Electronic Nose Based on Metal Oxide Semiconductor Sensors as an Alternative Technique for the Spoilage Classification of Red Meat

Abstract

The aim of the present study was to develop an electronic nose for the quality control of red meat. Electronic nose and bacteriological measurements are performed to analyse samples of beef and sheep meat stored at 4°C for up to 15 days. Principal component analysis (PCA) and support vector machine (SVM) based classification techniques are used to investigate the performance of the electronic nose system in the spoilage classification of red meats. The bacteriological method was selected as the reference method to consistently train the electronic nose system. The SVM models built classified meat samples based on the total microbial population into "unspoiled" (microbial counts < 6 log10 cfu/g) and "spoiled" (microbial counts ≥ 6 log10 cfu/g). The preliminary results obtained by the bacteria total viable counts (TVC) show that the shelf-life of beef and sheep meats stored at 4 °C are 7 and 5 days, respectively. The electronic nose system coupled to SVM could discriminate between unspoiled/ spoiled beef or sheep meats with a success rate of 98.81 or 96.43 %, respectively. To investigate whether the results of the electronic nose correlated well with the results of the bacteriological analysis, partial least squares (PLS) calibration models were built and validated. Good correlation coefficients between the electronic nose signals and bacteriological data were obtained, a clear indication that the electronic nose system can become a simple and rapid technique for the quality control of red meats.

Keywords: Bacterial measurement; Electronic nose; Red meat; Shelf-life; multivariate classification models; partial least squares.

Figure 1.

Schematic of the experimental set-up.

Figure 2.

Time responses of an array of six gas sensors at day 9 for beef (a) and sheep meats (b).

Figure 3.

Changes in the count of aerobic bacteria.

Figure 4.

Scores plot of a PCA on beef meat (a) and sheep meat (b).

Figure 5.

Evolution of the scores on the first principal component with the period of storage and polynomial fitting for beef and sheep meats.

Figure 6.

Performance of the SVM model in the spoilage analysis of beef and sheep samples.

Figure 7.

Results of the PLS models. Actual vs. predicted values of the TVC in beef (a) and sheep meats (b). The circles are the results of a leave-one-out cross-validation performed using training measurements and the crosses correspond to predictions for validation measurements.