A review of ganoderma Basal Stem Rot (BSR) disease detection and mapping using geospatial and advanced techniques

被引:2
|
作者
Baharim, Mohd Sharul Aikal [1 ]
Adnan, Nor Aizam [1 ]
Mohd, Fazly Amri [2 ]
Othman, Ainon Nisa [1 ]
Abdul Rahim, Haris [1 ]
Azis, Mohamad Haris Abd [1 ]
Seman, Idris Abu [3 ]
Izzuddin, Mohamad Anuar [3 ]
Shahabuddin, Nur Amanina [3 ]
Nordiana, Abd Aziz [3 ]
机构
[1] Univ Teknol MARA, Ctr Studies Surveying Sci & Geomat, Fac Architecture Planning & Surveying, Shah Alam, Malaysia
[2] Univ Teknol MARA, Ctr Studies Surveying Sci & Geomat, Fac Architecture Planning & Surveying, Arau, Malaysia
[3] Persiaran Inst, Malaysian Palm Oil Board MPOB, Kajang, Selangor, Malaysia
关键词
Basal Stem Rot (BSR); ganoderma; geospatial; remote sensing; UAV; OIL PALM PLANTATIONS; CLASSIFICATION; INFECTION; BONINENSE;
D O I
10.1080/10106049.2021.1993350
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In oil palm plantations, Basal Stem Rot (BSR) disease has been acknowledged by many researchers worldwide to be a core and consistent danger. Given this problem, the early evaluation of the disease is necessary to prevent any infection ranging from immature to mature levels within the oil palms. The main objective of this research study is to highlight several sensors and methods that are applied for disease detection at each level. This comprehensive review utilises the most recent geospatial technology together with other advanced technologies to study BSR disease remotely, based on assessments of multispectral data, hyperspectral data, electrical properties, Terrestrial Laser Scanning (TLS), spatial mapping, Intelligent Electronic Nose (e-nose), tomography techniques and RADAR sensors. This paper identifies and explains the important techniques and methods for detecting BSR disease for any researcher who has a significant interest in specifically monitoring the development of BSR disease.
引用
收藏
页码:8100 / 8126
页数:27
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