XU Xiaoqing, SU Qingyu, WANG Dong, et al. Application of Multiple Factor Analysis in Sensory Studies of Food and Beverage Industry [J]. Science and Technology of Food Industry, 2021, 42(13): 427−434. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2020090253.
Citation: XU Xiaoqing, SU Qingyu, WANG Dong, et al. Application of Multiple Factor Analysis in Sensory Studies of Food and Beverage Industry [J]. Science and Technology of Food Industry, 2021, 42(13): 427−434. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2020090253.

Application of Multiple Factor Analysis in Sensory Studies of Food and Beverage Industry

More Information
  • Received Date: September 23, 2020
  • Available Online: May 10, 2021
  • Multiple factor analysis (MFA) is a method of multivariate statistical analysis that can be used to describe and summarize multi-group datasets with complex structures and sources. This method is closely related to the pinciple component analysis and has been widely used in the fields of food and beverage, cosmetics, epidemiology and ecology. This paper focuses on the theoretical basics and analyzing procedures of MFA. It also introduces recent research studies and using cases to summarize the application of MFA on projective mapping, napping, free choice profile, and consumer sensory liking driver exploration. It aims to provide guidance and reference for researchers in related fields.
  • [1]
    Escofier B, Pages J. Multiple factor analysis (AFMULT package)[J]. Computational Statistics & Data Analysis,1994,18(1):121−140.
    [2]
    Abdi H, Williams L J, Valentin D. Multiple factor analysis: Principal component analysis for multitable and multiblock data sets[J]. Wiley Interdisciplinary Reviews: Computational Statistics,2013,5(2):149−179. doi: 10.1002/wics.1246
    [3]
    Becuebertaut M, Sebastien L E. Analysis of multilingual labeled sorting tasks: Application to a cross-cultural study in wine industry[J]. Journal of Sensory Studies,2011,26(5):299−310. doi: 10.1111/j.1745-459X.2011.00345.x
    [4]
    Le S, Husson F, Pages J. Confidence ellipses applied to the comparison of sensory profiles[J]. Journal of Sensory Studies,2006,21(3):241−248. doi: 10.1111/j.1745-459X.2006.00064.x
    [5]
    Cadoret M, Le S, Pages J. Statistical analysis of hierarchical sorting data[J]. Journal of Sensory Studies,2011,26(2):96−105. doi: 10.1111/j.1745-459X.2010.00326.x
    [6]
    Pages J, Husson F. Multiple factor analysis with confidence ellipses: A methodology to study the relationships between sensory and instrumental data[J]. Journal of Chemometrics,2005,19(3):138−144. doi: 10.1002/cem.916
    [7]
    陆龙建, 陈磊, 余苓, 等. 多元因子分析在卷烟风格特征剖析中的应用[J]. 烟草科技,2012(10):36−40. doi: 10.3969/j.issn.1002-0861.2012.09.009
    [8]
    Nabiilah Salmaa Dwiranti A A, Nurul Asiah. Sensory attributes of cold brew coffee products at various resting time after roasting process[J]. Pelita Perkebunan (a Coffee and Cocoa Research Journal),2019,35(No 1):42−50. doi: 10.22302/iccri.jur.pelitaperkebunan.v35i1.349
    [9]
    Perrin L, Symoneaux R, Maître I, et al. Comparison of three sensory methods for use with the Napping® procedure: Case of ten wines from Loire valley[J]. Food Quality and Preference,2008,19(1):1−11. doi: 10.1016/j.foodqual.2007.06.005
    [10]
    区靖祥, 伍时照, 甄海, 等. 华南地区籼稻米质综合评分和分类方法的研究[J]. 华南农业大学学报,1997(3):4−9.
    [11]
    马辰. 长白山地森林土壤跳虫的分布格局及其对环境变化的响应[D]. 哈尔滨: 东北师范大学, 2019.
    [12]
    Zhang R, Xu Y, Han Z. A comparison analysis of chemical composition of aerosols in the dust and non-dust periods in Beijing[J]. Advances in Atmospheric Sciences,2004,21(2).
    [13]
    Brard M, Le S. Adaptation of the Q-methodology for the characterization of a complex concept through a set of products: From the collection of the data to their analysis[J]. Food Quality and Preference,2017,67(77-86).
    [14]
    Pagès J. Collection and analysis of perceived product inter-distances using multiple factor analysis: Application to the study of 10 white wines from the Loire Valley[J]. Food Quality and Preference,2005,16(7):642−649. doi: 10.1016/j.foodqual.2005.01.006
    [15]
    Kuusinen A, Patynen J, Tervo S, et al. Relationships between preference ratings, sensory profiles, and acoustical measurements in concert halls[J]. Journal of the Acoustical Society of America,2014,135(1):239−250. doi: 10.1121/1.4836335
