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Sensors 2008, 8(1), 142-156; doi:10.3390/s8010142

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

1
Sensor Electronic  Instrumentation Group, Faculty of Sciences, Physics Department, Moulay Ismaïl University, B.P. 11201, Zitoune, Meknes, Morocco
2
MINOS, Microsystems and Nanotechnologies for Chemical Analysis, Universitat Rovira i Virgili, Avda. Països Catalans, 26, 43007 Tarragona, Spain
3
Biotechnology Agroalimentary and Biomedical Analysis Group, Faculty of Sciences, Biology Department, Moulay Ismaïl University, B.P. 11201, Zitoune, Meknes, Morocco
*
Author to whom correspondence should be addressed.
Received: 13 November 2007 / Accepted: 8 January 2008 / Published: 21 January 2008
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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: Electronic nose; Bacterial measurement; Red meat; Shelf-life; multivariate classification models; partial least squares Electronic nose; Bacterial measurement; Red meat; Shelf-life; multivariate classification models; partial least squares
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

El Barbri, N.; Llobet, E.; El Bari, N.; Correig, X.; Bouchikhi, B. Electronic Nose Based on Metal Oxide Semiconductor Sensors as an Alternative Technique for the Spoilage Classification of Red Meat. Sensors 2008, 8, 142-156.

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