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Updated: Aug 5, 2026

Fruit Volatile Analysis Using an Electronic Nose
Published on: March 30, 2012
Real-time spoilage detection of climacteric fruits using a potassium permanganate-based ethylene indicator and deep
Byeol Yi Kim1, Chahn-Mee Moh1, Sea Cheol Min1
1Seoul Women's University Korea, Seoul, Republic of Korea.
None:
This study explored the application of a potassium permanganate (KMnO4)-based ethylene indicator to assess the freshness of bananas and kiwifruit, alongside the integration of deep learning for interpreting indicator responses. A mobile application was developed using a trained deep learning model for real-time fruit freshness detection. The KMnO4 concentrations in the indicator were 0.1, 0.5, and 1.0% (w/v), and the fruits were stored at 25 C for 10 days in polypropylene pouches containing the indicator. The highest correlation was observed between the ethylene concentration and color change in the 0.5% KMnO4 indicator. The ResNet50 model exhibited high accuracy in predicting the freshness of both fruits. The developed mobile application enabled rapid and accurate real-time detection of freshness by analyzing indicator images of fruit packaging. These results demonstrate that the KMnO4-based ethylene indicator is reliable for assessing the freshness of fruits, with mobile software offering a solution for rapid freshness evaluation.
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