A primer on predictive techniques for food and bioresources transformation processes

Autor: Jason Sicard, Sophie Barbe, Rachel Boutrou, Laurent Bouvier, Guillaume Delaplace, Gwenaëlle Lashermes, Laëtitia Théron, Olivier Vitrac, Alberto Tonda
Přispěvatelé: Qualité des Produits Animaux (QuaPA), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Toulouse Biotechnology Institute (TBI), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Science et Technologie du Lait et de l'Oeuf (STLO), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Unité Matériaux et Transformations - UMR 8207 (UMET), Centrale Lille-Institut de Chimie du CNRS (INC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Fractionnement des AgroRessources et Environnement (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Paris-Saclay Food and Bioproduct Engineering (SayFood), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Mathématiques et Informatique Appliquées (MIA Paris-Saclay)
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Journal of Food Process Engineering
Journal of Food Process Engineering, 2023, ⟨10.1111/jfpe.14325⟩
ISSN: 0145-8876
1745-4530
DOI: 10.1111/jfpe.14325⟩
Popis: International audience; To meet current societal demand for more sustainable transformation processes and bioresources, these processes must be optimized and new ones developed. The evolution of various systems (raw material, food, or process attributes) can be predicted to optimize the uses of biomass for better quality, safety, economic benefit, and sustainability. Predictive modeling can guide the necessary changes and influence industrials, governmental policies and consumers decision-making. However, achieving good predictive capability requires reflection on the models and model validation, which can be difficult. This review aims to help scientists begin to predict by presenting the techniques currently used in predictive science for food and related bioproducts. First, a guideline helps readers initiate a prediction process along with final tips and a warning about the risks involved, with a particular focus on the crucial validation step. Threebroad categories of techniques are then presented: empirical, mechanistic, and artificial intelligence (or “data-driven”). For each category, the advantages and limitations of current techniques for prediction are explained in light of their current domains of applications, illustrated with literature studies and a detailed example. Thus this article provides engineering researchers information about predictive modeling which is a recent relevant development in optimization of both food and nonfood bioresources processes.Practical applications Predictive modeling is a recent development of much relevance in the optimizationof both food and nonfood bioresources processes. The goal of this article is to guide those in research or industry who would like to start predicting. Therefore, the article is intended as a primer on prediction concepts and predictive techniques for food and non-food bioresources processing. Three categories of techniques commonly used in these fields are illustrated by various examples of current applications and amore detailed example helps to understand the implementation process. An increased ability of the global scientific body to predict the outcome of various decisions, often linked or sequential, will open new avenues for designing food products with circularity in mind: maintaining value and not creating waste in the process.
Databáze: OpenAIRE
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