A Literature Review of the Detection and Categorization of various Arecanut Diseases using Image Processing and Machine Learning Approaches

Author:

B. R. Puneeth1,P. S. Nethravathi2

Affiliation:

1. Research Scholar, College of Computer Science and Information Science, Srinivas University, Mangaluru, India

2. Professor, College of Computer Science and Information Science, Srinivas University, Mangaluru, India

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.

Publisher

Srinivas University

Subject

General Medicine

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1. A Review of the Literature on Arecanut Sorting and Grading Using Computer Vision and Image Processing;International Journal of Applied Engineering and Management Letters;2023-04-29

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4. Alzheimer Disease MRI Preprocessed Images: A Machine Intelligent Based Approach for Classification and Analysis;International Journal of Case Studies in Business, IT, and Education;2022-08-31

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