• Amrutha Bhat
• Adarsh S Shetty
• Dishan Muralidhar Suvarna
• Goutham
• Rishika S Anchan

The classification and grading of arecanut is a crucial aspect of the arecanut industry. Arecanut is widely used as a stimulant and mouth freshener in many cultures, and its demand is increasing rapidly. The quality of the arecanut is determined by its size, colour, texture, and taste. Therefore, proper classification and grading of arecanut are necessary to maintain the quality of the product. The aim of this project is to develop a machine learning-based system that can classify and grade arecanut automatically. The proposed system will use image processing techniques to extract features from the arecanut images and then use machine learning algorithms to classify and grade them. The system will be trained using a dataset of arecanut images that have already been classified and graded by experts. The extracted features will be used to train a machine learning model that can classify the arecanut based on its size, colour and texture. The model will also be able to grade the arecanut based on its quality. The proposed system has several advantages over the traditional manual method of arecanut classification and grading. It is more accurate, efficient, and can process many arecanut samples in a short time. Moreover, it eliminates human errors and biases, thereby increasing the overall quality of the arecanut product. In conclusion, the proposed system for classification and grading of arecanut will be a significant contribution to the arecanut industry. It will enable the industry to maintain the quality of the product consistently, which will ultimately lead to increased customer satisfaction and higher profits.

Arecanut, classification, grading, machine learning, image processing, feature extraction, accuracy.

"A CNN-BASED APPROACH TO CLASSIFY ARECA NUTS BASED ON GRADES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 4, page no.m469-m472, April-2023, Available :http://www.jetir.org/papers/JETIR2304C59.pdf

"A CNN-BASED APPROACH TO CLASSIFY ARECA NUTS BASED ON GRADES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 4, page no. ppm469-m472, April-2023, Available at : http://www.jetir.org/papers/JETIR2304C59.pdf