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Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain : Wageningen UR Frontis Series - M.A.J.S. van Boekel

Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain

Wageningen UR Frontis Series

By: M.A.J.S. van Boekel (Editor), A.H.C van Bruggen (Editor), A. Stein (Editor)

Hardcover

Published: 31st March 2004
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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.

Preface
Introduction to Bayesian statistics
Bayesian statistics and the agro-food production chain
Bayesian solutions for food-science problems?
Methodology
Bayesian statistics: principles and benefits
Calibration in a Bayesian modelling framework
Bayesian methods for updating crop-model predictions, applications for predicting biomass and grain protein content
Bayesian approaches to quality and safety in primary food production
Applying prior knowledge to model batch keeping-quality of cucumber batches
Risk-analysis of human pathogen spread in the vegetable industry: a comparison between organic and conventional production chains
Are Bayesian approaches useful in plant pathology?
Bayesian approaches to quality and safety in food technology
Bayesian networks and food security: an introduction
Application of Bayesian belief network models to food-safety science
Bayesian approaches in the food chain, nutrition and epidemiology
Bayesian statistics for infection experiments
Quantitative modelling in design and operation of food supply systems
Some explorations into Bayesian modelling of risks due to pesticide intake from food
General discussion and conclusion
List of participants
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9781402019166
ISBN-10: 1402019165
Series: Wageningen UR Frontis Series
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 163
Published: 31st March 2004
Publisher: Springer-Verlag New York Inc.
Country of Publication: US
Dimensions (cm): 23.5 x 15.5  x 1.12
Weight (kg): 0.93