Prediction of total viable counts on chilled pork using an electronic nose combined with support vector machine.

The aim of this study was to predict the total viable counts (TVC) in chilled pork using an electronic nose (EN) together with support vector machine (SVM). EN and bacteriological measurements were performed on pork samples stored at 4 °C for up to 10 days. Bacterial numbers on pork were determined by plate counts on agar. Principal component analysis (PCA) was used to cluster EN measurements. The model for the correlation between EN signal responses and bacterial numbers was constructed by using the SVM, combined with partial least squares (PLS). Correlation coefficients for training and validation were 0.94 and 0.88, respectively, which suggested that the EN system could be used as a simple and rapid technique for the prediction of bacteria numbers in pork.

[1]  Michel Tenenhaus,et al.  PLS generalised linear regression , 2005, Comput. Stat. Data Anal..

[2]  E. Llobet,et al.  Electronic Nose Based on Metal Oxide Semiconductor Sensors as an Alternative Technique for the Spoilage Classification of Red Meat , 2008, Sensors.

[3]  J. Farkas,et al.  Estimation of bacteriological spoilage of pork cutlets by electronic nose. , 2007, Acta microbiologica et immunologica Hungarica.

[4]  J. Gardner,et al.  Biomedical Engineering Online Open Access Bacteria Classification Using Cyranose 320 Electronic Nose , 2022 .

[5]  Sean B. Holden.  PAC-like upper bounds for the sample complexity of leave-one-out cross-validation , 1996, COLT '96.

[6]  Hyun-Chul Kim,et al.  An efficient model order selection for PCA mixture model , 2003, Pattern Recognit. Lett..

[7]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[8]  Yubin Lan,et al.  Electronic Nose with an Air Sensor Matrix for Detecting Beef Freshness , 2008 .

[9]  A. Romain,et al.  Microbial volatile organic compounds as indicators of fungi. Can an electronic nose detect fungi in indoor environments , 2005 .

[10]  L. Moy,et al.  Electronic noses and artificial neural networks , 1996 .

[11]  J. Zhao,et al.  Probabilistic PCA for t distributions , 2006, Neurocomputing.

[12]  Suranjan Panigrahi,et al.  Design and development of a metal oxide based electronic nose for spoilage classification of beef , 2006 .

[13]  Su Qiang,et al.  Two semi-empirical approaches for the prediction of oxide ionic conductivities in ABO3 perovskites , 2009 .

[14]  A. Parry,et al.  Leg ulcer odour detection identifies β-haemolytic streptococcal infection. , 1995, Journal of wound care.

[15]  Sara Limbo,et al.  Freshness decay and shelf life predictive modelling of European sea bass (Dicentrarchus labrax) applying chemical methods and electronic nose , 2009 .

[16]  Peter M. Corcoran,et al.  Combining PCA-based datasets without retraining of the basis vector set , 2009, Pattern Recognit. Lett..

[17]  J. Suykens,et al.  A tutorial on support vector machine-based methods for classification problems in chemometrics. , 2010, Analytica chimica acta.

[18]  Lone Gram,et al.  Food spoilage--interactions between food spoilage bacteria. , 2002, International journal of food microbiology.

[19]  R. Green,et al.  Analysis of total aerobic viable counts in samples of raw meat using fluorescence-based probe and oxygen consumption assay , 2009 .

[20]  Changsheng Xie,et al.  Spoiling and formaldehyde-containing detections in octopus with an E-nose , 2009 .

[21]  Giovanni Luca Christian Masala,et al.  A comparative study of K-Nearest Neighbour, Support Vector Machine and Multi-Layer Perceptron for Thalassemia screening , 2003 .

[22]  M. Kearns,et al.  Algorithmic stability and sanity-check bounds for leave-one-out cross-validation , 1999 .

[23]  M. Peris,et al.  A 21st century technique for food control: electronic noses. , 2009, Analytica chimica acta.

[24]  Evor L. Hines,et al.  Identification of Staphylococcus aureus infections in hospital environment: electronic nose based approach , 2005 .

[25]  W. Du,et al.  Potential application of the electronic nose for quality assessment of salmon fillets under various storage conditions , 2002 .