C. Cipolat-Gotet

Comparison between mechanical and near-infrared methods for assessing coagulation properties of bovine milk

The aim of the present study was to compare milk coagulation properties measured through a traditional mechanical device, the Formagraph (FRM; Foss Electric A/S, Hillerød, Denmark), and a near-infrared optical device, the Optigraph (OPT; Ysebaert SA, Frépillon, France). Individual milk samples of 913 Brown Swiss cows from 63 herds located in Trento Province (Italy) were analyzed for rennet coagulation time (RCT, min), curd-firming time (k(20), min), and 2 measures of curd firmness (a(30) and a(45),mm) using the 2 instruments and under identical conditions. The trial was performed in the same laboratory, by the same technician, and following the same procedures. Extending the analysis by either instrument to 90 min permitted RCT and k(20) values to be obtained even for late-coagulating milk samples. Milk coagulation properties measured using the OPT differed considerably from those obtained using the FRM. The average k(20) values varied greatly (8.16 vs. 5.36 min for the OPT and the FRM, respectively), as did the a(45) figures (41.49 vs. 33.66 mm for the OPT and the FRM, respectively). The proportion of noncoagulating samples for which k(20) could be estimated differed between instruments, being less for the OPT. The between-instrument correlation coefficients were either moderate (0.48 for a(30)) or low (0.24 and 0.17 for k(20) and a(45), respectively) when the same traits were compared. The correlations between k(20) and a(45), and milk yield varied among instruments, as did the correlations between k(20), a(30), and a(45) and milk composition, and the correlations between a(45) and pH. The relative influence of days in milk on k(20) and a(45) varied, as did the effect of parity on a(45) and that of the measuring unit of coagulation meter on k(20) and a(30). The RCT estimated by the OPT was the only milk coagulation property to show good agreement with the FRM-derived value, although this was not true for the data from late-coagulating samples.

Factors affecting variation of different measures of cheese yield and milk nutrient recovery from an individual model cheese-manufacturing process

Cheese yield (CY) is the most important technological trait of milk, because cheese-making uses a very high proportion of the milk produced worldwide. Few studies have been carried out at the level of individual milk-producing animals due to a scarcity of appropriate procedures for model-cheese production, the complexity of cheese-making, and the frequent use of the fat and protein (or casein) contents of milk as a proxy for cheese yield. Here, we report a high-throughput cheese manufacturing process that mimics all phases of cheese-making, uses 1.5-L samples of milk from individual animals, and allows the simultaneous processing of 15 samples per run. Milk samples were heated (35°C for 40 min), inoculated with starter culture (90 min), mixed with rennet (51.2 international milk-clotting units/L of milk), and recorded for gelation time. Curds were cut twice (10 and 15 min after gelation), separated from the whey, drained (for 30 min), pressed (3 times, 20 min each, with the wheel turned each time), salted in brine (for 60 min), weighed, and sampled. Whey was collected, weighed, and sampled. Milk, curd, and whey samples were analyzed for pH, total solids, fat content, and protein content, and energy content was estimated. Three measures of percentage cheese yield (%CY) were calculated: %CY(CURD), %CY(SOLIDS), and %CY(WATER), representing the ratios between the weight of fresh curd, the total solids of the curd, and the water content of the curd, respectively, and the weight of the milk processed. In addition, 3 measures of daily cheese yield (dCY, kg/d) were defined, considering the daily milk yield. Three measures of nutrient recovery (REC) were computed: REC(FAT), REC(PROTEIN), and REC(SOLIDS), which represented the ratio between the weights of the fat, protein, and total solids in the curd, respectively, and the corresponding components in the milk. Energy recovery, REC(ENERGY), represented the energy content of the cheese compared with that in the milk. This procedure was used to process individual milk samples obtained from 1,167 Brown Swiss cows reared in 85 herds of the province of Trento (Italy). The assessed traits exhibited almost normal distributions, with the exception of REC(FAT). The average values (± SD) were as follows: %CY(CURD)=14.97±1.86, %CY(SOLIDS)=7.18±0.92, %CY(WATER)=7.77±1.27, dCY(CURD)=3.63±1.17, dCY(SOLIDS)=1.74±0.57, dCY(WATER)=1.88±0.63, REC(FAT)=89.79±3.55, REC(PROTEIN)=78.08±2.43, REC(SOLIDS)=51.88±3.52, and REC(ENERGY)=67.19±3.29. All traits were highly influenced by herd-test-date and days in milk of the cow, moderately influenced by parity, and weakly influenced by the utilized vat. Both %CY(CURD) and dCY(CURD) depended not only on the fat and protein (casein) contents of the milk, but also on their proportions retained in the curd; the water trapped in curd presented an higher variability than that of %CY(SOLIDS). All REC traits were variable and affected by days in milk and parity of the cows. The described model cheese-making procedure and the results obtained provided new insight into the phenotypic variation of cheese yield and recovery traits at the individual level.

