Abstract: Agriculture is the backbone of nations, and safeguarding crops from diseases is vital for food security. This research focuses on tomato, a quintessential crop present in various culinary forms, emphasizing the importance of disease prevention for maintaining quality. This article presents an innovative approach utilizing Machine Learning algorithms for early prediction and detection of tomato plant leaf diseases. A curated datasets was prepared, and operations such as feature extraction and rigorous testing were performed on it using eight diverse machine learning algorithms
Keywords: machine learning algorithm, disease prevention, feature extraction
Cite:
N. Veeratharini, K. Swathi, R. Arthi, "Tomato Leaf Disease Detection", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 3, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.133139.
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DOI:
10.17148/IJARCCE.2024.133139
