Chapter 5 – Multivariate Data Analysis for Product Development and Optimisation

This chapter describes the multivariate data analytical methods used for sensory analysis and includes a general introduction to bilinear modelling (BLM), principal component analysis, naive assessor reliability testing, generalised Procrustes analysis and partial least squares regression. Internal, external and hybrid (PLS) preference mapping is also discussed with respect to the mapping of subjective consumer type data to objective data such as sensory descriptive, instrumental and physicochemical data. BLM is also used to demonstrate how multivariate data analysis can be used for the correlation of a multimodal and complex data set incorporating gas chromatography/mass spectrometry, electronic nose data and descriptive sensory data in a presented case study.

[1]  Harry T. Lawless,et al.  Perceptual mapping of apples and cheeses using projective mapping and sorting. , 2010 .

[2]  Magni Martens,et al.  Multivariate Analysis of Quality : An Introduction , 2001 .

[3]  J. Kerry,et al.  Impact on the physicochemical and sensory properties of salt reduced corned beef formulated with and without the use of salt replacers , 2018, LWT.

[4]  D. V. Byrne,et al.  DEVELOPMENT OF A SENSORY VOCABULARY FOR WARMED‐OVER FLAVOR: PART I. IN PORCINE MEAT , 1999 .

[5]  H. Martens,et al.  THE RELIABILITY OF NAÏVE ASSESSORS IN SENSORY EVALUATION VISUALIZED BY PRAGMATICAL MULTIVARIATE ANALYSIS , 2002 .

[6]  Garmt Dijksterhuis,et al.  Procrustes Analysis in Studying Sensory‐Instrumental Relations , 1994 .

[7]  J. Kerry,et al.  Impact of ingredient replacers on the physicochemical properties and sensory quality of reduced salt and fat black puddings. , 2016, Meat science.

[8]  T. Isaksson,et al.  Multivariate techniques in the analysis of meat quality. , 1996, Meat science.

[9]  M. Wilkinson,et al.  Utilisation of a cell‐free extract of lactic acid bacteria entrapped in yeast to enhance flavour development in Cheddar cheese , 2014 .

[10]  J. Kerry,et al.  Study on the influence of age, gender and familiarity with the product on the acceptance of vegetable soups. , 2010 .

[11]  Maurice G. O'Sullivan,et al.  Carbon dioxide flavour taint in modified atmosphere packed beef steaks , 2011 .

[12]  J. Kerry,et al.  Effect of varying salt and fat levels on the sensory and physiochemical quality of frankfurters. , 2012, Meat science.

[13]  Maurice G. O'Sullivan,et al.  A comparison of warmed-over flavour in pork by sensory analysis, GC/MS and the electronic nose. , 2003, Meat science.

[14]  H. Martens,et al.  Modified Jack-knife estimation of parameter uncertainty in bilinear modelling by partial least squares regression (PLSR) , 2000 .

[15]  Tormod Næs,et al.  A comparison of Generalised Procrustes Analysis and Multiple Factor Analysis for projective mapping data , 2015 .

[16]  Maurice G. O'Sullivan,et al.  Use of sensory science as a practical commercial tool in the development of consumer-led processed meat products. , 2011 .

[17]  G. Fitzgerald,et al.  Assessment of wild non-dairy lactococcal strains for flavour diversification in a mini-Gouda type cheese model , 2014 .

[18]  John W. Hall,et al.  Comparison of projective mapping and sorting data collection and multivariate methodologies for identification of similarity-of-use of snack bars , 1998 .

[19]  Pieternel A. Luning,et al.  Internal versus external preference analysis : an exploratory study on end-user evaluation , 2006 .

[20]  Garmt Dijksterhuis,et al.  Multivariate data analysis in sensory and consumer science: An overview of developments , 1995 .

[21]  D. V. Byrne,et al.  Sensory and chemical assessment of pork supplemented with iron and vitamin E. , 2003, Meat science.

[22]  Morten Meilgaard,et al.  Sensory Evaluation Techniques , 2020 .

[23]  D. V. Byrne,et al.  Evaluation of pork colour sensory colour assessment using trained and untrained sensory panellists. , 2003, Meat science.