Genetic parameters of different measures of cheese yield and milk nutrient recovery from an individual model cheese-manufacturing process

Cheese yield (CY) is an important technological trait in the dairy industry, and the objective of this study was to estimate the genetic parameters of cheese yield in a dairy cattle population using an individual model-cheese production procedure. A total of 1,167 Brown Swiss cows belonging to 85 herds were sampled once (a maximum of 15 cows were sampled per herd on a single test day, 1 or 2 herds per week). From each cow, 1,500 mL of milk was processed according to the following steps: milk sampling and heating, culture addition, rennet addition, gelation-time recording, curd cutting, whey draining and sampling, wheel formation, pressing, salting in brine, weighing, and cheese sampling. The compositions of individual milk, whey, and curd samples were determined. Three measures of percentage cheese yield (%CY) were calculated: %CY(CURD), %CY(SOLIDS), and %CY(WATER), which represented the ratios between the weight of fresh curd, the total solids of the curd, and the water content of the curd, respectively, and the weight of the milk processed. In addition, 3 measures of daily cheese yield (dCY, kg/d) were defined, considering the daily milk yield. Three measures of nutrient recovery (REC) were computed: REC(FAT), REC(PROTEIN), and REC(SOLIDS), which represented the ratio between the weights of the fat, protein, and total solids in the curd, respectively, and the corresponding nutrient in the milk. Energy recovery, REC(ENERGY), represented the energy content of the cheese versus that in the milk. For statistical analysis, a Bayesian animal model was implemented via Gibbs sampling. The effects of parity (1 to ≥4), days in milk (6 classes), and laboratory vat (15 vats) were assigned flat priors; those of herd-test-date, animal, and residual were given Gaussian prior distributions. Intra-herd heritability estimates of %CY(CURD), %CY(SOLIDS), and %CY(WATER) ranged from 0.224 to 0.267; these were larger than the estimates obtained for milk yield (0.182) and milk fat content (0.122), and similar to that for protein content (0.275). Daily cheese yields showed heritability estimates similar to those of daily milk yield. The trait %CY(WATER) showed a highly positive genetic correlation with %CY(SOLIDS) (0.87), whereas their phenotypic correlation was moderate (0.37), and the fat and protein contents of milk showed high genetic correlations with %CY traits. The heritability estimates of REC(PROTEIN) and REC(FAT) were larger (0.490 and 0.208, respectively) than those obtained for the protein and fat contents of milk, and the genetic relationships between REC(PROTEIN) and REC(FAT) with milk protein and fat content were low or moderate; REC(PROTEIN) and REC(FAT) were moderately correlated with the %CY traits and highly correlated with REC(SOLIDS) and REC(ENERGY). Both REC(SOLIDS) and REC(ENERGY) were heritable (0.274 and 0.232), and showed high correlations with each other (0.96) and with the %CY traits (0.83 to 0.97). Together, these findings demonstrate the existence of economically important, genetically determined variability in cheese yield that does not depend solely upon the fat and protein contents of milk, but also relies on the ability of the coagulum to retain the highest possible proportions of the available protein, fat, and water. Exploitation of this interesting genetic variation does not seem to be feasible through direct measurement of the phenotype in cows at the population level. Instead, further research is warranted to examine possible means for indirect prediction, such as through assessing the mid-infrared spectra of milk samples.

Genetic analysis of rennet coagulation time, curd-firming rate, and curd firmness assessed over an extended testing period using mechanical and near-infrared instruments

