174.
  
  Fahey, T., Pham, H., Gardi, A., Sabatini, R., Stefanelli, D., Goodwin, I., & Lamb, D. W. (2020). Active and passive electro-optical sensors for health assessment in food crops. Sensors, 21(1), Article 171. https://doi.org/10.3390/s21010171
  
  Faizah, R., Putranto, R. A., Raharti, V. R., Supena, N., Sukma, D., Budiani, A., Wening, S., & Sudarsono, S. (2022). Defense response changes in roots of oil palm (Elaeis guineensis Jacq.) seedlings after internal symptoms of Ganoderma boninense Pat. infection. BMC Plant Biology, 22(1), Article 139. https://doi.org/10.1186/s12870-022-03493-0
  
  Farraji, H., Dahlan, I., & Eslamian, S. (2021). Water recycling from palm oil mill effluent. In S. Eslamian (Ed.), Handbook of Water Harvesting and Conservation: Basic Concepts and Fundamentals (pp. 307-320). John Wiley & Sons. https://doi.org/10.1002/9781119478911.ch20
  
  Girardeau-Montaut, D. (2016). CloudCompare - Point Cloud Processing Workshop. EDF R&D Telecom ParisTech. https://www.eurosdr.net/sites/default/files/images/inline/04-cloudcompare_pcp_2019_public.pdf
  
  Gregorio, E., & Llorens, J. (2021). Sensing crop geometry and structure. In R. Kerry & A. Escolà (Eds.), Sensing Approaches for Precision Agriculture (pp. 59-92). Springer. https://doi.org/10.1007/978-3-030-78431-7_3
  
  Hillman, S., Wallace, L., Reinke, K., & Jones, S. (2021). A comparison between TLS and UAS LiDAR to represent eucalypt crown fuel characteristics. ISPRS Journal of Photogrammetry and Remote Sensing, 181, 295-307. https://doi.org/10.1016/j.isprsjprs.2021.09.008
  
  Hilmi, N. H. Z., Idris, A. S., Maizatul-Suriza, M., Madihah, A. Z., & Nur-Rashyeda, R. (2022). Molecular PCR assays for detection of Ganoderma pathogenic to oil palm in Malaysia. Malaysian Applied Biology, 51(1), 171-182. https://doi.org/10.55230/mabjournal.v51i1.2201
  
  Hosoi, F., & Omasa, K. (2009). Estimating vertical plant area density profile and growth parameters of a wheat canopy at different growth stages using three-dimensional portable lidar imaging. ISPRS Journal of Photogrammetry and Remote Sensing, 64(2), 151-158. https://doi.org/10.1016/j.isprsjprs.2008.09.003
  
  Huijser, P., & Schmid, M. (2011). The control of developmental phase transitions in plants. Development, 138(19), 4117-4129. https://doi.org/10.1242/dev.063511
  
  Husin, N. A., Bejo, S. K., Abdullah, A. F., Kassim, M. S., & Ahmad, D. (2021). Relationship of oil palm crown features extracted using terrestrial laser scanning for basal stem rot disease classification. Basrah Journal of Agricultural Sciences, 34, 1-10. https://doi.org/10.37077/25200860.2021.34.sp1.1
  
  Husin, N. A., Khairunniza-Bejo, S., Abdullah, A. F., Kassim, M. S., Ahmad, D., & Aziz, M. H. (2020a). Classification of basal stem rot disease in oil palm plantations using terrestrial laser scanning data and machine learning. Agronomy, 10(11), Article 1624. https://doi.org/10.3390/agronomy10111624
  
  Husin, N. A., Khairunniza-Bejo, S., Abdullah, A. F., Kassim, M. S., Ahmad, D., & Azmi, A. N. (2020b). Application of ground-based LiDAR for analysing oil palm canopy properties on the occurrence of basal stem rot (BSR) disease. Scientific Reports, 10(1), Article 6464. https://doi.org/s41598-020-62275-6
  
