Articoli correlati a Bayesian Statistics and Quality Modelling in the Agro-Food...

Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain: Proceedings of the Frontis Workshop on Bayesian Statistics and Quality ... Wageningen, The Netherlands, 1-14 May 2003: 3 - Rilegato

 
9781402019166: Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain: Proceedings of the Frontis Workshop on Bayesian Statistics and Quality ... Wageningen, The Netherlands, 1-14 May 2003: 3
Rilegato
ISBN 10: 1402019165 ISBN 13: 9781402019166
Casa editrice: Kluwer Academic Pub, 2004

Sinossi

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Dalla quarta di copertina

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Kluwer Academic Pub
Data di pubblicazione
2004
Lingua
Inglese
ISBN 10 
1402019165
ISBN 13 
9781402019166
Rilegatura
Copertina rigida
Numero di pagine
163
Redattore
Van Boekel M.A.J.S., Stein A., Van Bruggen A.H.C.
Contatto del produttore
Springer Nature Customer Service Center GmbH
ProductSafety@springernature.com

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