The aims of this study were (1) to analyze rennet coagulation time (RCT), curd-firming rate, and curd firmness obtained by extending the standard 30-min testing time to 45 min; (2) to estimate heritabilities of the aforementioned traits determined by mechanical (Formagraph; Foss Electric, Hillerød, Denmark) and near-infrared optical (Optigraph; Ysebaert, Frépillon, France) instruments, and to assess the statistical relevance of their genetic background by using the Bayes factor procedure, the deviance information criterion, and the mean squared error; (3) to estimate phenotypic and genetic relationships between instruments within trait and between traits within instrument; and (4) to obtain correlations for sire rankings based on the used instruments. Individual milk samples were collected from 913 Brown Swiss cows reared in 63 herds located in Trento Province (Italy). Milk coagulation properties (MCP) were measured using 2 different instruments: Formagraph and Optigraph. Both instruments were housed in the same laboratory and operated by the same technician. Each sample was analyzed simultaneously on each instrument. All experimental conditions (milk temperature and the concentration and type of rennet) were identical. For the analysis, univariate and bivariate animal models were implemented using Bayesian methods. Univariate analyses were conducted to test the hypothesis that the traits showed additive genetic determination. Deviance information criterion, Bayes factor, and mean squared error were used as model choice criteria. The main results were that (1) RCT could be measured on all samples by extending the observation time to 45 min, and its genetic parameters (h(2)=0.23) and breeding values could be estimated while avoiding the bias of noncoagulating samples; (2) curd-firming rate could be measured on almost all milk samples, and its genetic parameters could be estimated for the first time on a field data set (h(2)=0.21); (3) for the first time, genetic parameters of curd firmness 45 min after rennet addition (h(2)=0.12) were estimated, and they were compared with curd firmness 30 min after rennet addition (h(2)=0.17); and (4) MCP estimated using the Optigraph appeared to be genetically different from those determined by Formagraph, with the partial exception of RCT (genetic correlation=0.97). Breeding strategies for the improvement of MCP must be planned with caution. Currently, the high throughput, ease of use, and reduced costs of analysis make predictions obtained from mid-infrared spectroscopy (MIRS) on untreated milk samples a promising alternative to produce relevant data at the population level. The use of mechanical lactodynamographs to establish reference data for MIRS calibrations have been already studied, whereas the use of near-infrared optical lactodynamographs as a reference method for MIRS calibrations needs to be investigated.

Effect of dairy farming system, herd, season, parity, and days in milk on modeling of the coagulation, curd firming, and syneresis of bovine milk

The objectives of this study were to characterize the variation in curd firmness model parameters obtained from coagulating bovine milk samples, and to investigate the effects of the dairy system, season, individual farm, and factors related to individual cows (days in milk and parity). Individual milk samples (n = 1,264) were collected during the evening milking of 85 farms representing different environments and farming systems in the northeastern Italian Alps. The dairy herds were classified into 4 farming system categories: traditional system with tied animals (29 herds), modern dairy systems with traditional feeding based on hay and compound feed (30 herds), modern dairy system with total mixed ration (TMR) that included silage as a large proportion of the diet (9 herds), and modern dairy system with silage-free TMR (17 herds). Milk samples were analyzed for milk composition and coagulation properties, and parameters were modeled using curd firmness measures (CFt) collected every 15 s from a lacto-dynamographic analysis of 90 min. When compared with traditional milk coagulation properties (MCP), the curd firming measures showed greater variability and yielded a more accurate description of the milk coagulation process: the model converged for 93.1% of the milk samples, allowing estimation of 4 CFt parameters and 2 derived traits [maximum CF (CF(max)) and time from rennet addition to CF(max) (t(max))] for each sample. The milk samples whose CFt equations did not converge showed longer rennet coagulation times obtained from the model (RCT(eq)) and higher somatic cell score, and came from less-productive cows. Among the sources of variation tested for the CFt parameters, dairy herd system yielded the greatest differences for the contrast between the traditional farm and the 3 modern farms, with the latter showing earlier coagulation and greater instant syneresis rate constant (k(SR)). The use of TMR yielded a greater tmax because of a higher instant curd-firming rate constant (k(CF)). Season of sampling was found to be very important, yielding higher values during winter for all traits except k(CF) and k(SR). All CFt traits were affected by individual cow factors. For parity, milk produced by first-lactation cows showed higher k(CF) and k(SR), but delays in achieving CF(max). With respect to stage of lactation, RCT(eq) and potential asymptotic CF increased during the middle of lactation and stabilized thereafter, whereas the 2 instant rate constants presented the opposite pattern, with the lowest (k(CF)) and highest (k(SR)) values occurring in mid lactation. The new challenge offered by prolonging the test interval and individual modeling of milk technological properties allowed us to study the effects of parameters related to the environment and to individual cows. This novel strategy may be useful for investigating the genetic variability of these new coagulation traits.

