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Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain (Paperback, 2004 ed.)
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Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain (Paperback, 2004 ed.)
Series: Wageningen UR Frontis Series, 3
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The food market is changing from a producer-controlled to a
consumer-directed market. A main driving force is consumer concern
about agricultural production methods and food safety. More than
before, the consumer demands transparency of the production and
processing chain.
A food chain can be quite complex and the use of models has become
indispensable to handle this complexity. Modelling tools are
becoming increasingly important to guide the decisions for
production of high-quality and safe agricultural foods. With the
aid of models it becomes possible to control and predict quality
attributes, so that product innovation can be done more
efficiently. However, quality is an elusive concept, and there is
always an aspect of subjectivity and uncertainty.
A novel approach in the agro-food chain would be to tackle
subjective elements and uncertainty in modelling by using Bayesian
statistics and Bayesian Belief Networks. Bayesian approaches use
prior probabilities (partly accounting for subjectivity) to
estimate posterior probabilities, resulting in higher accuracy than
is possible with classical statistical techniques. Thus, the
variability and uncertainty in data and decisions, inherent in a
complex food chain, can be dealt with.
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