A Comprehensive Review on Groundnut (Arachis Hypogaea L.) Decorticator, Sorter and Grader Using Image Processing
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A Comprehensive Review on Groundnut (Arachis Hypogaea L.) Decorticator, Sorter and Grader Using Image Processing
Dr .A. Lovelin Jerald Department of Food Processing and Preservation Technology.
Avinashilingam Institute for Home Science and Higher Education for Women.Coimbatore,Tamil Nadu
lovelin_fppt@avinuty.ac.in
Shri Nidhi M
Department of Food Processing and Preservation Technology Avinashilingam Institure for Home Science and Higher Education for
Women Coimbatore,Tamil Nadu
22uef025@avinuty.ac.in
Sreelakshmi Anil
Department of Food Processing and Preservation Technology Avinashilingam Institure for Home Science and Higher Education for Women Coimbatore,Tamil Nadu
22uef028@avinuty.ac.in
Visalini T
Department of Food Processing and
Preservation Technology Avinashilingam Institure for Home Science and Higher Education for Women Coimbatore,Tamil Nadu
22uef032@avinuty.ac.in
Abstract—Groundnut (Arachis hypogaea L.) is one of the most important oilseed crops grown worldwide. It plays a crucial role in food security, edible oil production, and economies based on agriculture. Post-harvest processing tasks like decortication, sorting, and grading greatly affect kernel quality, market value, and storage stability. Traditional processing methods are mostly manual or semi-mechanized. These methods often require a lot of labour, lead to inconsistent quality, and result in higher post-harvest losses.
Recently, new technologies in agricultural engineering, machine vision, artificial intelligence (AI), and the Internet of Things (IoT) have made it possible to create automated and intelligent systems for processing groundnuts. This review looks closely at both traditional and modern methods for groundnut decortication, sorting, and grading, focusing especially on machine vision and AI techniques. It also discusses how integrating AI and IoT can help with real-time monitoring and smart control in groundnut processing. The review shows how these technologies can improve processing efficiency, enhance kernel quality, lower losses, and help with consistent quality assessment in modern agriculture systems.
Keywords—Groundnut processing, decortication, sorting, grading, machine vision, artificial intelligence, IoT