    [16]
    Naes T, Berget I, Liland K H, et al. Estimating and interpreting more than two consensus components in projective mapping: INDSCAL vs. multiple factor analysis (MFA)[J]. Food Quality and Preference,2017,58:45−60.
    [17]
    Kostov B, Becuebertaut M, Husson F. An original methodology for the analysis and interpretation of word-count based methods: Multiple factor analysis for contingency tables complemented by consensual words[J]. Food Quality and Preference,2014,32(35-40).
    [18]
    Gutierrezsalomon A L, Gambaro A, Angulo O. Influence of sample presentation protocol on the results of consumer tests[J]. Journal of Sensory Studies,2014,29(3):219−232. doi: 10.1111/joss.12097
    [19]
    Cadena R S, Cruz A G, Netto R R, et al. Sensory profile and physicochemical characteristics of mango nectar sweetened with high intensity sweeteners throughout storage time[J]. Food Research International,2013,54(2):1670−1679. doi: 10.1016/j.foodres.2013.10.012
    [20]
    Kim S, Yang S, Cho M, et al. Understanding the drivers of liking for fresh pears: A cross-cultural investigation of Chinese and Korean panels and consumers[J]. Journal of the Science of Food and Agriculture,2019,99(11):5092−5101. doi: 10.1002/jsfa.9753
    [21]
    Dooley L M, Lee Y, Meullenet J. The application of check-all-that-apply (CATA) consumer profiling to preference mapping of vanilla ice cream and its comparison to classical external preference mapping[J]. Food Quality and Preference,2010,21(4):394−401. doi: 10.1016/j.foodqual.2009.10.002
    [22]
    Parente M E, Manzoni A V, Ares G. External preference mapping of commercial antiaging creams based on consumers' responses to a Check-All-That-Apply question[J]. Journal of Sensory Studies,2011,26(2):158−166. doi: 10.1111/j.1745-459X.2011.00332.x
    [23]
    De Morais E C, Esmerino E A, Monteiro R A, et al. Prebiotic low sugar chocolate dairy desserts: physical and optical characteristics and performance of parafac and PCA preference map[J]. Journal of Food Science,2016,81(1).
    [24]
    Risvik E, McEwan J A, Colwill J S, et al. Projective mapping: A tool for sensory analysis and consumer research[J]. Food Quality and Preference,1994,5(4):263−269. doi: 10.1016/0950-3293(94)90051-5
    [25]
    Risvik E, McEwan J A, Rødbotten M. Evaluation of sensory profiling and projective mapping data[J]. Food Quality and Preference,1997,8(1):63−71. doi: 10.1016/S0950-3293(96)00016-X
    [26]
    苏晓霞, 黄序, 黄一珍, 等. 快速描述性分析方法在食品感官评定中应用进展[J]. 食品科技,2013,38(7):298−303.
    [27]
    Morin M, Hayward L, Mcsweeney M B. Use of experienced panelists and the projective mapping task in comparison to trained panelists and naïve consumers[J]. Journal of Sensory Studies, 2018, 33(6).
    [28]
    Barcenas P, Elortondo F J P, Albisu M. Projective mapping in sensory analysis of ewes milk cheeses: A study on consumers and trained panel performance[J]. Food Research International,2004,37(7):723−729. doi: 10.1016/j.foodres.2004.02.015
    [29]
    Nestrud M A, Lawless H T. Perceptual mapping of apples and cheese using projective mapping and sorting[J]. Journal of Sensory Studies,2010,25(3):390−405. doi: 10.1111/j.1745-459X.2009.00266.x
    [30]
    田欣, 张会宁, 祁新春, 等. 快速感官分析技术在葡萄酒香气感官分析中的应用[J]. 食品与发酵工业,2019,45(21):215−220.
    [31]
    Byrnes N K, Nestrud M A, Hayes J E. Perceptual mapping of chemesthetic stimuli in naïve assessors[J]. Chemosensory Perception,2015,8(1):19−32. doi: 10.1007/s12078-015-9178-7
    [32]
    Kennedy J, Heymann H. Projective mapping and descriptive analysis of milk and dark chocolates[J]. Journal of Sensory Studies,2009,24(2):220−233. doi: 10.1111/j.1745-459X.2008.00204.x
    [33]
    Varela P, Berget I, Hersleth M, et al. Projective mapping based on choice or preference: An affective approach to projective mapping[J]. Food Research International,2017,100:241−251.
    [34]
    Pages J, Cadoret M, Le S. The sorted napping: A new holistic approach in sensory evaluation[J]. Journal of Sensory Studies,2010,25(5):637−658. doi: 10.1111/j.1745-459X.2010.00292.x
    [35]
    Park H, Le S, Hong J, et al. Sensory perception of yackwa (Korean traditional fried cookie) by consumer groups of different age using the sorted napping procedure[J]. Journal of Sensory Studies,2014,29(6):425−434. doi: 10.1111/joss.12123
