Effect of temperature and inoculum concentration on gel microstructure, permeability and syneresis kinetics. Cottage cheese-type gels

Modulating in vitro digestion of whey protein cold-set emulsion gels via gel properties modification with gallic acid and EGCG

Gallic acid (GA) and epigallocatechin gallate (EGCG), cooperated at varied ratios (1:0, 3:1, 1:1, 1:3, and 0:1), were employed to modify gel properties of calcium induced-whey protein emulsion gel. The effects of GA/EGCG on emulsion morphology, as well as gel properties and in vitro digestive behavior of the emulsion gels were investigated. Compared with emulsions without phenolics, GA/EGCG induced slightly smaller particle size and stronger electrostatic repulsion between emulsion droplets. Moreover, GA/EGCG, notably at a ratio of 3:1, promoted electrostatic and hydrophobic interactions between protein molecules and the formation of a compact and filamentous gel microstructure, resulting in a remarkable increment in the gel strength (up to 106 %). Furthermore, in vitro oral digestion, dynamic gastric digestion (using an artificial gastric digestive system, AGDS), and intestinal digestion of the emulsion gels were simulated. Particle size and protein hydrolysis results revealed that GA/EGCG was prone to weaken the physical disintegration of gels, reduce protein hydrolysis, and enhance the stability of emulsified oil droplets during dynamic gastric digestion. As a consequence, delayed release of oil droplets was observed in the gels and more free fatty acids were released in the intestinal digestion, particularly in the gel with GA/EGCG (3:1). These findings would provide novel strategies for application of phenolic compounds in developing protein gel-based delivery systems.

Saccharomyces cerevisiae improves rennet-induced gelation of ultra-high temperature milk

Heating milk at high temperatures impairs its renneting properties, but rennet-induced curds can be formed from ultra-high temperature (UHT) milk inoculated with Saccharomyces cerevisiae. Herein, we measured physicochemical indices of UHT milk inoculated with S. cerevisiae before rennet addition, monitored the kinetics of gel formation, and investigated the physicochemical properties and microstructure of rennet-induced curds to explore the mechanisms by which S. cerevisiae influenced rennet-induced gelation of UHT milk. Compared with untreated pasteurized cow milk and UHT milk, the ethanol content was increased, the pH was decreased, the particle size and ζ-potential were increased, the time points at which the elasticity index began to increase were advanced, and the maximum elasticity index was increased for UHT milk inoculated with S. cerevisiae. The number of S. cerevisiae cells affected the structure of rennet-induced curds; with few cells added, the protein network of curds was continuous and tight, the mean square displacement curves showed an asymptotic behavior, and the water retention capacity and curd yield were high; with more cells added, the loosely entangled proteins aggregated, the continuity of the network was destroyed, and the curd yield decreased. In summary, a low number of S. cerevisiae cells (<1.0 × 10⁷ cfu/mL) can increase particle size, ζ-potential, and ethanol content, and decrease pH of S. cerevisiae-inoculated UHT milk, thereby accelerating the aggregation reactions after enzymatic reaction and improving the renneting properties.

Predictive modeling of the early stages of semi-solid food ripening: Spatio-temporal dynamics in semi-solid casein matrices

A mechanistic, spatio-temporal model to predict early stage semi-solid food ripening, exemplary for semi-solid casein matrices, was created using software based on the finite element method (FEM). The model was refined and validated by experimental data obtained during 8 wk of ripening of a casein matrix that was inoculated by one single central injection of starter culture. The resulting spatio-temporal distributions of lactococci strains, lactose, lactic acid/lactate and pH allowed us to optimize a number of parameters of the predictive model. Using the optimized model, the agreement between simulation and experiment was found to be satisfactory, with the pH matching best. The predictive model unveiled that effective diffusion of substrate and metabolites were crucial for an eventual homogeneous distribution of the measured substances. Hence, while using the optimized parameters from the single injection model, an injection technology for starter culture to inoculate and ferment casein matrices homogeneously was developed by means of solving another optimization problem with respect to injection positions. The casein matrix inoculated by the proposed injection pattern (21 injections, distance = 19 mm) showed sufficient homogeneity (bacterial activity and pH distribution) after the early stages of ripening, demonstrating the potential of application of the injection technology for fermentation of casein-based foods e.g. cheese.

