Rapid Classification of Hairtail Fish and Pork Freshness Using an Electronic Nose Based on the PCA Method

Abstract

We report a method for building a simple and reproducible electronic nose based on commercially available metal oxide sensors (MOS) to monitor the freshness of hairtail fish and pork stored at 15, 10, and 5 °C. After assembly in the laboratory, the proposed product was tested by a manufacturer. Sample delivery was based on the dynamic headspace method, and two features were extracted from the transient response of each sensor using an unsupervised principal component analysis (PCA) method. The compensation method and pattern recognition based on PCA are discussed in the current paper. PCA compensation can be used for all storage temperatures, however, pattern recognition differs according to storage conditions. Total volatile basic nitrogen (TVBN) and aerobic bacterial counts of the samples were measured simultaneously with the standard indicators of hairtail fish and pork freshness. The PCA models based on TVBN and aerobic bacterial counts were used to classify hairtail fish samples as “fresh” (TVBN ≤ 25 g and microbial counts ≤ 106 cfu/g) or “spoiled” (TVBN ≥ 25 g and microbial counts ≥ 106 cfu/g) and pork samples also as “fresh” (TVBN ≤ 15 g and microbial counts ≤ 106 cfu/g) or “spoiled” (TVBN ≥ 15 g and microbial counts ≥ 106 cfu/g). Good correlation coefficients between the responses of the electronic nose and the TVBN and aerobic bacterial counts of the samples were obtained. For hairtail fish, correlation coefficients were 0.97 and 0.91, and for pork, correlation coefficients were 0.81 and 0.88, respectively. Through laboratory simulation and field application, we were able to determine that the electronic nose could help ensure the shelf life of hairtail fish and pork, especially when an instrument is needed to take measurements rapidly. The results also showed that the electronic nose could analyze the process and level of spoilage for hairtail fish and pork.