Browsing by Author "Perez-Correa J.R."

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    Advances in White Wine Protein Stabilization Technologies
    (NLM (Medline), 2022) Silva-Barbieri D.; Escalona N.; Perez-Correa J.R.; Salazar F.N.; Lopez F.; Brossard N.; Escalona N.
    The unstable proteins in white wine cause haze in bottles of white wine, degrading its quality. Thaumatins and chitinases are grape pathogenesis-related (PR) proteins that remain stable during vinification but can precipitate at high temperatures after bottling. The white wine protein stabilization process can prevent haze by removing these unstable proteins. Traditionally, bentonite is used to remove these proteins; however, it is labor-intensive, generates wine losses, affects wine quality, and harms the environment. More efficient protein stabilization technologies should be based on a better understanding of the main factors and mechanisms underlying protein precipitation. This review focuses on recent developments regarding the instability and removal of white wine proteins, which could be helpful to design more economical and environmentally friendly protein stabilization methods that better preserve the products´ quality.
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    Multicriteria optimal design of emamectin benzoate microparticles obtained by spray drying and ionic gelation
    (Elsevier B.V., 2022) Molina V.; Franco W.; Perez-Correa J.R.; Benavides S.; Troncoso J.M.; Robert P.; Luna R.; von Plessing C.
    © 2022 Elsevier B.V.Emamectin benzoate (EB) is an antiparasitic used to control Caligus rogercresseyi in Chile. However, it has lost efficacy, and the parasite has been exposed to a sublethal dose. Microencapsulation has been suggested as an alternative method to protect and control the release of poorly absorbed drugs to ensure their lethal doses. Accordingly, design of experiments (DOE) and response surface methodology (RSM) were applied to find optimal conditions for EB's ionic gelation (IG) and spray drying (SD) microencapsulation. We used multiobjective (MOO) and multi-response optimization techniques as the desirability function (DFA) to obtain optimal conditions that produce microparticles that satisfy several criteria, such as low gastric digestion (GD) and high yield (Y), encapsulation efficiency (EE), load capacity (LC), and intestinal digestion (ID). The optimization process prioritized the digestion responses and was constrained according to a mass balance. MOO generated theoretical solutions that were better than any of the DOE experimental solutions. Both optimization methods achieved a more balanced performance than the responses obtained in the experimental design. Each optimization method produced better experimental responses than the other in some responses. In SD, DFA yielded higher LC, GD, and ID than MOO by 7.5%, 9.3%, and 2.1%, respectively. In contrast, MOO obtained higher Y and EE than DFA by 6.2% and 10.1%, respectively. In IG, the DFA method yielded a solution with better responses than MOO in LC (3.7%), GD (7.4%), and ID (3.2%), while the MOO solution was better in Y (14.2%) and EE (19.3%). Both multicriteria optimization techniques were suitable for obtaining optimal solutions; however, neither proved superior in all cases.