Chemometric Analysis of Sensory Data

Comprehensive Chemometrics

Volumn 4, Issue , 2009, Pages 377-424

  Hibbert, D B ^a  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

Analysis of variance; Aroma; Artificial neural networks; Beverage analysis; Canonical correlation analysis; Consumer preference; Food analysis; Food profiling; Free choice profiling; Generalized Procrustes analysis; Hedonics; N way partial least squares; Organoleptic; Parallel factor analysis; Partial least squares; Principal components analysis; Product development; Quantitative descriptive analysis; Quantitative descriptive profiling; Sensory analysis

Indexed keywords

EID: 82955197303     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1016/B978-044452701-1.00010-7     Document Type: Chapter

References (139)

1. Naes T., Risvik E. Multivariate Analysis of Data in Sensory Science 1996, Vol. 16. Elsevier, Amsterdam, p 348.
2. Martens H., Martens M. Multivariate Analysis of Quality. An Introduction 2001, John Wiley & Sons, Chichester.
3. Martens M. A Philosophy for Sensory Science. Food Qual. Prefer. 1999, 10(4-5):233-244.
4. Kwan W.O., Kowalski B.R. Data Analysis of Sensory Scores. Evaluations of Panelists and Wine Score Cards. J. Food Sci. 1980, 45(2):213-216.
5. Moskowitz H. Applied Sensory Analysis of Foods 1988, Vol. 2. CRC Press, Boca Raton.
6. Aishima T., Nakai S. Chemometrics in Flavor Research. Food Rev. Int. 1991, 7:33-101.
7. Karoui R., De Baerdemaeker J. A Review of the Analytical Methods Coupled with Chemometric Tools for the Determination of the Quality and Identity of Dairy Products. Food Chem. 2007, 102(3):621-640.
8. Vestergaard J.S., Martens M., Turkki P. Analysis of Sensory Quality Changes during Storage of a Modified Atmosphere Packaged Meat Product (Pizza Topping) by an Electronic Nose System. LWT - Food Sci. Technol. 2007, 40(6):1083-1094.
9. Vestergaard J.S., Martens M., Turkki P. Application of an Electronic Nose System for Prediction of Sensory Quality Changes of a Meat Product (Pizza Topping) during Storage. LWT - Food Sci. Technol. 2007, 40(6):1095-1101.
10. Xie L.J., Ying Y.B., Ying T.J., Yu H.Y., Fu X.P. Discrimination of Transgenic Tomatoes Based on Visible/Near-Infrared Spectra. Anal. Chim. Acta 2007, 584(2):379-384.
11. Sinesio F., Di Natale C., Quaglia G.B., Bucarelli F.M., Moneta E., Macagnano A., Paolesse R., D'Amico A. Use of Electronic Nose and Trained Sensory Panel in the Evaluation of Tomato Quality. J. Sci. Food Agric. 2000, 80(1):63-71.
12. Vlasov Y., Legin A., Rudnitskaya A. Electronic Tongues and Their Analytical Application. Anal. Bioanal. Chem. 2002, 373(3):136-146.
13. Gallardo J., Alegret S., de Roman M.A., Munoz R., Hernandez P.R., Leija L., del Valle M. Determination of Ammonium Ion Employing an Electronic Tongue Based on Potentiometric Sensors. Anal. Lett. 2003, 36(14):2893-2908.
14. Gallardo J., Alegret S., del Valle M. A Flow-Injection Electronic Tongue Based on Potentiometric Sensors for the Determination of Nitrate in the Presence of Chloride. Sens. Actuators B Chem. 2004, 101(1-2):72-80.
15. Scott S.M., James D., Ali Z. Data Analysis for Electronic Nose Systems. Microchim. Acta 2007, 156(3-4):183-207.
16. Thaler E.R., Hanson C.W. Medical Applications of Electronic Nose Technology. Expert Rev. Med. Devices 2005, 2(5):559-566.
17. Winquist F., Krantz-Rulcker C., Wide P., Lundstrom I. Monitoring of Freshness of Milk by an Electronic Tongue on the Basis of Voltammetry. Meas. Sci. Technol. 1998, 9(12):1937-1946.
