Identification of tea storage times by linear discrimination analysis and back-propagation neural network techniques based on the eigenvalues of principal components analysis of E-nose sensor signals

Sensors

Volumn 9, Issue 10, 2009, Pages 8073-8082

  Yu, Huichun ^a,b   Wang, Yongwei ^a   Wang, Jun ^a  

^a ZHEJIANG UNIVERSITY   (China)

^b HENAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

BP neural network; Electronic nose; Linear discrimination analysis; Principle components analysis; Storage time; Tea

Indexed keywords

BP NEURAL NETWORKS; ELECTRONIC NOSE; LINEAR DISCRIMINATION ANALYSIS; PRINCIPLE COMPONENTS ANALYSIS; STORAGE TIME; TEA;

BEVERAGES; DIGITAL STORAGE; EIGENVALUES AND EIGENFUNCTIONS; FACE RECOGNITION; NEURAL NETWORKS; SENSORS; TORSIONAL STRESS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 70350409879     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s91008073     Document Type: Article

References (19)

1. Chen, Q.S.; Zhao, J.W.; Fang, C.H.; Wang, D.M. Feasibility study on identification of green, black and oolong teas using near-infrared spectroscopy based on support vector machine (SVM). Spectrochim. Acta, Part A 2006, 66, 568-574.
2. Zhang, H.; Wang, J.; Ye, S. Predictions of acidity, soluble solids and firmness of pears using electronic nose technique. J. Food Eng. 2008, 86, 370-378.
3. Zhang, H.M.; Wang, J.; Tian, X.J.; Yu, H.; Yu, Y. Optimization of sensor array and detection of stored duration of wheat by electronic nose. J. Food Eng. 2007, 82, 403-408.
4. Gomez, A.H.; Wang, J.; Hu, G.; Pereira, A.G. Monitoring storage shelf live of tomato using electronic nose technique. J. Food Eng. 2008, 85, 625-631.
5. Rajamaki, T.; Alakomi, H.L.; Ritvanen, T.; Skytta, E.; Smolander, M.; Ahvenainen, R. Application of an electronic nose for quality assessment of modified atmosphere packaged poultry meat. Food Ctrl. 2006, 17, 5-13.
6. Panigrahi, S.; Balasubramanian, S.; Gu, H.; Logue, C.; Marchello, M. Neuralnetwork-integrated electronic nose system for identification of spoiled beef. LWT-Food Sci. Tec. 2006, 39,135-145.
7. Olafsdottir, G.; Nesvadba, P.; Natale, C.D.; Careche, M. Multisensor for fish quality determination. Trends Food Sci Tech. 2004, 15, 86-93.
8. Laberche, S.; Bazzo, S.; Cade, S.; Chanie, E. Shelf life determination by electronic nose: Application to milk. Sens. Actuat. B 2005, 106, 199-206.
9. Parpinello, G.P.; Fabbri, A.; Domenichelli, S.; Mesisca, V.; Cavicchi, L.; Versari, A. Discrimination of apricot cultivars by gasmultisensor array using an artificial neural network. Biosyst. Eng. 2007, 97, 371-378.
10. Garcia, M.; Aleixandre, M.; Gutierrez, J.; Horrillo, M.C. Electronic nose for wine discrimination. Sens. Actuat. B 2006, 113, 911-916.
11. Santos, P.J.; Fernandez, M.J.; Fontecha, J.L.; Lozano, J.; Aleixandre, M.; Garcia, M.; Gutierrez, J.; Horrillo, M. C. SAW sensor array for wine discrimination. Sens. Actuat. B 2005, 107, 291-295.
12. Dutta, R.; Hines, E.L.; Gardner, J.W.; Ksahwan K.R.; Bhuyan, M. Tea quality prediction using a tin oxide-based electronic nose: An artificial intelligence approach. Sens. Actuat. B 2003. 94, 228-237.
13. Dutta, R.; Kashwan, K.R.; Bhuyan, M.; Hines, E.L.; Gardner, J.W. Electronic nose based tea quality standardization. Neural Net. 2003, 16, 846-853.
14. Bhattacharyya, N.; Seth, S.; Tudu, B. Detection of optimum fermentation time for black tea manufacturing using electronic nose. Sens. Actuat. B 2007a, 122, 627-634.
15. Bhattacharyya, N.; Seth, S.; Tudu, B. Monitoring of black tea fermentation process using electronic nose. J. Food Eng. 2007b, 80, 1146-1156.
16. Yu, H.C.; Wang, J. Discrimination of Longjing green-tea grade by electronic nose. Sens. Actuat. B 2007, 122, 134-140.
17. Yu, H.C.; Wang, J.; Yao, C.; Zhang, H.; Yu, Y. Quality grade identification of green tea using E-nose by CA and ANN. LWT-Food Sci. Tec. 2008, 41, 1268-1273.
18. Yu, H.C.; Wang, J.; Xiao, H.; Liu, M. Quality grade identification of green tea using the eigenvalues of PCA based on the E-nose signals. Sens. Actuat. B 2009, 140, 378-382.
19. The Criteria of the Sensory Panel Assessment (SB/T 10157-93). Standard of Agricultural Administration of China, 1993.