  Husin, N. A., Khairunniza-Bejo, S., Abdullah, A. F., Kassim, M. S., & Ahmad, D. (2022). Multi-temporal analysis of terrestrial laser scanning data to detect basal stem rot in oil palm trees. Precision Agriculture, 23(1), 101-126. https://doi.org/10.1007/s11119-021-09829-4
  
  Husin, N. A., Khairunniza–Bejo, S., Abdullah, A. F., Kassim, M. S. M., & Ahmad, D. (2020c). Study of the oil palm crown characteristics associated with Basal Stem Rot (BSR) disease using stratification method of point cloud data. Computers and Electronics in Agriculture, 178, Article 105810. https://doi.org/10.1016/j.compag.2020.105810
  
  Johnson, M., & Liscio, E. (2015). Suspect height estimation using the Faro Focus3D laser scanner. Journal of Forensic Sciences, 60(6), 1582-1588. https://doi.org/10.1111/1556-4029.12829
  
  Khairunniza-Bejo, S., Shahibullah, M. S., Azmi, A. N. N., & Jahari, M. (2021). Non-destructive detection of asymptomatic Ganoderma boninense infection of oil palm seedlings using NIR-hyperspectral data and support vector machine. Applied Sciences, 11(22), Article 10878. https://doi.org/10.3390/app112210878
  
  Li, Z., Yu, T., Paul, R., Fan, J., Yang, Y., & Wei, Q. (2020). Agricultural nanodiagnostics for plant diseases: Recent advances and challenges. Nanoscale Advances, 2(8), 3083-3094. https://doi.org/10.1039/C9NA00724E
  
  Liang, X., Kankare, V., Hyyppä, J., Wang, Y., Kukko, A., Haggrén, H., Yu, X., Kaartinen, H., Jaakkola, A., Guan, F., Holopainen, M., & Vastaranta, M. (2016). Terrestrial laser scanning in forest inventories. ISPRS Journal of Photogrammetry and Remote Sensing, 115, 63-77. https://doi.org/10.1016/j.isprsjprs.2016.01.006
  
  Liu, G., Wang, J., Dong, P., Chen, Y., & Liu, Z. (2018). Estimating individual tree height and diameter at breast height (DBH) from terrestrial laser scanning (TLS) data at plot level. Forests, 9(7), Article 398. https://doi.org/10.3390/f9070398
  
  Lumme, J., Karjalainen, M., Kaartinen, H., Kukko, A., Hyyppä, J., Hyyppä, H., Jaakkola, A., & Kleemola, J. (2008). Terrestrial laser scanning of agricultural crops. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37, 563-566.
  
  Maas, H. G., Bienert, A., Scheller, S., & Keane, E. (2008). Automatic forest inventory parameter determination from terrestrial laser scanner data. International Journal of Remote Sensing, 29(5), 1579-1593. https://doi.org/10.1080/01431160701736406
  
  Madihah, A. Z., Idris, A. S., & Rafidah, A. R. (2014). Polyclonal antibodies of Ganoderma boninense isolated from Malaysian oil palm for detection of basal stem rot disease. African Journal of Biotechnology, 13(34), 3455-3463. https://doi.org/10.5897/AJB2013.13604
  
  Madihah, A. Z., Maizatul-Suriza, M., Idris, A. S., Bakar, M. F. A., Kamaruddin, S., Bharudin, I., Bakar, F. D. A., & Murad, A. M. A. (2018). Comparison of DNA extraction and detection of Ganoderma, causal of basal stem rot disease in oil palm using loop-mediated isothermal amplification. Malaysian Applied Biology, 47(5), 119-127.
  