18. Winquist F., Bjorklund R., Krantz-Ruelcker C., Lundstroem I., Oestergren K., Skoglund T. An Electronic Tongue in the Dairy Industry. Sens. Actuators B Chem. 2005, B111-B112:299-304.
19. Ciosek P., Brzozka Z., Wroblewski W. Electronic Tongue for Flow-Through Analysis of Beverages. Sens. Actuators B Chem. 2006, 118(1-2):454-460.
20. Ciosek P., Wroblewski W. Performance of Selective and Partially Selective Sensors in the Recognition of Beverages. Talanta 2007, 71(2):738-746.
21. Legin A., Rudnitskaya A., Lvova L., Vlasov Y., Di Natale C., D'Amico A. Evaluation of Italian Wine by the Electronic Tongue: Recognition, Quantitative Analysis and Correlation with Human Sensory Perception. Anal. Chim. Acta 2003, 484(1):33-44.
22. Parra V., Arrieta A.A., Fernandez-Escudero J.A., Iniguez M., De Saja J.A., Rodriguez-Mendez M.L. Monitoring of the Ageing of Red Wines in Oak Barrels by Means of an Hybrid Electronic Tongue. Anal. Chim. Acta 2006, 563(1-2):229-237.
23. Clark G.M. The Multiple-Channel Cochlear Implant: The Interface between Sound and the Central Nervous System for Hearing, Speech, and Language in Deaf People - A Personal Perspective. Philos. Trans. R. Soc. Ser. B Biol. Sci. 2006, 361(1469):791-810.
24. Aishima T. Correlating Sensory Attributes to Gas Chromatography-Mass Spectrometry Profiles and e-Nose Responses Using Partial Least Squares Regression Analysis. J. Chromatogr. A 2004, 1054(1-2):39-46.
25. Tang C., Heymann H., Hsieh F.H. Alternatives to Data Averaging of Consumer Preference Data. Food Qual. Prefer. 2000, 11(1-2):99-104.
26. Vilanova M., Vilarino F. Influence of Geographic Origin on Aromatic Descriptors of Spanish Albarino Wine. Flav. Fragr. J. 2006, 21(2):373-378.
27. Bahamonde A., Diez J., Quevedo J.R., Luaces O., del Coz J.J. How to Learn Consumer Preferences from the Analysis of Sensory Data by Means of Support Vector Machines (SVM). Trends Food Sci. Technol. 2007, 18(1):20-28.
28. Tomic O., Nilsen A., Martens M., Naes T. Visualization of Sensory Profiling Data for Performance Monitoring. LWT - Food Sci. Technol. 2007, 40(2):262-269.
29. Carpenter R.P., Lyon D., Hasdell T. Guidelines for Sensory Analysis in Food Product Development and Control 2000, Aspen Publishers, Gaithersburg, p 205.
30. Sensory Analysis - Identification and Selection of Descriptors for Establishing a Sensory Profile by a Multidimensional Approach 1994, ISO, 11035, International Organization for Standardization, Geneva.
31. Lawless H.T., Sheng N., Knoops S.S.C.P. Multidimensional Scaling of Sorting Data Applied to Cheese Perception. Food Qual. Prefer. 1995, 6:91-98.
32. Piombino P., Nicklaus S., Le Fur Y., Moio L., Le Quere J.L. Selection of Products Presenting Given Flavor Characteristics: An Application to Wine. Am. J. Enol. Vitic. 2004, 55(1):27-34.
33. Cartier R., Rytz A., Lecomte A., Poblete F., Krystlik J., Belin E., Martin N. Sorting Procedure as an Alternative to Quantitative Descriptive Analysis to Obtain a Product Sensory Map. Food Qual. Prefer. 2006, 17(7-8):562-571.
34. Noble A.C. Wine Aroma Wheel (Accessed). http://www.winearomawheel.com/.
35. Varela P., Gambaro A. Sensory Descriptive Analysis of Uruguayan Tannat Wine: Correlation to Quality Assessment. J. Sens. Stud. 2006, 21(2):203-217.
