Revolutionizing food processing with infrared heating: New approaches to quality and efficiency
Notice bibliographique
Résumé
Infrared (IR) heating technology represents a cutting-edge thermal technology in food processing, offering energy-efficient and effective solutions for various unit operations such as blanching, microbial decontamination, peeling, roasting, and thawing. Recent advancements in IR heating have highlighted its advantages over conventional methods, including short processing time, uniform heating and product temperature, superior quality of products, low energy consumption, high heat transfer rate, high energy efficiency, ease of control, compact equipment and eco-friendliness over the conventional heating systems. Considering these merits, IR has found several applications in food processing with increased interest and research in the last decade. Thus, this review discusses recent studies and technological advancements in IR heating, addressing the benefits, limitations, and challenges of its implementation across different food processing applications. In addition, it explores the synergistic utilization of IR radiation when combined with other novel technologies by assessing their combined impact on process efficiency, energy savings, and food quality. The findings of this study showed that in blanching, IR heating has shown potential to reduce nutrient loss and preserve sensory quality, enhancing the retention of vitamins and minerals. For microbial decontamination, it provides a non-chemical approach to pathogen reduction, minimizing foodborne risks while preserving product quality. In peeling applications, IR heating can achieve efficient removal of skin with minimal waste and damage to the edible portion, making it an eco-friendly option. When used for roasting, it contributes to the development of desirable colour, flavor, and texture attributes. Finally, in thawing applications, IR technology provides faster and more uniform heating, reducing drip loss and improving product quality. From the foregoing, it was established that the adoption of IR heating technology in food processing represents a significant advancement in enhancing product quality and process efficiency across the various applications. Moreover, combining IR heating with other novel food processing technologies further improved process efficiency, enhanced energy savings, and preserved or even boosted food quality. Further research on optimization, process modelling, and the integration of IR heating with other technologies could expand its applicability and effectiveness, paving the way for more sustainable and high-quality food processing solutions. • IR heating improves processing efficiency and food quality, enhancing consumer appeal • IR integration with other technologies creates synergy for improved overall food processing • Optimizing the heating process and IR equipment in food processing offers numerous benefits • The applicability of IR is anticipated to grow in the coming years due to its merits
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».