Received Date : 29-May-2017
Published Online: 01-September-2017
FIGURES & TABLES
Microorganisms are contained in all foods, some of them don't pose a risk for consumers, but many others became pathogenic, because of bad conservation or expired dates. Food will be degraded when the number of microorganisms became very large. The focus in this paper will be on the design of an electronic nose used in detecting rotten food. This nose is applied to detect bad odor diffused by rotten beef, and rotten chicken those meat have almost the same odor at rottenness which is not easily identified by human. Durations and gases emit of its rotten are determined by the pattern recognition methods PCA (Principal Components Analysis) for classification and DFA (Discriminate factorial analysis) for dating, and we will be identify between those rotten meat by DFA method.
E.Chenoll, M.Macian, P. Elizaquivel and R.Aznar, “Lactic Acid Bacteria Associated with Vacuum-packed Cooked Meat Product Spoilage: Population Analysis by rDNA-based Methods”, Journal of Applied Microbiology, vol. 102, pp. 498-508, 2006.
J.Bruhn, A.Christensen, L.Flodgaard, , K.Nielsen, T.Larsen, M.Givskov and L.Gram, “Presence of Acylated Homoserine Lactones (AHLs) and AHL-Producting Bacteria in Meat and Potential Role of AHL in Spoilage of Meat’’, Applied and Environmental Microbiology, vol. 70, pp. 4293-4302, 2004.
B.Nihad, B.,Mohammed, N.M’barak, B.Naima and D.Sanae ,“The detection of smell in spoiled meat by TGS822 gas sensor for an electronic nose used in rotten food’’, Europe Middle East and North Africa Conference on Technology and Security to Support Learning, EMENA-TSSL, Springer, vol. 520, pp. 279-286, Morocco, 2017.
A.Che Soh, K.K.Chow, U. K.Mohammad Yusuf, A. J.Ishak, M. K.Hassan and S.Khamis, “Development of neural network-based electronic nose for herbs recognition”, International Journal on Smart Sensing and Intelligent Systems, Vol. 7, June 2014.
B. Tudu, B. Kow, N. Bhattacharyya and R. Bandyopadhyay ,“Normalization techniques for gas sensor array as applied to classification of black tea”, International Journal on Smart Sensing and Intelligent Systems, Vol. 2, pp.1-14, 2009.
T.Kriengkri, T.Theeraphop, L.Noppon and W.Chatchawal, “Evaluation of bacterial population on chicken meats using a briefcase electronic nose”, Biosystems Engineering, Elsevier, vol. 151, pp. 116–125, November 2016.
D.Linong, C.Chunxiang, G.Meijuan and L.Xiaoxiang, “A model for discrimination freshness of shrimp’’, Sensing and Bio-Sensing Research, Elsevier, vol. 6, December 2015, pp. 28–32.
N.ul Hasan, N. Ejaz,W. Ejaz and H.Seok Kim, “Meat and Fish Freshness Inspection System Based on Odor Sensing’’, Sensors, pp. 15542–15557, November 2012.
K.H. Eom, K.H.Hyun, S.Lin and J.W.Kim,“The Meat Freshness Monitoring System Using the Smart RFID Tag’’, International Journal of Distributed Sensor Networks, January 2014.
G.H.Elżbieta, G.Dominika, M.Zuzanna, W.K.Iwona, B.Marta and W.Agnieszka, “Applications of electronic noses in meat analysis’’, Food Science and Technology, vol.36, no.3, July 2016.
C. Pérès, F.Begnaud, L.Eveleigh and J.L.Berdagué, “Fast Characterization of Foodstuff by Headspace Mass Spectrometry (HS-MS) ’’, Trends in Analytical Chemistry, 2003, pp.858-866.
K.Arshak, E.Moore, G.M.Lyons, J.Harris and S.Clifford, “A review of gas sensors employed in electronic nose applications’’, Sensor Review, vol. 24, pp. 181-198, 2004.