    [36]
    Carroll J D, Chang J. Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition[J]. Psychometrika,1970,35(3):283−319. doi: 10.1007/BF02310791
    [37]
    Schlich P. Defining and validating assessor compromises about product distances and attribute correlations[M]. Multivariate analysis of data in sensory sciences. New York: Elsevier. 1996: 229-230.
    [38]
    Tucker L R. The extension of factor analysis in three-dimensional matrices.[M]//GULLIKSEN N F H. Contributions to mathematical psychology. New York: Holt, Rinehart and Winston. 1964.
    [39]
    Nestrud M A, Lawless H T. Perceptual mapping of citrus juices using projective mapping and profiling data from culinary professionals and consumers[J]. Food Quality and Preference,2008,19(4):431−438. doi: 10.1016/j.foodqual.2008.01.001
    [40]
    Tomic O, Berget I, Naes T. A comparison of generalised procrustes analysis and multiple factor analysis for projective mapping data[J]. Food Quality and Preference,2015,43(34-46).
    [41]
    Reinbach H C, Giacalone D, Ribeiro L M, et al. Comparison of three sensory profiling methods based on consumer perception: CATA, CATA with intensity and Napping[J]. Food Quality and Preference,2014,32(32):160−166.
    [42]
    Williams A A, Langron S P. The use of free-choice profiling for the evaluation of commercial ports[J]. Journal of the Science of Food and Agriculture,1984,35(5):558−568. doi: 10.1002/jsfa.2740350513
    [43]
    De Jong S, Heidema J, Der Knaap H C M V. Generalized procrustes analysis of coffee brands tested by five European sensory panels[J]. Food Quality and Preference,1998,9(3):111−114. doi: 10.1016/S0950-3293(97)00041-4
    [44]
    Gower J C. Generalized procrustes analysis[J]. Psychometrika,1975,40(1):33−51. doi: 10.1007/BF02291478
    [45]
    Liu J, Bredie W L P, Sherman E, et al. Comparison of rapid descriptive sensory methodologies: Free-choice profiling, flash profile and modified flash profile[J]. Food Research International,2018,106:892−900.
    [46]
    He W, Chung H Y. Multivariate relationships among sensory, physicochemical parameters, and targeted volatile compounds in commercial red sufus (Chinese fermented soybean curd): Comparison of QDA® and Flash Profile methods[J]. Food Research International,2019,125:108548.
    [47]
    Ares G, Gimenez A, Barreiro C, et al. Use of an open-ended question to identify drivers of liking of milk desserts. Comparison with preference mapping techniques[J]. Food Quality and Preference,2010,21(3):286−294. doi: 10.1016/j.foodqual.2009.05.006
    [48]
    Worch T. PrefMFA, a solution taking the best of both internal and external preference mapping techniques[J]. Food Quality and Preference,2013,30(2):180−191. doi: 10.1016/j.foodqual.2013.05.009
    [49]
    Pages J, Tenenhaus M. Multiple factor analysis combined with PLS path modelling. Application to the analysis of relationships between physicochemical variables, sensory profiles and hedonic judgements[J]. Chemometrics and Intelligent Laboratory Systems,2001,58(2):261−273. doi: 10.1016/S0169-7439(01)00165-4
    [50]
    Partidasedas J G, Ferreiro M N M, Vazquezoderiz M L, et al. Influence of the postharvest processing of the “Garnica” coffee variety on the sensory characteristics and overall acceptance of the beverage[J]. Journal of Sensory Studies, 2019.
    [51]
    Le S, Husson F. Sensominer: A package for sensory data analysis[J]. Journal of Sensory Studies,2008,23(1):14−25. doi: 10.1111/j.1745-459X.2007.00137.x
    [52]
    Escoufier Y. Le traitement des variables vectorielles[J]. Biometrics,1973,29(4):751. doi: 10.2307/2529140
  • Cited by

    Periodical cited type(4)

    1. 赵小勤,许莉,杨小艳,汪洋,罗霄,李及,张良,康帅,马双成. 智能感官技术在中药领域的应用研究进展. 中国药事. 2025(01): 96-104 .
    2. 刘玉璇,李倩倩,王宇慧,沈力,李泽玉,张璐璐,马超. 黄精“九蒸九制”过程中感官品质变化及其物质基础研究. 食品与发酵科技. 2025(01): 16-24 .
    3. 马景余,孙涛,王彦荣,李鑫,曾婉晴,王志强. 基于电子舌和电子眼信息融合的贝母品种快速辨识方法. 食品工业科技. 2024(18): 9-18 . 本站查看
    4. 王雪芹,程启康. 新鲜莲子营养成分影响因素及保鲜技术研究进展. 现代农业科技. 2024(19): 121-124+131 .

    Other cited types(1)

Catalog

    Article Metrics

    Article views (410) PDF downloads (41) Cited by(5)

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return