Taking consumer quality perceptions into account is very important for new-fruit product development in todays competitive food market. To this end, consumer-oriented quality improvement models like the Quality Guidance Model (QGM) have been proposed. Implementing such mod- els in the agro industry is challenging. We propose the use of Bayesian Structure Equation Modelling (SEM) for parameterizing the Quality Guid- ance Model, allowing for the integration of elicited expert knowledge. Such casual modelling would furnish important insights for determining the opti- mal fruit product in terms of consumer avour-quality perceptions. In the context of tomato breeding, where we have data about metabolites, sensory- panel judgments, and consumer avour-quality perceptions, we estimated a benchmark Bayesian SEM using non-informative priors, starting from an initial causal model derived from the data with a score-based Bayesian Network (BN) learning algorithm. The results so far have given some in- dication of the importance of accounting for consumer heterogeneity in the modeling process.
|Title of host publication||The Contribution of Young Researchers to Bayesian Statistics - Proceedings of BAYSM 2013|
|Publication status||Published - 2014|
|Event||BAYSM2013 - |
Duration: 5 Jun 2013 → 6 Jun 2013
|Name||Springer Proceedings in Mathematics and Statistics|
|Period||5/06/13 → 6/06/13|
Tesfaye, L. M., van der Lans, I. A., Bink, M. C. A. M., Gremmen, H. G. J., & van Trijp, J. C. M. (2014). Consumer-Oriented New Product Development in Fruit Flavour Breeding: A Bayesian Approach. In The Contribution of Young Researchers to Bayesian Statistics - Proceedings of BAYSM 2013 (pp. 113-119). (Springer Proceedings in Mathematics and Statistics; Vol. 63). https://doi.org/10.1007/978-3-319-02084-6_23