Abstract
Background/Purpose: Every scholarly research project starts with a survey of the literature, which acts as a springboard for new ideas. The purpose of this literature review is to become familiar with the study domain and to assess the work's credibility. It also improves with the subject's integration and summary. This article briefly discusses the detection of disease and classification to achieve the objectives of the study. Objective: The main objective of this literature survey is to explore the different techniques applied to identify and classify the various diseases on arecanut. This paper also recommends the methodology and techniques that can be used to achieve the objectives of the study. Design/Methodology/Approach: Multiple data sources, such as journals, conference proceedings, books, and research papers published in reputable journals, were used to compile the essential literature on the chosen topic and collect information from the arecanuts research centre and many farmers in the south Canara and Udupi districts, before narrowing down the literature that is relevant to the research work. The shortlisted literature was carefully assessed by reading each paper and taking notes as appropriate. The information gathered is then examined to identify the potential gap in the study. Findings/Result: Based on the analysis of the papers reviewed, discussion with farmers and research center officers, it is observed that, not much work is carried out in the field of disease identification and classification on arecanut using machine learning techniques. This survey paper recommends techniques and the methodology that can be applied to identify and classify the diseases in arecanut and to classify them in to healthy and unhealthy. Research limitations/implications: The literature review mentioned in this paper are detection and classification of different diseases in arecanut. Originality/Value: This paper focuses on various online research journals, conference papers, technical books, and web articles. Paper Type: Literature review paper on techniques and methods used to achieve the objectives.
Highlights
The seed of the areca palm is known as an arecanut, available in most throughout much of the tropical Pacific-ocean, South-East and South-Asian country, and Eastern Africa place
The results showed difficulty to detect the bunches in the early and middle growing stage overall 66.96% detection accuracy
More than 90% accuracy support vector machine (SVM) 93.54%, Convolutional Neural Network (CNN) 93.72% of accuracy
Summary
The seed of the areca palm is known as an arecanut, available in most throughout much of the tropical Pacific-ocean, South-East and South-Asian country, and Eastern Africa place. Areca is derived from the Malayalam word aaykka, it was used by Dutch and Portuguese sailors who imported the nut from India to Europe in the 16th century [1]. Karnataka is the larger producer of arecanut in India mainly in Dakshina Kannada and Uttara Kannada district and Malnad regions, days Tumkur, Davangere, Hassan, Mysore districts cultivate arecanut. It thrives in the 140C to 360C temperature range but is harmed by temperatures below 10oC and above 40oC. Another option is to cover the bunches with plastic bags [7]
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