36. Hough G., Wakeling I., Mucci A., Chambers E., Gallardo I.M., Alves L.R. Number of Consumers Necessary for Sensory Acceptability Tests. Food Qual. Prefer. 2006, 17(6):522-526.
37. Garcia-Gonzalez D.L., Roncales P., Cilla I., del Rio S., Poma J.P., Aparicio R. Interlaboratory Evaluation of Dry-Cured Hams (from France and Spain) by Assessors from Two Different Nationalities. Meat Sci. 2006, 73(3):521-528.
38. Findlay C.J., Castura J.C., Schlich P., Lesschaeve I. Use of Feedback Calibration to Reduce the Training Time for Wine Panels. Food Qual. Prefer. 2006, 17(3-4):266-276.
39. Stone H., Sidel J.L. Sensory Evaluation Practices 1985, Academic Press, London.
40. Heymann H., Lawless H.T. Sensory Evaluation in Food: Principles and Practices 1999, Springer, Berlin, p 848.
41. Forde C.G., Williams E.R., O'Riordan P.J. Use of Multi-Stratum Design and Analysis in a Sensory Trial. Food Qual. Prefer. 2007, 18(4):614-618.
42. Smilde A.K., Westerhuis J.A., de Jong S. A Framework for Sequential Multiblock Component Methods. J. Chemom. 2003, 17(6):323-337.
43. Mazerolles G., Hanafi M., Dufour E., Bertrand D., Qannari E.M. Common Components and Specific Weights Analysis: A Chemometric Method for Dealing with Complexity of Food Products. Chemom. Intell. Lab. Syst. 2006, 81(1):41-49.
44. Cocchi M., Bro R., Durante C., Manzini D., Marchetti A., Saccani F., Sighinolfi S., Ulrici A. Analysis of Sensory Data of Aceto Balsamico Tradizionale di Modena (ABTM) of Different Ageing by Application of PARAFAC Models. Food Qual. Prefer. 2006, 17(6):419-428.
45. Morita K., Kubota K., Aishima T. Investigating Sensory Characteristics and Volatile Components in Boiled Scallop Aroma Using Chemometric Techniques. Food Chem. 2002, 78(1):39-45.
46. Kontkanen D., Reynolds A.G., Cliff M.A., King M. Canadian Terroir: Sensory Characterization of Bordeaux-Style Red Wine Varieties in the Niagara Peninsula. Food Res. Int. 2005, 38(4):417-425.
47. Dueck D., Morris Q.D., Frey B.J. Multi-Way Clustering of Microarray Data Using Probabilistic Sparse Matrix Factorization. Bioinformatics 2005, 21(Suppl. 1):i144-i151.
48. Larson T.M., Gawlitzek M., Evans H., Albers U., Cacia J. Chemometric Evaluation of On-Line High-Pressure Liquid Chromatography in Mammalian Cell Cultures: Analysis of Amino Acids and Glucose. Biotechnol. Bioeng. 2002, 77(5):553-563.
49. Morita K., Kubota K., Aishima T. Comparison of Aroma Characteristics of 16 Fish Species by Sensory Evaluation and Gas Chromatographic Analysis. J. Sci. Food Agric. 2003, 83(4):289-297.
50. Hirst D., Naes T. A Graphical Technique for Assessing Differences among a Set of Rankings. J. Chemom. 1994, 8(1):81-93.
51. Naes T., Hirst D., Baardseth P. Using Cumulative Ranks to Detect Individual Differences in Sensory Profiling. J. Sens. Stud. 1994, 9(1):87-99.
52. Kermit M., Lengard V. Assessing the Performance of a Sensory Panel - Panellist Monitoring and Tracking. J. Chemom. 2005, 19(3):154-161.
53. Yuan S., Chang S.K.C. Texture Profile of Tofu as Affected by Instron Parameters and Sample Preparation, and Correlations of Instron Hardness and Springiness with Sensory Scores. J. Food Sci. 2007, 72(2):S136-S145.
