Bayesian networks for food science: theoretical background and potential applications

V.A. Phan, M. Dekker, U. Garczarek, M.A.J.S. van Boekel

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

2 Citations (Scopus)


Although Bayesian networks have gained popularity in many fields, they have just recently emerged in food-related problems. This technique can be used as a tool for prediction, explanation, exploration or decision making under uncertainty. The chapter mainly gives a theoretical background of Bayesian networks through a food example. It also discusses the advantages and challenges, as well as potential applications of Bayesian networks in the food area.
Original languageEnglish
Title of host publicationConsumer-driven innovation in food and personal care products
EditorsS.R. Jaeger, H. MacFie
Place of PublicationCambridge
Number of pages662
Publication statusPublished - 2010

Publication series

NameWoodhead Food Series
PublisherWoodhead Publishing Limited


  • Bayesian network theory
  • Food design
  • Modeling in food science
  • Prediction
  • Uncertainty


Dive into the research topics of 'Bayesian networks for food science: theoretical background and potential applications'. Together they form a unique fingerprint.

Cite this