Breed of cow and herd productivity affect milk composition and modeling of coagulation, curd firming, and syneresis

Milk coagulation properties (MCP) have been widely investigated in the past using milk collected from different cattle breeds and herds. However, to our knowledge, no previous studies have assessed MCP in individual milk samples from several multi-breed herds characterized by either high or low milk productivity, thereby allowing the effects of herd and cow breed to be evaluated independently. Multi-breed herds (n=41) were classified into 2 categories based on milk productivity (high vs. low), defined according to the average milk net energy yielded daily by lactating cows. Milk samples were taken from 1,508 cows of 6 different breeds: 3 specialized dairy (Holstein-Friesian, Brown Swiss, Jersey) and 3 dual-purpose (Simmental, Rendena, Alpine Grey) breeds, and analyzed in duplicate (3,016 tests) using 2 lactodynamographs to obtain 240 curd firming (CF) measurements over 60min (1 every 15 s) for each duplicate. The 5 traditional single-point MCP (RCT, k20, a30, a45, and a60) were yielded directly by the instrument from the available CF measures. All 240 CF measures of each replicate were also used to estimate 4 individual equation parameters: RCT estimated according to curd firm change over time modeling (RCTeq), asymptotic potential curd firmness (CFP), curd firming instant rate constant (kCF), and syneresis instant rate constant (kSR) and 2 derived traits: maximum curd firmness achieved within 45min (CFmax) and time at achievement of CFmax (tmax) by curvilinear regression using a nonlinear procedure. Results showed that the effect of herd-date on traditional and modeled MCP was modest, ranging from 6.1% of total variance for k20 to 10.7% for RCT, whereas individual animal variance was the highest, ranging from 32.0% for tmax to 82.5% for RCTeq. The repeatability of MCP was high (>80%) for all traits except those associated with the last part of the lactodynamographic curve (i.e., a60, kSR, kCF, and tmax: 57 to 71%). Reproducibility, taking into account the effect of instrument, was equal to or slightly lower than repeatability. Milk samples collected in farms characterized by high productivity exhibited delayed coagulation (RCTeq: 18.6 vs. 16.3min) but greater potential curd firmness (CFP: 76.8 vs. 71.9mm) compared with milk samples collected from low-productivity herds. Parity and days in milk influenced almost all MCP. Large differences in all MCP traits were observed among breeds, both between specialized and dual-purpose breeds and within these 2 groups of breeds, even after adjusting for milk quality and yield. Milk quality and MCP of samples from Jersey cows, and coagulation time of samples from Rendena cows were better than in milk from Holstein-Friesian cows, and intermediate results were found with the other breeds of Alpine origin. The results of this study, taking into account the intrinsic limitation of this technique, show that the effects of breed on traditional and modeled MCP are much greater than the effects of herd productivity class, parity, and DIM. Moreover, the variance in individual animals is much greater than the variance in individual herds within herd productivity class. It seems that improvement in MCP depends more on genetics (e.g., breed, selection) than on environmental and management factors.

Genetic parameters of cheese yield and curd nutrient recovery or whey loss traits predicted using Fourier-transform infrared spectroscopy of samples collected during milk recording on Holstein, Brown Swiss, and Simmental dairy cows.

Cheese yield is the most important technological parameter in the dairy industry in many countries. The aim of this study was to infer (co)variance components for cheese yields (CY) and nutrient recoveries in curd (REC) predicted using Fourier-transform infrared (FTIR) spectroscopy of samples collected during milk recording on Holstein, Brown Swiss, and Simmental dairy cows. A total of 311,354 FTIR spectra representing the test-day records of 29,208 dairy cows (Holstein, Brown Swiss, and Simmental) from 654 herds, collected over a 3-yr period, were available for the study. The traits of interest for each cow consisted of 3 cheese yield traits (%CY: fresh curd, curd total solids, and curd water as a percent of the weight of the processed milk), 4 curd nutrient recovery traits (REC: fat, protein, total solids, and the energy of the curd as a percent of the same nutrient in the processed milk), and 3 daily cheese production traits (daily fresh curd, total solids, and the water of the curd per cow). Calibration equations (freely available upon request to the corresponding author) were used to predict individual test-day observations for these traits. The (co)variance components were estimated for the CY, REC, milk production, and milk composition traits via a set of 4-trait analyses within each breed. All analyses were performed using REML and linear animal models. The heritabilities of the %CY were always higher for Holstein and Brown Swiss cows (0.22 to 0.33) compared with Simmental cows (0.14 to 0.18). In general, the fresh cheese yield (%CYCURD) showed genetic variation and heritability estimates that were slightly higher than those of its components, %CYSOLIDS and %CYWATER. The parameter RECPROTEIN was the most heritable trait in all the 3 breeds, with values ranging from 0.32 to 0.41. Our estimation of the genetic relationships of the CY and REC with milk production and composition revealed that the current selection strategies used in dairy cattle are expected to exert only limited effects on the REC traits. Instead, breeders may be able to exploit genetic variations in the %CY, particularly RECFAT and RECPROTEIN. This last component is not explained by the milk protein content, suggesting that its direct selection could be beneficial for cheese production aptitude. Collectively, our findings indicate that breeding strategies aimed at enhancing CY and REC could be easily and rapidly implemented for dairy cattle populations in which FTIR spectra are routinely acquired from individual milk samples.

