Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain (Paperback, 2004 ed.)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Wageningen UR Frontis Series, 3
Release date:	March 2004
First published:	August 2004
Editors:	M.A.J.S. van Boekel • A. Stein • A.H.C van Bruggen
Dimensions:	279 x 216 x 10mm (L x W x T)
Format:	Paperback
Pages:	163
Edition:	2004 ed.
ISBN-13:	978-1-4020-1917-3
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Business & Economics > Industry & industrial studies > Primary industries > Agriculture & related industries Promotions
LSN:	1-4020-1917-3
Barcode:	9781402019173

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