Development of a membrane filtration process for concentrating a fava bean extract for plant-based dairy applications
Notice bibliographique
Résumé
Introduction:Fava beans are becoming an increasingly popular and viable crop, offering a nutritious option for innovative plant-based food products. Despite their potential, fava beans remain underutilized in the food industry, with their primary use still being as animal feed [1]. However, fava beans are an interesting base material for producing plant-based milk alternatives. While soy milk currently dominates the legume-based beverage market, incorporating fava beans presents an opportunity to diversify and expand this segment, offering enhanced functionality and nutrition compared to soy beans [2, 3]. The limited research on membrane filtration in the plant-based dairy industry highlights the potential for further exploration in this area. Common processing methods for plant-based beverages, such as high-shear mixing and ultra-high temperature treatments, can induce shear and thermal effects that alter protein structures, which affects the stability of protein emulsions [4]. Ultrafiltration, a well-established method in traditional cow dairy processing, also shows great potential for legume-based products. Therefore, this study explores ultrafiltration as a viable solution for plant-based dairy production.Experimental/Methodology:A series of experiments was conducted to evaluate membrane performance. Initially, five commercial ultrafiltration membranes from Alfa Laval, Microdyn Nadir, and Synder, with low molecular weight cut-offs, were screened using an Alfa Laval LabStak M20 unit. The screening was carried out in concentration mode at 50°C, with a transmembrane pressure of 2 bar and a volume flow rate of 4 L/min. Subsequently, the two most promising membranes were further examined through a parameter study and fouling/cleaning assessments using an Alfa Laval LabStak M10 unit. Optimal operating conditions were determined by varying the transmembrane pressure (0.1–2.5 bar) and crossflow velocity (0.1–1.0 m/s) at 50°C. A pilot-scale experiment was then conducted with the most promising membrane candidate in an Alfa Laval M39 Combi unit (3.8” spiral wound), focusing on both parameter and concentration studies. During this stage, transmembrane pressure was varied between 0.5 and 2.5 bar, while flow rates ranged from 0.6 to 1.2 m³/h. Fouling and cleaning capacities were evaluated using pure water flux measurements and an alkaline cleaning agent.Results and Discussion:From the membrane screening, the GR90 (Alfa Laval) and UH005 (Microdyn Nadir) membranes were identified as the most promising candidates, delivering good fluxes (14.8 and 12.8 L/m²/h, respectively) alongside high protein retention rates (79% and 80% total nitrogen retention, respectively). The parameter study revealed that a crossflow velocity of 1 m/s and a transmembrane pressure of around 1 bar were optimal operational settings. Upon scaling up the process using a 3.8” spiral wound module with the GR90 membrane, a crossflow of 1.2 m³/h and 0.7 bar was applied to concentrate the fava bean base, achieving a volumetric concentration factor of 3.0. Despite significant fouling on the membrane surfaces, the pure water flux was restored using an alkaline cleaning agent. The flux during the concentration ranged from 1 to 6 L/m²/h. Overall, the study demonstrated that ultrafiltration is a promising unit operation for future plant-based dairy production.Acknowledgments:The authors gratefully acknowledge Green Dairy AB, Sweden, for their collaboration and for supplying the fava bean base.References:[1] Crépon, K.; Marget, P.; Peyronnet, C.; Carrouée, B.; Arese, P.; Duc, G. Field Crops Research, 2010, 115 (3), 329-339.[2] Nawaz, M. A.; Singh, T. K.; Stockmann, R.; Jegasothy, H.; Buckow, R. Foods, 2021, 10 (6).[3] Nawaz, M. A.; Tan, M.; Øiseth, S.; Buckow, R. Food Reviews International, 2022, 38 (5), 1064-1102.[4] Qamar, S.; Bhandari, B.; Prakash, S. Food Research International, 2019, 116, 1374-1385.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».