54. Guest S., Essick G., Patel A., Prajapati R., McGlone F. Labeled Magnitude Scales for Oral Sensations of Wetness, Dryness, Pleasantness and Unpleasantness. Food Qual. Prefer. 2007, 18(2):342-352.
55. Vainionpää J., Kervinen R., de Prado M., Laurila E., Kari M., Mustonen L., Ahvenainen R. Exploration of Storage and Process Tolerance of Different Potato Cultivars Using Principal Component and Canonical Correlation Analyses. J. Food Eng. 2000, 44(1):47-61.
56. Pagliarini E., Tomaselli N., Brenna O.V. Study on Sensory and Composition Changes in Italian Amarone Valpolicella Red Wine during Aging. J. Sens. Stud. 2004, 19(5):422-432.
57. Sahmer K., Qannari E.M. Procedures for the Selection of a Subset of Attributes in Sensory Profiling. Food Qual. Prefer. 2008, 19(2):141-145.
58. Vigneau E., Qannari E.M. Clustering of Variables around Latent Components. Commun. Stat. B Simul. Comput. 2003, 32(4):1131-1150.
59. Sahmer K., Vigneau E., Qannari E.M. A Cluster Approach to Analyze Preference Data: Choice of the Number of Clusters. Food Qual. Prefer. 2006, 17(3-4):257-265.
60. Carpino S., Acree T.E., Barbano D.M., Licitra G., Siebert K.J. Chemometric Analysis of Ragusano Cheese Flavor. J. Agric. Food Chem. 2002, 50(5):1143-1149.
61. Lee S.J., Noble A.C. Characterization of Odor-Active Compounds in Californian Chardonnay Wines Using GC-Olfactometry and GC-Mass Spectrometry. J. Agric. Food Chem. 2003, 51(27):8036-8044.
62. Vivien M., Verron T., Sabatier R. Comparing and Predicting Sensory Profiles from NIRS Data: Use of the GOMCIA and GOMCIA-PLS Multiblock Methods. J. Chemom. 2005, 19(3):162-170.
63. Schulbach K.F., Rouseff R.L., Sims C.A. Relating Descriptive Sensory Analysis to Gas Chromatography/Olfactometry Ratings of Fresh Strawberries Using Partial Least Squares Regression. J. Food Sci. 2004, 69(7):S273-S277.
64. Cozzolino D., Smyth H.E., Lattey K.A., Cynkar W., Janik L., Dambergs R.G., Francis I.L., Gishen M. Relationship between Sensory Analysis and Near Infrared Spectroscopy in Australian Riesling and Chardonnay Wines. Anal. Chim. Acta 2005, 539(1-2):341-348.
65. Cliff M.A., King M.C., Schlosser J. Anthocyanin, Phenolic Composition, Colour Measurement and Sensory Analysis of BC Commercial Red Wines. Food Res. Int. 2007, 40(1):92-100.
66. Ollivier D., Artaud J., Pinatel C., Durbec J.P., Guerere M. Differentiation of French Virgin Olive Oil RDOs by Sensory Characteristics, Fatty Acid and Triacylglycerol Compositions and Chemometrics. Food Chem. 2006, 97(3):382-393.
67. Rason J., Martin J.F., Dufour E., Lebecque A. Diversity of the Sensory Characteristics of Traditional Dry Sausages from the Centre of France: Relation with Regional Manufacturing Practice. Food Qual. Prefer. 2007, 18(3):517-530.
68. Westad F. Independent Component Analysis and Regression Applied on Sensory Data. J. Chemom. 2005, 19(3):171-179.
69. Gower J.C. Generalized Procrustes Analysis. Psychometrika 1975, 40(1):33-51.
70. Dijksterhuis G. Procrustes Analysis in Sensory Science. Multivariate Analysis of Data in Sensory Science 1996, 185-219. Elsevier, Amsterdam. T. Naes, E. Risvik (Eds.).
71. Peay E.R. Multidimensional Rotation and Scaling of Configurations to Optimal Agreement. Psychometrika 1988, 53(2):199-208.
