VegCheck: A Vegetable Detection Website

Abstract

Food safety and reduction of food wastage are major concerns in today’s society. Vegetables, being highly perishable, often deteriorate rapidly, leading to health risks and economic loss. This paper presents VegCheck, an intelligent system designed to detect vegetable freshness and determine whether the vegetable is fit for consumption or has become rotten. The proposed system utilizes image processing and machine learning techniques to analyze visual features such as color, texture, and surface characteristics of vegetables. Based on the freshness classification, the system provides appropriate outputs including nutritional information and healthy recipe suggestions for fresh vegetables, while recommending safe disposal methods for rotten produce. The system aims to assist consumers in making informed food safety decisions, reduce food wastage, and promote sustainable consumption practices. Experimental results demonstrate the effectiveness of VegCheck in accurately classifying vegetable freshness and enhancing user awareness regarding nutrition and waste management.

Introduction

1. “Application on Food Waste Management System,” ResearchGate. Available:

https://www.researchgate.net/publication/380759750_APPLICATION_ON_FOOD_WASTE_MANAGEMENT_SYSTEM

1.  “Food Waste Management System,” International Research Journal of Modernization in Engineering Technology and Science (IRJMETS), vol. 19, no. 1, 2023. Available: https://www.ripublication.com/ijaer23/ijaerv19n1_13.pdf
2. “Smart Food Waste Management System,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), 2023. Available: https://ijarcce.com/wpcontent/uploads/2023/02/IJARCCE_2023_12247.pdf
3.  “Food Waste Detection and Management System,” arXiv preprint, 2023. Available: https://arxiv.org/abs/2309.02598
4.  “Intelligent Food Waste Management Using Machine Learning,” Elsevier – ScienceDirect. Available:

https://www.sciencedirect.com/science/article/pii/S2665927124000492

1. “Food Waste Management System Using Smart Technology,” International Journal of Innovative Research and Publications (IJRPR), vol. 5, issue 2. Available: https://ijrpr.com/uploads/V5ISSUE2/IJRPR22727.pdf
2. “Automated Food Waste Management System,” Journal of Emerging Technologies and Novel Research (JETNR), 2025. Available:

https://jpn.org/jetnr/papers/JETNR2504014.pdf

Conclusion

The proposed VegCheck system provides an effective solution for detecting vegetable freshness using image processing and machine learning techniques. The system accurately classifies vegetables as fresh or rotten and provides appropriate guidance such as nutritional information, recipe suggestions, and safe disposal methods. VegCheck is simple, cost-effective, and user-friendly, making it suitable for improving food safety, reducing food wastage, and supporting sustainable consumption practices.

References

[1] “Application on Food Waste Management System,” ResearchGate. Available: https://www.researchgate.net/publication/380759750_APPLICATION_ON_FOOD_WASTE_MANAGEMENT_SYSTEM [2] “Food Waste Management System,” International Research Journal of Modernization in Engineering Technology and Science (IRJMETS), vol. 19, no. 1, 2023. Available: https://www.ripublication.com/ijaer23/ijaerv19n1_13.pdf [3] “Smart Food Waste Management System,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), 2023. Available: https://ijarcce.com/wpcontent/uploads/2023/02/IJARCCE_2023_12247.pdf [4] “Food Waste Detection and Management System,” arXiv preprint, 2023. Available: https://arxiv.org/abs/2309.02598 [5] “Intelligent Food Waste Management Using Machine Learning,” Elsevier – ScienceDirect. Available: https://www.sciencedirect.com/science/article/pii/S2665927124000492 [6] “Food Waste Management System Using Smart Technology,” International Journal of Innovative Research and Publications (IJRPR), vol. 5, issue 2. Available: https://ijrpr.com/uploads/V5ISSUE2/IJRPR22727.pdf [7] “Automated Food Waste Management System,” Journal of Emerging Technologies and Novel Research (JETNR), 2025. Available: https://jpn.org/jetnr/papers/JETNR2504014.pdf

Copyright

Copyright © 2026 Prof. Deepika A. Bhosale, Ms. Sejal Santosh Katkar, Ms. Sejal Vijay kandalge, Ms. Kritika Jaywant Karnure, Ms. Neha Kiran Kumbhar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.