Automated image analysis and improvisations to manage palm oil plantation. Issue 1 (December 2020)

• Record Type: Journal Article
• Authors: Akhtar, M N; Khan, S. A.; Mohamed, Mazlan; Ahmed Janvekar, Ayub
• Is Part Of: IOP conference series. Volume 1007:Issue 1(2020)
• Publication Date: 2020-12
• Subjects: Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/1007/1/012082
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: Palm oil industry plays an essential role in South-East Asian agricultural commodity sector as it contributes to the substantial gross domestic product of the country. However, with the advent of climate change and massive deforestation, the disease and malfunctioning in growth of palm tree has increased. Therefore, it has become essential to detect any form of disease in palm oil plantation which can hamper its productivity as it can cause a serious problem to the countries whose economic conditions are primarily dependent upon palm oil plantations. Hence, early detection of disease from the initial stage is crucial to the production of palm oil. In this regard, the proposed manuscript highlights the importance of image processing in detecting early disease in palm oil plantation using image segmentation and also proposes some improvisations in palm oil plantation which will be helpful in managing the palm oil commodity business.