Abstract: A tropical crop called areca nuts, sometimes referred to as betel nuts, is grow. India is the world's second-largest producer and consumer of areca nuts. The early monsoon winds from the Indian Ocean and the Bay of Bengal bring heavy rain, which causes a range of illnesses to afflict the areca nut throughout its life cycle, including Yellow Leaf, Nut Split, and Fruit Rot. The only method of disease detection currently available to farmers is observation with the naked eye, and they must periodically examine each crop carefully in order to identify any diseases. Furthermore, without a farmer who is well-versed in these diseases and areca nuts, it will be difficult to detect diseases. This system incorporates several machine learning and image processing principles that will make this vision a reality. As the system concentrates on early detection so the issue might be eliminated at the starting stage in order to avoid the barriers later, it may accept inputs from areca nuts (including the tree) and transport them there for pre-processing. Otherwise, it poses a serious risk.
Keywords: Areca nut, yellow leaf, fruit rot, machine learning, image processing.
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DOI:
10.17148/IJARCCE.2023.125134