  Naidu, Y., Siddiqui, Y., Rafii, M. Y., Saud, H. M., & Idris, A. S. (2018). Inoculation of oil palm seedlings in Malaysia with white-rot hymenomycetes: Assessment of pathogenicity and vegetative growth. Crop Protection, 110, 146-154. https://doi.org/10.1016/j.cropro.2018.02.018
  
  Parveez, G. K. A., Kamil, N. N., Zawawi, N. Z., Ong-Abdullah, M., Rasuddin, R., Loh, S. K., Selvaduray, K. R., Hoong, S. S., & Idris, Z. (2022). Oil palm economic performance in Malaysia and R&D progress in 2021. Journal of Oil Palm Research, 34(2), 185-218. https://doi.org/10.21894/jopr.2022.0036
  
  Pitkänen, T. P., Raumonen, P., Liang, X., Lehtomäki, M., & Kangas, A. (2021). Improving TLS-based stem volume estimates by field measurements. Computers and Electronics in Agriculture, 180, Article 105882. https://doi.org/10.1016/j.compag.2020.105882
  
  Rees, R. W., Flood, J., Hasan, Y., Potter, U., & Cooper, R. M. (2009). Basal stem rot of oil palm (Elaeis guineensis); Mode of root infection and lower stem invasion by Ganoderma boninense. Plant Pathology, 58(5), 982-989. https://doi.org/0.1111/j.1365-3059.2009.02100.x
  
  Rosette, J., Suárez, J., Nelson, R., Los, S., Cook, B., & North, P. (2012). Lidar remote sensing for biomass assessment. Remote Sensing of Biomass—Principles and Applications, 24, 3-27. https://doi.org/10.5772/17479
  
  Sanderson, F. R. (2005). An insight into spore dispersal of Ganoderma boninense on oil palm. Mycopathologia, 159(1), 139-141. https://doi.org/10.1007/s11046-004-4436-2
  
  Santoso, H., Gunawan, T., Jatmiko, R. H., Darmosarkoro, W., & Minasny, B. (2011). Mapping and identifying basal stem rot disease in oil palms in North Sumatra with QuickBird imagery. Precision Agriculture, 12(2), 233–248. https://doi.org/10.1007/s11119-010- 9172-7
  
  Shoresh, M., Harman, G. E., & Mastouri, F. (2010). Induced systemic resistance and plant responses to fungal biocontrol agents. Annual Review of Phytopathology, 48(1), 21-43. https://doi.org/10.1146/annurev-phyto-073009-114450
  
  Stovall, A. E., Anderson-Teixeira, K. J., & Shugart, H. H. (2018). Assessing terrestrial laser scanning for developing non-destructive biomass allometry. Forest Ecology and Management, 427, 217-229. https://doi.org/10.1016/j.foreco.2018.06.004
  
  Surendran, A., Siddiqui, Y., Saud, H. M., & Manickam, N. S. A. A. S. (2017). The antagonistic effect of phenolic compounds on ligninolytic and cellulolytic enzymes of Ganoderma boninense, causing basal stem rot in oil palm. International Journal of Agriculture & Biology, 19, 1437-1446. https://doi.org/10.17957/IJAB/15.0439
  
  Wagers, S., Castilla, G., Filiatrault, M., & Sanchez-Azofeifa, G. A. (2021). Using TLS-measured tree attributes to estimate aboveground biomass in small black spruce trees. Forests, 12(11), Article 1521. https://doi.org/10.3390/f12111521
  
  Yap, P., Rosdin, R., Abdul-Rahman, A. A. A., Omar, A. T., Mohamed, M. N., & Rahami, M. S. (2021). Malaysian sustainable palm oil (MSPO) certification progress for independent smallholders in Malaysia. In IOP Conference Series: Earth and Environmental Science (Vol. 736, No. 1, p. 012071). IOP Publishing. https://doi.org/10.1088/1755-1315/736/1/012071
  
  Zevgolis, Y. G., Alsamail, M. Z., Akriotis, T., Dimitrakopoulos, P. G., & Troumbis, A. Y. (2022). Detecting, quantifying, and mapping urban trees’ structural defects using infrared thermography: Implications for tree risk assessment and management. Urban Forestry & Urban Greening, 75, Article 127691. https://doi.org/10.1016/j.ufug.2022.127691