Cluster analysis: Application in food science and technology

Author(s):  
Gastón Ares
Author(s):  
J Chapman ◽  
A Power ◽  
S Chandra ◽  
J Roberts ◽  
D Cozzolino

Food Control ◽  
2021 ◽  
Vol 127 ◽  
pp. 108116
Author(s):  
John Dzikunoo ◽  
Emmanuel Letsyo ◽  
Zeenatu Adams ◽  
David Asante-Donyinah ◽  
Courage Sedem Dzah

Foods ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1128
Author(s):  
Giacomo Squeo ◽  
Davide De Angelis ◽  
Riccardo Leardi ◽  
Carmine Summo ◽  
Francesco Caponio

Background: Mixtures play a key role in Food Science and Technology. For studying them, rational approaches should be used. In detail, the experimental designs for mixtures are useful tools for studying the effects of ingredients/components in formulations. Results: Food Science and Technology is the fourth category among the total records considered in this review. The applications span from food formulation to the composition of modified atmosphere, shelf-life improvement and bioactives extraction. However, the majority of the studies regards few products and ingredients. Simplex-lattice and simplex-centroid designs are the most common used, although some optimal designs, such as the D-optimal, have also interesting applications. Finally, some issues are highlighted, which basically regard the interpretation of the models coefficients and the lack of model validation. Conclusion: In the last decade, mixture designs have been fairly used in the field of Food Science and Technology. Modeling the response(s) allows researchers to achieve a global knowledge of the system under study within the defined experimental domain. However, the majority of application has regarded limited classes of products, and thus an increase in the spectrum of applications is desired.


2011 ◽  
Vol 53 (3) ◽  
pp. 391-414 ◽  
Author(s):  
Michael N. Tuma ◽  
Reinhold Decker ◽  
Sören W. Scholz

Market segmentation is a widely accepted concept in marketing research and planning. Although cluster analysis has been extensively applied to segment markets in the last 50 years, the ways in which the results were obtained have often been reported to be less than satisfactory by both practitioners (Yankelovich & Meer 2006) and academics (Dolnièar 2003). In order to provide guidance to those undertaking market segmentation, this study discusses the critical issues involved when using cluster analysis to segment markets, makes suggestions for best practices and potential improvements, and presents an empirical survey that seeks to provide an up-to-date assessment of cluster analysis application in market segmentation within a six-stage framework. Analyses of more than 200 journal articles published since 2000, in which cluster analysis was empirically used in a marketing research setting, indicate that many critical issues are still ignored rather than addressed adequately.


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