72. Popper R., Heymann H. Analysing Differences among Products by Multidimensional Scaling. Multivariate Analysis of Data in Sensory Science 1996, 159-184. Elsevier, Amsterdam. T. Naes, E. Risvik (Eds.).
73. Kruskal J.B. Multidimensional-Scaling by Optimizing Goodness of Fit to a Nonmetric Hypothesis. Psychometrika 1964, 29(1):1-27.
74. Lee S.J., Noble A.C. Use of Partial Least Squares Regression and Multidimensional Scaling on Aroma Models of California Chardonnay Wines. Am. J. Enol. Vitic. 2006, 57(3):363-370.
75. Morales M.T., Alonso M.V., Rios J.J., Aparicio R. Virgin Olive Oil Aroma - Relationship between Volatile Compounds and Sensory Attributes by Chemometrics. J. Agric. Food Chem. 1995, 43(11):2925-2931.
76. Ferrier J.G., Block D.E. Neural-Network-Assisted Optimization of Wine Blending Based on Sensory Analysis. Am. J. Enol. Vitic. 2001, 52(4):386-395.
77. Haugen J.E., Kvaal K. Electronic Nose and Artificial Neural Network. Meat Sci. 1998, 49:S273-S286.
78. Evans P., Persaud K.C., McNeish A.S., Sneath R.W., Hobson N., Magan N. Evaluation of a Radial Basis Function Neural Network for the Determination of Wheat Quality from Electronic Nose Data. Sens. Actuators B Chem. 2000, 69(3):348-358.
79. Techakriengkrai I., Paterson A., Taidi B. Relationship of Sensory Staleness in Two Lagers to Headspace Concentrations of Trans-2-Nonenal and Three Staling Aldehydes. J. Inst. Brew. 2006, 112(1):36-40.
80. Techakriengkrai I., Paterson A., Taidi B., Piggott J.R. Relationships of Overall Estery Aroma Character in Lagers with Volatile Headspace Congener Concentrations. J. Inst. Brew. 2006, 112(1):41-49.
81. Park B., Chen Y.R., Whittaker A.D., Miller R.K., Hale D.S. Neural Network Modelling for Beef Sensory Evaluation. Trans. ASAE 1994, 37(5):1547-1553.
82. Bro R. Review on Multiway Analysis in Chemistry - 2000-2005. Crit. Rev. Anal. Chem. 2006, 36(3-4):279-293.
83. Pravdova V., Boucon C., de Jong S., Walczak B., Massart D.L. Three-Way Principal Component Analysis Applied to Food Analysis: An Example. Anal. Chim. Acta 2002, 462(2):133-148.
84. Dahl T., Tomic O., Wold J.P., Naes T. Some New Tools for Visualising Multi-Way Sensory Data. Food Qual. Prefer. 2008, 19(1):103-113.
85. Qannari E., Wakeling I., Courcoux P., MacFie H.J.H. Defining the Underlying Sensory Dimensions. Food Qual. Prefer. 2000, 11(1-2):151-154.
86. Preys S., Mazerolles G., Courcoux P., Samson A., Fischer U., Hanafi M., Bertrand D., Cheynier V. Relationship between Polyphenolic Composition and Some Sensory Properties in Red Wines Using Multiway Analyses. Anal. Chim. Acta 2006, 563(1-2):126-136.
87. Huang Y., Kangas L.J., Rasco B.A. Applications of Artificial Neural Networks (ANNs) in Food Science. Crit. Rev. Food Sci. Nutr. 2007, 47(2):113-126.
88. Deisingh A.K., Stone D.C., Thompson M. Applications of Electronic Noses and Tongues in Food Analysis. Int. J. Food Sci. Technol. 2004, 39(6):587-604.
89. Ciosek P., Wroblewski W. The Analysis of Sensor Array Data with Various Pattern Recognition Techniques. Sens. Actuators B Chem. 2006, B114(1):85-93.
90. You C.-C., Miranda O.R., Gider B., Ghosh P.S., Kim Ik-Bum, Erdogan B., Krovi S.A., Bunz U.H.F., Rotello V.M. Detection and Identification of Proteins Using Nanoparticle-Fluorescent Polymer 'Chemical Nose' Sensors. Nat. Nanotechnol. 2007, 2:318-323.