[24]  J. Kerry,et al.  Effect of varying salt and fat levels on the sensory quality of beef patties. , 2012, Meat science.

[25]  R. Cattell,et al.  The Procrustes Program: Producing direct rotation to test a hypothesized factor structure. , 2007 .

[26]  J. Kerry,et al.  The impact of salt and fat level variation on the physiochemical properties and sensory quality of pork breakfast sausages. , 2013, Meat science.

[27]  J. Kerry,et al.  Effect of marinating time and low pH on marinade performance and sensory acceptability of poultry meat. , 2010, Meat science.

[28]  D. V. Byrne,et al.  Sensory and chemical investigations on the effect of oven cooking on warmed-over flavour development in chicken meat. , 2002, Meat science.

[29]  J. Kerry,et al.  Impact of varying salt and fat levels on the physicochemical properties and sensory quality of white pudding. , 2015, Meat science.

[30]  J. Kerry,et al.  Investigation of the influence of age, gender and consumption habits on the liking of jam-filled cakes , 2010 .

[31]  J. Gower.  Generalized procrustes analysis , 1975 .

[32]  D. V. Byrne,et al.  Sensory panel consistency during development of a vocabulary for warmed-over flavour , 2001 .

[33]  J. Kerry,et al.  Use of optical oxygen sensors to monitor residual oxygen in pre- and post- pasteurised bottled beer , 2012 .

[34]  J. Kerry,et al.  Use of smart packaging technologies for monitoring and extending the shelf-life quality of modified atmosphere packaged (MAP) bread: application of intelligent oxygen sensors and active ethanol emitters , 2013, European Food Research and Technology.

[35]  M. Wilkinson,et al.  Utilisation of microfluidisation to enhance enzymatic and metabolic potential of lactococcal strains as adjuncts in Gouda type cheese , 2014 .

[36]  J. Kerry,et al.  Resting of MAP (modified atmosphere packed) beef steaks prior to cooking and effects on consumer quality. , 2015, Meat science.

[37]  Gastón Ares,et al.  Sensory profiling, the blurred line between sensory and consumer science. A review of novel methods for product characterization , 2012 .

[38]  H. Macfie.  23 – Preference mapping and food product development , 2007 .

[39]  J. Kerry,et al.  Application of soy protein coatings and their effect on the quality and shelf-life stability of beef patties , 2015 .

[40]  Garmt Dijksterhuis,et al.  Procrustes Analysis in Sensory Research , 1996 .

[41]  D. V. Byrne,et al.  Evaluation of pork colour: prediction of visual sensory quality of meat from instrumental and computer vision methods of colour analysis. , 2003, Meat science.

[42]  Einar Risvik,et al.  Evaluation of sensory profiling and projective mapping data , 1997 .

[43]  Michel Tenenhaus,et al.  The use of partial least squares methods in new food product development , 2007 .

[44]  D. V. Byrne,et al.  Sensory colour assessment of fresh meat from pigs supplemented with iron and vitamin E. , 2002, Meat science.

[45]  J. Kerry,et al.  Nondestructive and continuous monitoring of oxygen levels in modified atmosphere packaged ready-to-eat mixed salad products using optical oxygen sensors, and its effects on sensory and microbiological counts during storage. , 2013, Journal of food science.

[46]  Harald Martens,et al.  LPLS-regression: a method for prediction and classification under the influence of background information on predictor variables , 2008 .

[47]  Hildegarde Heymann,et al.  PROJECTIVE MAPPING AND DESCRIPTIVE ANALYSIS OF MILK AND DARK CHOCOLATES , 2009 .

[48]  J. Kerry,et al.  Effect of using ingredient replacers on the physicochemical properties and sensory quality of low-salt and low-fat white puddings , 2016, European Food Research and Technology.

[49]  J. Kerry,et al.  Assessment and Use of Optical Oxygen Sensors as Tools to Assist in Optimal Product Component Selection for the Development of Packs of Ready-to-Eat Mixed Salads and for the Non-Destructive Monitoring of in-Pack Oxygen Levels Using Chilled Storage , 2013, Foods.