A.C. Soria, M.J. García-Sarrió and M.L. Sanz, “Volatile sampling by headspace techniques’’, TrAC Trends in Analytical Chemistry, Elsevier, vol.71, pp.85-99, 2015.
B.Nihad, B.,Mohammed, N.M’barak, B.Naima and D.Sanae, “Design of temperature and humidity sensors for an electronic nose used in rotten food’’, Electrical and Information Technologies (ICEIT),IEEE, July 2016.
H.Singha, V. B.Rajb, J. Kumara, F. Durania, M. Mishraa, A.T. Nimala and M.U. Sharmaa, “SAW mono sensor for identification of harmful vapors using PCA and ANN’’, Process Safety and Environmental Protection,Elsevier,vol.102,pp.577-588, July 2016.
C.M.M. Peter, , W.Zheng and M. N.Karl, “Compressing movement information via principal components analysis (PCA): Contrasting outcomes from the time and frequency domains’’, Human Movement Science, Elsevier,vol.32, pp.1495-1511, 2013.
R.Z. Morawski and A.Miękina,“Application of principal components analysis and signal-to-noise ratio for calibration of spectrophotometric analysers of food’’, Measurement, Elsevier, vol.79, pp.302–310, February 2016.
Y.B. Monakhovaa, R. Godelmannc, T. Kuballac, S.P.Mushtakovab and D.N. Rutledged, “Independent components analysis to increase efficiency of discriminant analysis methods (FDA and LDA): Application to NMR fingerprinting of wine’’, Talanta, Elsevier, vol.141, pp.60-65, August 2015.
K.Romdhane, H.Moncef, R.Hamadi and B.Christophe, “Mid infrared and fluorescence spectroscopies coupled with factorial discriminant analysis technique to identify sheep milk from different feeding systems’’, Food Chemistry, Elsevier, vol.127, pp.743-748, 2011.
H.Moncef, R.Hamadi, S.Nizar, S.Houcine, A.Mutlag, B.Christophe and K.Romdhane, “Fluorescence spectroscopy coupled with factorial discriminant analysis technique to identify sheep milk from different feeding systems’’, Food Chemistry, Elsevier, vol.122, pp.1344-1350, 2010.
K. Brudzewskia, J. Ulaczykb, S. Osowskic and T. Markiewiczc, “Chiral behavior of TGS gas sensors: Discrimination of the enantiomers by the electronic nose’’, Sensors and Actuators B: Chemical, vol.122, pp.493-502, March 2007.
Benabdellah,N., Hachami,K., Bourhaleb,M., & Benazzi,N.(2017).IDENTIFICATION OF TWO TYPES OF ROTTEN MEAT USING AN ELECTRONIC NOSE FOR FOOD QUALITY CONTROL.International Journal on Smart Sensing and Intelligent Systems, 10(3), 673-695.doi:10.21307/ijssis-2017-229.
Benabdellah,Nihad., Khalid Hachami, Mohammed Bourhaleb, and Naima Benazzi"IDENTIFICATION OF TWO TYPES OF ROTTEN MEAT USING AN ELECTRONIC NOSE FOR FOOD QUALITY CONTROL"International Journal on Smart Sensing and Intelligent Systems 10,no.3(2017):673-695doi:10.21307/ijssis-2017-229.
Benabdellah,Nihad., Khalid Hachami, Mohammed Bourhaleb, and Naima Benazzi"IDENTIFICATION OF TWO TYPES OF ROTTEN MEAT USING AN ELECTRONIC NOSE FOR FOOD QUALITY CONTROL"International Journal on Smart Sensing and Intelligent Systems 10.no.3(2017):673-695doi:10.21307/ijssis-2017-229.
Share article: IDENTIFICATION OF TWO TYPES OF ROTTEN MEAT USING AN ELECTRONIC NOSE FOR FOOD QUALITY CONTROL