91. Acree T.E., Barnard J., Cunningham D.G. A Procedure for Sensory Analysis of Gas Chromatograph Effluents. Food Chem. 1984, 14:273-286.
92. Delahunty C.M., Eyres G., Dufour J.P. Gas Chromatography-Olfactometry. J. Sep. Sci. 2006, 29(14):2107-2125.
93. Kamadia V.V., Yoon Y., Schilling M.W., Marshall D.L. Relationships between Odorant Concentration and Aroma Intensity. J. Food Sci. 2006, 71(3):S193-S197.
94. Barbano D.M., Lynch J.M. Major Advances in Testing of Dairy Products: Milk Component and Dairy Product Attribute Testing. J. Dairy Sci. 2006, 89(4):1189-1194.
95. Gambaro A., Ares G., Gimenez A. Shelf-Life Estimation of Apple-Baby Food. J. Sens. Stud. 2006, 21(1):101-111.
96. Garitta L.V., Serrat C., Hough G.E., Curia A.V. Determination of Optimum Concentrations of a Food Ingredient Using Survival Analysis Statistics. J. Food Sci. 2006, 71(7):S526-S532.
97. Luz Calle M., Hough G., Curia A., Gomez G. Bayesian Survival Analysis Modeling Applied to Sensory Shelf Life of Foods. Food Qual. Prefer. 2006, 17:307-312.
98. Klein J.P., Moeschberger M.L. Survival Analysis: A Self Learning Text 1997, Springer-Verlag, New York.
99. Noble A.C., Arnold R.A., Buechsenstein J., Leach E.J., Schmidt J.O., Stern P.M. Modification of a Standardized System of Wine Aroma Terminology. Am. J. Enol. Vitic. 1987, 38(2):143-146.
100. Lee S.J., Lee J.E., Kim S.S., Koh K.H. Development of Korean Red Wines Using Vitis labrusca Varieties: Instrumental and Sensory Characterization. Food Chem. 2006, 94(3):385-393.
101. Durante C., Cocchi M., Grandi M., Marchetti A., Bro R. Application of N-PLS to Gas Chromatographic and Sensory Data of Traditional Balsamic Vinegars of Modena. Chemom. Intell. Lab. Syst. 2006, 83(1):54-65.
102. Cozzolino D., Smyth H.E., Lattey K.A., Cynkar W., Janik L., Dambergs R.G., Francis I.L., Gishen M. Combining Mass Spectrometry Based Electronic Nose, Visible-Near Infrared Spectroscopy and Chemometrics to Assess the Sensory Properties of Australian Riesling Wines. Anal. Chim. Acta 2006, 563(1-2):319-324.
103. Pereira R., Matia-Merino L., Jones V., Singh H. Influence of Fat on the Perceived Texture of Set Acid Milk Gels: A Sensory Perspective. Food Hydrocoll. 2006, 20(2-3):305-313.
104. Alonso-Salces R.M., Barranco A., Abad B., Berrueta L.A., Gallo B., Vicente F. Polyphenolic Profiles of Basque Cider Apple Cultivars and Their Technological Properties. J. Agric. Food Chem. 2004, 52(10):2938-2952.
105. Angerosa F., DiGiacinto L., Vito R., Cumitini S. Sensory Evaluation of Virgin Olive Oils by Artificial Neural Network Processing of Dynamic Head-Space Gas Chromatographic Data. J. Sci. Food Agric. 1996, 72(3):323-328.
106. Biasioli F., Gasperi F., Aprea E., Endrizzi I., Framondino V., Marini F., Mott D., Mark T.D. Correlation of PTR-MS Spectral Fingerprints with Sensory Characterisation of Flavour and Odour Profile of 'Trentingrana' Cheese. Food Qual. Prefer. 2006, 17(1-2):63-75.
107. Boselli E., Minardi M., Giomo A., Frega N.G. Phenolic Composition and Quality of White d.o.c. Wines from Marche (Italy). Anal. Chim. Acta 2006, 563(1-2):93-100.
