Two phases are generally recognized in the enzymatic coagulation of milk: hydrolysis and aggregation, although nowadays more and more researchers consider the non-enzymatic phase to actually be a stage of gel formation made up of two sub-stages: micellar aggregation and hardening of the three-dimensional network of para-κ-casein. To evaluate this controversy, the main descriptive models have been reviewed. Most of them can only model micellar aggregation, without modeling the hardening stage. Some are not generalizable enough. However, more recent models have been proposed, applicable to a wide range of conditions, which could differentiate both substages. Manufacturing quality enzymatic cheeses in a cost-effective and consistent manner requires effective control of coagulation, which implies studying the non-enzymatic sub-stages of coagulation separately, as numerous studies require specific measurement methods for each of them. Some authors have recently reviewed the micellar aggregation models, but without differentiating it from hardening. Therefore, a review of the proposed models is necessary, as coagulation cannot be controlled without knowing its mechanisms and the stages that constitute it.

Optimización de las condiciones de extracción de pectina a partir de cáscara de limón francés (Citrus medica) utilizando la metodología de superficie de respuesta

Most researchers who have studied enzymatic milk coagulation in depth recognize that this process is composed of two overlapping phases: an enzymatic phase (first) and a non-enzymatic phase (second). The latter is composed of two consecutive sub-phases that are also partially overlapping: the first is called micellar aggregation, and the second is called the gel hardening phase by many researchers. This final phase, which consists of the rearrangement of the three-dimensional para-κ-casein network, is one of the most complex and least studied milk coagulation stages. A review conducted prior to this publication confirmed that existing models describe micellar aggregation up to network formation but cannot characterize the subsequent network rearrangement and gel hardening process. The objective of this review is to examine the main models that describe the gel hardening phase, evaluating each one to highlight its advantages, disadvantages, and main limitations. Among the models reviewed, those based on light scattering stand out, as they are non-invasive and allow for the prediction of gel firmness in real time. This review is expected to provide greater support to the cheese industry in achieving better control of enzymatic milk coagulation.

Este estudio analizó el efecto de las diferentes proporciones de frutos enteros de aguaymanto (Physalis peruviana), uva (Vitis vinífera) negra y fresa (Fragaria ananassa) en la aceptabilidad sensorial (aroma, color, sabor y aceptabilidad general) de un macerado en pisco. Se utilizó un diseño de mezclas con centroide ampliado para determinar las proporciones de frutas (aguaymanto, uva negra y fresa), las cuales fueron mezcladas con pisco, diluido a 25 °GL y estandarizado a 20 °Brix. La evaluación sensorial se realizó con jueces no entrenados y empleando una escala hedónica estructurada (10 puntos). El modelo lineal se ajustó mejor a los datos experimentales (p < 0.05) y todos los macerados fueron aceptables (calificación mayor a 5 puntos). Los macerados de pisco más aceptados en aroma, color, sabor y aceptación general fueron los que tuvieron mayor proporción de uva.