Goat cheese yield and recovery of fat, protein, and total solids in curd are affected by milk coagulation properties

The aims of the present research were to quantify the effects of each coagulation trait, traditional milk coagulation properties [MCP: rennet coagulation time (RCT), curd-firming time (k₂₀), and curd firmness at 30 min (a₃₀)], and modeled curd-firming over time (CF_t) parameters [estimated rennet coagulation time (RCT_eq), curd-firming instant rate constant (k_CF), and potential curd firmness (CF_P)] directly on the following: (1) recovery of 3 milk components in the curd (%REC), (2) 3 measures of cheese yield (%CY), and (3) 3 daily cheese yield traits (dCY) from goat milk. Cheese-making traits were analyzed using 2 mixed different models, the first to test MCP and the second to test CF_t parameters. Pearson correlations were also calculated. Significant and favorable relationships (negative for time intervals and positive for CF measures) were found between the traditional MCP and the CF_t parameters and %REC and %CY traits. The effects of milk fat and protein contents were particularly important on all cheese-making traits, with the only exception being the effect of fat content on water retention in cheese (%CY_WATER). We found an optimum value of milk k₂₀, associated with the highest recovery of components and cheese yield in solids (%CY_SOLIDS). In addition, a lower level of curd water retention and an increased fresh curd yield (%CY_CURD) were associated with greater recovery of fat. The collection of all available information during the process of milk coagulation and curd-firming allowed us to discover the effect of RCT_eq on %REC traits and %CY_SOLIDS, which had not previously been revealed for traditional RCT. Moreover, higher k_CF values were associated with increased %CY_CURD and %CY_SOLIDS. Given that CF_t parameters showed a high level of independence from one another, these can also be easily used and characterized in future applications at the industry level. Information provided by traditional and modeled coagulation properties could efficiently support the goat dairy industry and lay the foundations for a quality payment scheme for goat milk.

Multiple linear regression modeling: Prediction of cheese curd dry matter during curd treatment

Cheese curd dry matter determines functional properties and process parameters during cheese manufacture. Dry matter is affected by many internal (milk composition and pre-treatment) and external (cheese process parameters) factors that are not considered in the most common models. The purpose of this study was to consider a large number of multiple linear regression models that use these internal and external factors as predictor variables, and select the most suitable of these models in order to predict the cheese curd dry matter during curd treatment. Dry matter (DM_exp,nat) was experimentally determined to create a native data set (n = 1013) for fitting the regression model. Dry matter was affected by curd treatment time (CTT), curd treatment temperature (ϑ), pH-value (pH), curd grain size (CGS), fat level (f) and degree of microfiltration (i). A large number of empirical regression models, organized into three different groups, depending on the predictors used, were developed on basis of DM_exp,nat. A Monte Carlo approach was used to select the optimal model, taking into account the value of Akaike's information criterion (AICc) and the coefficient of determination (R²) of each model. The best models were further analyzed to check for potential bias and to verify that the model assumptions were met. We considered one model of group G2 with 11 terms to most closely fit the aforementioned criteria (native data set; R² = 95.55). This model was successfully validated by an independent validation data set (n = 120; R² = 91.95).

High Pressure Homogenization of Porcine Pepsin Protease: Effects on Enzyme Activity, Stability, Milk Coagulation Profile and Gel Development

This study investigated the effect of high pressure homogenization (HPH) (up to 190 MPa) on porcine pepsin (proteolytic and milk-clotting activities), and the consequences of using the processed enzyme in milk coagulation and gel formation (rheological profile, proteolysis, syneresis, and microstructure). Although the proteolytic activity (PA) was not altered immediately after the HPH process, it reduced during enzyme storage, with a 5% decrease after 60 days of storage for samples obtained with the enzyme processed at 50, 100 and 150 MPa. HPH increased the milk-clotting activity (MCA) of the enzyme processed at 150 MPa, being 15% higher than the MCA of non-processed samples after 60 days of storage. The enzyme processed at 150 MPa produced faster aggregation and a more consistent milk gel (G' value 92% higher after 90 minutes) when compared with the non-processed enzyme. In addition, the gels produced with the enzyme processed at 150 MPa showed greater syneresis after 40 minutes of coagulation (forming a more compact protein network) and lower porosity (evidenced by confocal microscopy). These effects on the milk gel can be associated with the increment in MCA and reduction in PA caused by the effects of HPH on pepsin during storage. According to the results, HPH stands out as a process capable of changing the proteolytic characteristics of porcine pepsin, with improvements on the milk coagulation step and gel characteristics. Therefore, the porcine pepsin submitted to HPH process can be a suitable alternative for the production of cheese.