108. Chammas I.G., Saliba R., Beal C. Characterization of the Fermented Milk 'Laban' with Sensory Analysis and Instrumental Measurements. J. Food Sci. 2006, 71(2):S156-S162.
109. Chida M., Yamashita K., Izumiya Y., Watanabe K., Tamura H. Aroma Impact Compounds in Three Citrus Oils: Cross-Matching Test and Correspondence Analysis Approach. J. Food Sci. 2006, 71(1):S54-S58.
110. Choi U.-K., Kim M.-H., Kwon O.J., Lee T.-J., Lee N.-H. Characterization of Aroma Components in Barley Bran Sauce Using Statistical Analysis. Food Sci. Biotechnol. 2007, 16(1):23-28.
111. Chung S.J., Heymann H., Grun I.U. Application of GPA and PLSR in Correlating Sensory and Chemical Data Sets. Food Qual. Prefer. 2003, 14(5-6):485-495.
112. Corrigan V.K., Hedderley D.I., Hurst P.L. Assessment of Objective Texture Measurements for Characterising and Predicting the Sensory Quality of Squash ( Cucurbita maxima). N. Z. J. Crop Hortic. Sci. 2006, 34(4):369-379.
113. Crisosto C.H., Crisosto G.M., Echeverria G., Puy J. Segregation of Plum and Pluot Cultivars According to Their Organoleptic Characteristics. Postharvest Biol. Technol. 2007, 44(3):271-276.
114. Fagan C.C., Everard C., O'Donnell C.P., Downey G., Sheehan E.M., Delahunty C.M., O'Callaghan D.J. Evaluating Mid-Infrared Spectroscopy as a New Technique for Predicting Sensory Texture Attributes of Processed Cheese. J. Dairy Sci. 2007, 90(3):1122-1132.
115. Gasperi F., Gallerani G., Boschetti A., Biasioli F., Monetti A., Boscaini E., Jordan A., Lindinger W., Iannotta S. The Mozzarella Cheese Flavour Profile: A Comparison between Judge Panel Analysis and Proton Transfer Reaction Mass Spectrometry. J. Sci. Food Agric. 2001, 81(3):357-363.
116. Iizuka K., Takasaki S., Suzuki A., Morita K., Aishiina T. Comparison of Three Varieties of Pork Using Quantitative Descriptive Analysis (QDA). J. Jap. Soc. Food Sci. Technol.-Nippon Shokuhin Kagaku Kogaku Kaishi 2006, 53(1):23-30.
117. Ikeda G., Tomizawa A., Imayoshi Y., Iwabuchi H., Hinata T., Sagara Y. Flavor Design of Sesame-Flavored Dressing Using Gas Chromatography/Olfactometry and Food Kansei Model. Food Sci. Technol. Res. 2006, 12(4):261-269.
118. Isleib T.G., Pattee H.E., Sanders T.H., Hendrix K.W., Dean L.O. Compositional and Sensory Comparisons between Normal- and High-Oleic Peanuts. J. Agric. Food Chem. 2006, 54(5):1759-1763.
119. Jahan K., Paterson A., Spickett C.M. Relationships between Flavour, Lipid Composition and Antioxidants in Organic, Free-Range and Conventional Chicken Breasts from Modelling. Int. J. Food Sci. Nutr. 2006, 57(3-4):229-243.
120. Jensen P.N., Sorensen G., Engelsen S.B., Bertelsen G. Evaluation of Quality Changes in Walnut Kernels ( Juglans regia L.) by Vis/NIR Spectroscopy. J. Agric. Food Chem. 2001, 49(12):5790-5796.
121. Kallithraka S., Arvanitoyannis I.S., Kefalas P., El-Zajouli A., Soufleros E., Psarra E. Instrumental and Sensory Analysis of Greek Wines; Implementation of Principal Component Analysis (PCA) for Classification According to Geographical Origin. Food Chem. 2001, 73(4):501-514.
