Premium
VALIDATING A GRAPH THEORETIC SCREENING APPROACH TO FOOD ITEM COMBINATIONS
Author(s) -
NESTRUD MICHAEL A.,
ENNIS JOHN M.,
FAYLE CHARLES M.,
ENNIS DANIEL M.,
LAWLESS HARRY T.
Publication year - 2011
Publication title -
journal of sensory studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.61
H-Index - 53
eISSN - 1745-459X
pISSN - 0887-8250
DOI - 10.1111/j.1745-459x.2011.00348.x
Subject(s) - computer science , graph , product (mathematics) , machine learning , data mining , theoretical computer science , mathematics , geometry
Tools from the mathematical field of graph theory potentially allow the consumer scientist to efficiently analyze large numbers of combinations of food items, such as components on a salad. In this study, we tested the validity of such an approach. We began by asking subjects whether or not pairs of ingredients would be appropriate to combine on a salad. Next, using graph theoretic methods, we predicted which combinations of 3–8 components should go together, and perhaps more importantly, which combinations should not. Subjects were then asked whether or not particular combinations were appropriate to combine on a salad. A paired Wilcoxon test between the predicted and nonpredicted combinations was significant for all combination sizes. PRACTICAL APPLICATIONS A consumer‐driven graph theory methodology provides a screening tool to quickly and efficiently reduce a vast number of combinations of food items down to a reasonable number, which can then be evaluated by the consumer scientist using suitability criteria together with more traditional tools. In the case of salads, we screened over 1.7 million combinations and determined all but a handful were unsuitable. This methodology has potential in menu development, portfolio design and individual product formulations. The advantage to the researcher is that the method can be inexpensively performed, is nonbiased and is comprehensive. This study validates the use of this approach in a particular screening application.