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Mycotoxins, ergosterol, and odor volatiles in durum wheat during granary storage at 16% and 20% moisture content
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Characterization and classification of Italian Barbera wines by using an electronic nose and an amperometric electronic tongue
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Buratti, S., S. Benedetti, M. Scampicchio, and E. C. Pangerod. 2004. Characterization and classification of Italian Barbera wines by using an electronic nose and an amperometric electronic tongue. Analytica Chimica Acta 525(1): 133-139.
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Analysis of single-cultivar extra virgin olive oils by means of an Electronic Nose and HS-SPME/GC/MS methods
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Cimato, A., D. D. Monaco, C. Distante, M. Epifani, P. Siciliano, A. M. Taurino, M. Zuppa, and G. Sani. 2006. Analysis of single-cultivar extra virgin olive oils by means of an Electronic Nose and HS-SPME/GC/MS methods. Sens Actuator B 114(2): 674-680.
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Evaluation of a radial basis function neural network for the determination of wheat quality from electronic nose data
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Evans, P., C. P. Krishna, S. A. McNeish, W. R. Sneath, N. Hobson, and N. Magan. 2000. Evaluation of a radial basis function neural network for the determination of wheat quality from electronic nose data. Sens Actuator B 69(3): 348-358.
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Determination of the relationship between sewage odour and BOD by neural networks
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Guleda, O., D. Ibrahim, and N. E. Seref. 2005. Determination of the relationship between sewage odour and BOD by neural networks. Environmental Modelling & Software 20(4): 843-850.
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Electronic nose and data analysis for detection of maize oil adulteration in sesame oil
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Hai, Z., and W. Jun. 2006. Electronic nose and data analysis for detection of maize oil adulteration in sesame oil. Sens Actuator B 119(2): 449-455.
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Classification of white wine aromas with an electronic nose
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Lozano, J., J. P. Santos, and M. C. Horrillo. 2005. Classification of white wine aromas with an electronic nose. Talanta. 67(3): 610-616.
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Application of ANN with extracted parameters from an electronic nose in cigarette brand identification
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Luoa, D., H. G. Hosseini, and J. R. Stewart. 2004. Application of ANN with extracted parameters from an electronic nose in cigarette brand identification. Sens Actuator B 99(2-3): 253-257.
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Volatiles as an indicator of fungal activity and differentiation between species, and the potential use of electronic nose technology for early detection of grain spoilage
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Magan, N., and P. Evans. 2000. Volatiles as an indicator of fungal activity and differentiation between species, and the potential use of electronic nose technology for early detection of grain spoilage. J. of Stored Products Research 36(4): 319-340.
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Application of a headspace mass spectrometry system to the differentiation and classification of wines according to their origin, variety and ageing
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Mart, M. P, B. Olga, and G. Josep. 2004. Application of a headspace mass spectrometry system to the differentiation and classification of wines according to their origin, variety and ageing. J. of Chromatography A. 1057(1): 211-217.
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Needham, R., J. Williams, N. Beales, P. Voysey, and N. Magan. 2005. Early detection and differentiation of spoilage of bakery products. Sens Actuator B 106(1): 20-23.
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Olsson, J., T. Borjesson, T. Lundstedt, and J. Schnurer. 2000. Volatiles for mycological quality grading of barley grains: determinations using gas chromatography-mass spectrometry and electronic nose. International J. of Food Microbiology 59(1): 167-178.
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Olsson, J., T. Borjesson, T. Lundstedt, and J. Schnurer. 2000. Volatiles for mycological quality grading of barley grains: determinations using gas chromatography-mass spectrometry and electronic nose. International J. of Food Microbiology 59(1): 167-178.
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Non-destructive evaluation of apple maturity using an electronic nose system
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Pathange, L. P., P. Mallikarjunan, R. P. Marini, S. O'Keefe, and D. Vaughan. 2006. Non-destructive evaluation of apple maturity using an electronic nose system. J. of Food Engineering 77(4): 1018-1023.
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Neural-network-integrated electronic nose system for identification of spoiled beef
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Panigrahi, S., S. Balasubramanian, H. Gu, C. Logue, and M. Marchello. 2006. Neural-network-integrated electronic nose system for identification of spoiled beef. Lebensmittel-Wissenschaft und-Tech 39(1): 135-145.
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Chemometric characterization of Italian wines by thin-film multisensors array and artificial neural networks
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Penza, M., and G. Cassano. 2004. Chemometric characterization of Italian wines by thin-film multisensors array and artificial neural networks. Food Chemistry 86(2): 283-296.
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Application of an electronic nose for quality assessment of modified atmosphere packaged poultry meat
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Rajama ki, T., H. Alakomi, T. Ritvanen, E. Skytta, M. Smolander, and R. Ahvenainen. 2006. Application of an electronic nose for quality assessment of modified atmosphere packaged poultry meat. Food Contro. 17(1): 5-13.
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Electronic nose based tea quality standardization
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Ritaban, D., K. R. Kashwan, M. Bhuyan, E. L. Hines, and J. W. Gardner. 2003. Electronic nose based tea quality standardization. Neural Networks 16(5-6): 847-853.
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Sai d, L., S. Bazzo, S. Cade, and E. Chanie. 2005. Shelf life determination by electronic nose: Application to milk. Sens Actuator B 106(1): 199-206.
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A comparison study of chemical sensor array pattern recognition algorithms
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Quantification of odours from piggery effluent ponds using an electronic nose and an artificial neural network
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Sohn, J. H., R. Smith, E. Yoong, J. Leis, and G. Galvin. 2003. Quantification of odours from piggery effluent ponds using an electronic nose and an artificial neural network. Biosystems Engineering 86(2): 399-410.
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