Optimal operating conditions calculation for a pork meat dehydration–impregnation–soaking process
| Autor: | Antoine Collignan, Bertrand Broyart, A. Olmos, Gilles Trystram, Isabelle Poligne, Ioan-Cristian Trelea |
|---|---|
| Přispěvatelé: | Génie industriel alimentaire (GENIAL), Institut National de la Recherche Agronomique (INRA)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut National Agronomique Paris-Grignon (INA P-G)-Ecole Nationale Supérieure des Industries Agricoles et alimentaires, Génie et Microbiologie des Procédés Alimentaires (GMPA), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, MRST, Chambre de Commerce et d'Industrie de la Réunion (CCI Réunion), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad) |
| Jazyk: | angličtina |
| Rok vydání: | 2004 |
| Předmět: |
optimal
Optimization problem Viande séchée [SDV]Life Sciences [q-bio] Flavour rendement 02 engineering and technology Viande porcine batch Immersion 0202 electrical engineering electronic engineering information engineering dynamic optimization Solution Process engineering Mathematics dynamic Process (computing) 04 agricultural and veterinary sciences 040401 food science Durée 020201 artificial intelligence & image processing Schedule osmotic drying Méthode d'optimisation Raw material 0404 agricultural biotechnology Q02 - Traitement et conservation des produits alimentaires pork meat Q04 - Composition des produits alimentaires Sequential quadratic programming business.industry modeling Séchage Yield (chemistry) Séchage osmotique business Constant (mathematics) control Food Science |
| Zdroj: | LWT-Food Science and Technology LWT-Food Science and Technology, Elsevier, 2004, 37 (7), pp.763-770. ⟨10.1016/j.lwt.2004.02.010⟩ Lebensmittel-Wissenschaft und Technologie-Food Science and Technology |
| ISSN: | 0023-6438 1096-1127 |
| DOI: | 10.1016/j.lwt.2004.02.010⟩ |
| Popis: | Mass yield and operating time for a pork meat dehydration–impregnation–soaking (DIS) process were optimized using a coupled genetic algorithm/sequential quadratic programming method in order to obtain the optimal operating conditions: temperature and soaking solution concentrations. The DIS process was simulated by a neural network model. The non-linear optimization problem was constrained to ensure the main product characteristics: stability indicated by the water activity target and flavour characterized by the phenol gain target. The climatic conditions, the model validity region, the raw material costs and the operator working schedule were taken into account. Optimal solutions are discussed for three different batch configurations: single-stage processing under constant conditions, single-stage processing under varying temperature and two-stage processing under constant conditions. The most convenient operation resulted in a two-stage soaking process because of time, energy and cost savings, control convenience, product cooling anticipation and a reasonably high mass yield. |
| Databáze: | OpenAIRE |
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