Effect of exopolysaccharides on the proteolytic and angiotensin-I converting enzyme-inhibitory activities and textural and rheological properties of low-fat yogurt during refrigerated storage

The aim of this study was to examine the influence of using exopolysaccharide (EPS) producing strain of Streptococcus thermophilus on the viability of yogurt starters, their proteolytic and angiotensin-I converting enzyme-inhibitory activities, and on the textural and rheological properties of the low-fat yogurt during storage at 4 degrees C for 28 d. The use of an EPS-producing strain of S. thermophilus did not have influence on pH, lactic acid content, or the angiotensin-I converting enzyme-inhibition activity of low-fat yogurt. However, EPS showed a protective effect on the survival of Lactobacillus delbrueckii ssp. bulgaricus. Presence of EPS reduced the firmness, spontaneous whey separation, yield stress, and hysteresis loop area but not the consistency and flow behavior index of low-fat yogurt.

Novel online sensor technology for continuous monitoring of milk coagulation and whey separation in cheesemaking

The cheese industry has continually sought a robust method to monitor milk coagulation. Measurement of whey separation is also critical to control cheese moisture content, which affects quality. The objective of this study was to demonstrate that an online optical sensor detecting light backscatter in a vat could be applied to monitor both coagulation and syneresis during cheesemaking. A prototype sensor having a large field of view (LFV) relative to curd particle size was constructed. Temperature, cutting time, and calcium chloride addition were varied to evaluate the response of the sensor over a wide range of coagulation and syneresis rates. The LFV sensor response was related to casein micelle aggregation and curd firming during coagulation and to changes in curd moisture and whey fat contents during syneresis. The LFV sensor has potential as an online, continuous sensor technology for monitoring both coagulation and syneresis during cheesemaking.

Effect of Cutting Time, Temperature, and Calcium on Curd Moisture, Whey Fat Losses, and Curd Yield by Response Surface Methodology

Response surface methodology was used to study the effect of temperature, cutting time, and calcium chloride addition level on curd moisture content, whey fat losses, and curd yield. Coagulation and syneresis were continuously monitored using 2 optical sensors detecting light backscatter. The effect of the factors on the sensors' response was also examined. Retention of fat during cheese making was found to be a function of cutting time and temperature, whereas curd yield was found to be a function of those 2 factors and the level of calcium chloride addition. The main effect of temperature on curd moisture was to increase the rate at which whey was expelled. Temperature and calcium chloride addition level were also found to affect the light backscatter profile during coagulation whereas the light backscatter profile during syneresis was a function of temperature and cutting time. The results of this study suggest that there is an optimum firmness at which the gel should be cut to achieve maximum retention of fat and an optimum curd moisture content to maximize product yield and quality. It was determined that to maximize curd yield and quality, it is necessary to maximize firmness while avoiding rapid coarsening of the gel network and microsyneresis. These results could contribute to the optimization of the cheese-making process.

Computer Vision and Color Measurement Techniques for Inline Monitoring of Cheese Curd Syneresis

Optical characteristics of stirred curd were simultaneously monitored during syneresis in a 10-L cheese vat using computer vision and colorimetric measurements. Curd syneresis kinetic conditions were varied using 2 levels of milk pH (6.0 and 6.5) and 2 agitation speeds (12.1 and 27.2 rpm). Measured optical parameters were compared with gravimetric measurements of syneresis, taken simultaneously. The results showed that computer vision and colorimeter measurements have potential for monitoring syneresis. The 2 different phases, curd and whey, were distinguished by means of color differences. As syneresis progressed, the backscattered light became increasingly yellow in hue for circa 20 min for the higher stirring speed and circa 30 min for the lower stirring speed. Syneresis-related gravimetric measurements of importance to cheese making (e.g., curd moisture content, total solids in whey, and yield of whey) correlated significantly with computer vision and colorimetric measurements.