Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 427434
Title Bringing the voice of consumers into plant breeding with Bayesian modelling
Author(s) Tesfaye, L.M.; Bink, M.C.A.M.; Lans, I.A. van der; Gremmen, B.; Trijp, H.C.M. van
Source Euphytica 189 (2013)3. - ISSN 0014-2336 - p. 365 - 378.
Department(s) Marketing and Consumer Behaviour
Biometris (PPO/PRI)
Applied Philosophy Group
Methodical Ethics and Technology Assessment
Publication type Refereed Article in a scientific journal
Publication year 2013
Keyword(s) marker-assisted selection - quantitative trait loci - product development - crop improvement - quality guidance - chemical traits - tomatoes - genomics - preferences - tool
Abstract Improving flavour quality traits in fruit breeding calls for innovative consumer-oriented product development. This paper explores the potential of marker-assisted breeding from genomics and consumer-based quality-improvement models from marketing, and exploits the progresses at both sides as technology push and market pull. An integrative and cross-disciplinary quality-improvement model is proposed based on Bayesian modelling. This Bayesian modelling allows for the integration of elicited knowledge of breeders and flavour researchers concerning the degree of causal associations of metabolites and flavour quality traits of fruits in the model. We also present the flavour quality improvement challenge as a multi-criteria optimization process and show the potential and current limitations of the proposed model. Insights gained from the model would help flavour researchers determine the optimum concentration of flavour-affecting metabolites which could be used for further DNA marker development. These ideas and concepts will help translate consumer-desired product features into genomic information, ultimately resulting in successful new cultivars
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