Abstract
In this study, the capability of an electronic nose machine to identify chilled and frozen-thawed chicken meat was investigated. According to the importance of fresh chicken meat consumption in people’s daily diet, recognition of fresh chicken meat from frozen-thawed one is an essential issue. In the mentioned system, eight sensors (MOS type) were applied. The outputs of sensors were preprocessed, then features were extracted, and fuzzy K-nearest neighbors (F-KNN) algorithm was applied for classification. Chicken meats were classified in two classes (fresh and frozen-thawed). Also, each group of fresh and frozen-thawed chicken meat was classified in five classes according to their shelf life (elapsed day after slaughtering/thawing). The obtained results showed that the average amount of accuracy for fresh-chilled chicken meat classification and frozen-thawed one were 95.2 and 94.67%, respectively. Finally, the accuracy of fresh chicken meat with 95.83% demonstrated the high accuracy of it compare with frozen-thawed one. According to the results, high performance of F-KNN algorithm demonstrated that e-nose system can be applied as a rapid, accurate, and nondestructive method for online and automated identification of fresh and frozen-thawed chicken meat.
Published Version
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