The free-linking task: A graph-inspired method for generating non-disjoint similarity data with food products

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dc.contributor.authorLahne, Jacoben
dc.contributor.authorPhetxumphou, Katherineen
dc.contributor.authorTejedor-Romero, Marinoen
dc.contributor.authorOrden, David R.en
dc.date.accessioned2021-12-17T15:01:33Zen
dc.date.available2021-12-17T15:01:33Zen
dc.date.issued2022-01-01en
dc.date.updated2021-12-17T15:01:31Zen
dc.description.abstract“Free sorting”, in which subjects are asked to sort a set of items into groups of “most similar” items, is increasingly popular as a technique for profiling sets of foods. However, free sorting implies an unrealistic model of sample similarity: that similarity is purely binary (is/is not similar) and that similarity is fully transitive (similarities {A, B} and {B, C} imply {A, C}). This paper proposes a new method of rapid similarity testing—the “free-linking” task—that solves both problems: in free linking, subjects draw a similarity graph in which they connect pairs of samples with a line if they are similar, according to the subject's individual criteria. This simple task provides a more realistic model of similarity which allows degrees of similarity through the graph distance metric and does not require transitive similarity. In two pilot studies with spice blends (10 samples, 58 subjects) and chocolate bars (10 samples, 63 subjects), free linking and free sorting are evaluated and compared using DISTATIS, RVb, and the graph parameters degree, transitivity, and connectivity; subjects also indicated their preferences and ease-of-use for the tasks. In both studies, the first two dimensions of the DISTATIS consensus were highly comparable across tasks; however, free linking provided more discrimination in dimensions three and four. RVb stability was equivalent for the two methods. Graph statistics indicated that free linking had greater discrimination power: on average subjects made similarity groupings with lower degree, lower transitivity, and higher connectivity for free linking in both studies. However, subjects did overall find free sorting easier and liked it more, indicating a higher cognitive difficulty of free linking. The free-linking task, therefore, provides more robust, realistic similarity maps at the cost of higher panelist effort, and should prove a valuable alternative for rapid sensory assessment of product sets.en
dc.description.versionAccepted versionen
dc.format.extent11 page(s)en
dc.format.mimetypeapplication/pdfen
dc.identifierARTN 104355 (Article number)en
dc.identifier.doihttps://doi.org/10.1016/j.foodqual.2021.104355en
dc.identifier.eissn1873-6343en
dc.identifier.issn0950-3293en
dc.identifier.orcidLahne, Jacob [0000-0002-2344-1816]en
dc.identifier.urihttp://hdl.handle.net/10919/107093en
dc.identifier.volume95en
dc.language.isoenen
dc.publisherElsevieren
dc.relation.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000701603400012&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=930d57c9ac61a043676db62af60056c1en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectLife Sciences & Biomedicineen
dc.subjectFood Science & Technologyen
dc.subjectSensometricsen
dc.subjectFree sortingen
dc.subjectFree linkingen
dc.subjectDISTATISen
dc.subjectGraph theoryen
dc.subjectNetwork theoryen
dc.subjectFood Scienceen
dc.subject0908 Food Sciencesen
dc.subject1505 Marketingen
dc.titleThe free-linking task: A graph-inspired method for generating non-disjoint similarity data with food productsen
dc.title.serialFood Quality and Preferenceen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherArticleen
dc.type.otherJournalen
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Agriculture & Life Sciencesen
pubs.organisational-group/Virginia Tech/Agriculture & Life Sciences/Food Science and Technologyen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Agriculture & Life Sciences/CALS T&R Facultyen

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