122. Kihlberg I., Ostrom A., Johansson L., Risvik E. Sensory Qualities of Plain White Pan Bread: Influence of Farming System, Year of Harvest and Baking Technique. J. Cereal Sci. 2006, 43(1):15-30.
123. Le Quere J.M., Husson F., Renard C., Primault J. French Cider Characterization by Sensory, Technological and Chemical Evaluations. LWT - Food Sci. Technol. 2006, 39(9):1033-1044.
124. Lebecque A., Laguet A., Devaux M.F., Dufour E. Delineation of the Texture of Salers Cheese by Sensory Analysis and Physical Methods. Lait 2001, 81(5):609-624.
125. Lillo M.P.Y., Agosin E., Latrille E. Chemical Markers for Tracking the Sensory Contribution of Production Stages in Muscat Wine Distillates. J. Food Sci. 2005, 70(7):S432-S441.
126. Luna G., Morales M.T., Aparicio R. Characterisation of 39 Varietal Virgin Olive Oils by Their Volatile Compositions. Food Chem. 2006, 98(2):243-252.
127. Mildner-Szkudlarz S., Jelen H.H., Zawirska-Wojtasiak R., Wasowicz E. Application of Headspace - Solid Phase Microextraction and Multivariate Analysis for Plant Oils Differentiation. Food Chem. 2003, 83(4):515-522.
128. Moller J.K.S., Parolari G., Gabba L., Christensen J., Skibsted L.H. Monitoring Chemical Changes of Dry-Cured Parma Ham during Processing by Surface Autofluorescence Spectroscopy. J. Agric. Food Chem. 2003, 51(5):1224-1230.
129. Morand E., Pages J. Procrustes Multiple Factor Analysis to Analyse the Overall Perception of Food Products. Food Qual. Prefer. 2006, 17(1-2):36-42.
130. Morita K., Kubota K., Aishima T. Comparing Sensory and Gas Chromatographic Profiles in Aromas of Boiled Squid, Prawn, and Scallop Using Full Factorial Design. J. Food Sci. 2002, 67(9):3456-3462.
131. Panda S.H., Parmanick M., Ray R.C. Lactic Acid Fermentation of Sweet Potato ( Ipomoea batatas L.) into Pickles. J. Food Process. Preserv. 2007, 31(1):83-101.
132. Pedro A.M.K., Ferreira M.M.C. Multivariate Accelerated Shelf-Life Testing: A Novel Approach for Determining the Shelf-Life of Foods. J. Chemom. 2006, 20(1-2):76-83.
133. Pereira R.B., Singh H., Munro P.A., Luckman M.S. Sensory and Instrumental Textural Characteristics of Acid Milk Gels. Int. Dairy J. 2003, 13(8):655-667.
134. Petka J., Ferreira V., Gonzalez-Vinas M.A., Cacho J. Sensory and Chemical Characterization of the Aroma of a White Wine Made with Devin Grapes. J. Agric. Food Chem. 2006, 54(3):909-915.
135. Pihlsgard P., Larsson M., Leufven A., Lingnert H. Chemical and Sensory Properties of Liquid Beet Sugar. J. Agric. Food Chem. 1999, 47(10):4346-4352.
136. Ritvanen T., Lampolahti S., Lilleberg L., Tupasela T., Isoniemi M., Appelbye U., Lyytikainen T., Eerola S., Uusi-Rauva E. Sensory Evaluation, Chemical Composition and Consumer Acceptance of Full Fat and Reduced Fat Cheeses in the Finnish Market. Food Qual. Prefer. 2005, 16(6):479-492.
137. Tournier C., Martin C., Guichard E., Issanchou S., Sulmont-Rosse C. Contribution to the Understanding of Consumers' Creaminess Concept: A Sensory and a Verbal Approach. Int. Dairy J. 2007, 17(5):555-564.
138. Varona L., Hernandez P. A Multithreshold Model for Sensory Analysis. J. Food Sci. 2006, 71(4):S333-S336.
139. Villarroel M., Pino L., Hazbun J. Development of an Optimized Formulation of Flaxseed ( Linum usitatissimum) Mousse. Arch. Latinoam. Nutr. 2006, 56(2):185-191.