Phenotypic factors affecting coagulation properties of milk from Sarda ewes.

In this study, milk-coagulation properties (MCP) were characterized in the Sarda sheep breed. Milk composition and MCP [rennet-coagulation time (RCT), curd-firming time [time to reach a curd firmness of 20mm (k20)], and curd firmness (a30), (a45), and (a60)] were obtained extending the lactodynamographic analysis from 30 to 60 min from a population of 1,121 ewes from 23 different farms. Managerial characteristics of farms and parity, individual daily milk yields and stage of lactation of ewes were recorded. Data were analyzed using a mixed-model procedure with fixed effects of days in milk, parity, daily milk yield, and flock size and the random effect of the flock/test day nested within flock size. Sampled farms were classified as small (<300 ewes) and medium (300 to 600 ewes), and these were kept by family operations, or as large (>600 ewes), often operated through hired workers. Daily milk yield was, on average, 1.58 ± 0.79 L/d and variability for this trait was very high. The average content of fat, protein, and casein was respectively 6.41, 5.39, and 4.20%. The class of flock size had a significant effect only on curd firmness, whereas days in milk affected RCT and k20. The flock test day, parity, and daily milk yield were important sources of variation for all MCP. The mean value of RCT (8.6 min) and the low occurrence of noncoagulating samples (0.44%) confirmed the excellent coagulation ability of sheep milk compared with cattle milk. A more rapid coagulation was observed in mid-lactating, primiparous, and high-yielding ewes. The k20 was usually reached in less than 2 min after gelation, with the most favorable values at mid lactation. The mean value of curd firmness 30 min after rennet addition (a30) was, on average, 50mm and decreased to 46 and 42 mm respectively after 45 (a45) and 60 min (a60). The decreasing value of curd-firmness traits was likely to be caused by curd syneresis and whey expulsion. The correlation between RCT and a30 was much lower than in dairy cows and about null for a45 and a60. This means that curd firmness in dairy ewes is almost independent of gelation time and this can provide specific information for this species. In conclusion, this study showed that milk from Sarda sheep is characterized by an earlier gelation, a faster increase in curd firmness with time, and greater curd firmness after 30 min compared with dairy cows. Furthermore, correlations between MCP in sheep are much lower than in bovines and some of the assumptions and interpretations related to cows cannot be applied to sheep.

Quality traits and modeling of coagulation, curd firming, and syneresis of sheep milk of Alpine breeds fed diets supplemented with rumen-protected conjugated fatty acid

The aim of this study was to test the modeling of curd-firming (CF) measures and to compare the sheep milk of 3 Alpine breeds supplemented with or without rumen-protected conjugated linoleic acid (rpCLA). Twenty-four ewes of the Brogna, Foza, and Lamon breeds were allotted to 6 pens (2 pens/breed) and fed a diet composed of corn grain, corn silage, dried sugar beet pulp, soybean meal, wheat bran, wheat straw, and a vitamin-mineral mixture. The rpCLA supplement (12 g/d per ewe plus 4 g/d for each lamb older than 30 d) was mixed into the diet of 1 pen per sheep breed (3 pens/treatment) to provide an average of 0.945 and 0.915 g/d per ewe of the cis-9,trans-11 C18:2 and trans-10,cis-12 C18:2 conjugated linoleic acid isomers, respectively. The trial started at 38 ± 23 d after parturition, and individual morning milk samples were collected on d 16, 23, 37, 44, and 59 of the trial. Milk samples were analyzed for composition, and duplicate samples were assessed for milk coagulation properties (MCP). A total of 180 CF measures for each sample (1 every 15s) were recorded. Model parameters were the rennet coagulation time, the asymptotic potential CF, the CF instant rate constant, the syneresis instant rate constant, the maximum CF achieved within 45 min (CFmax), and the time at achievement of CFmax. The data were analyzed using a hierarchical model that considered the fixed effects of breed, diet, lamb birth, and initial days in milk, which were tested on individual ewe (random) variance; the fixed effect of sampling day, which was tested on the within-ewe sample (random) variance; and the fixed effect of instrument or cuvette position (only for MCP), which was tested on the residual (replicates within samples) variance. The local Alpine sheep breeds displayed similar milk compositions, traditional MCP, and CF modeling parameters. Supplementation with rpCLA triggered changes in milk composition and worsened MCP (e.g., delayed rennet coagulation time, slower CF instant rate constant, and a doubling of syneresis instant rate constant), but did not influence potential CF. Overall, our results indicate that rpCLA supplementation reduced the actual maximum CF (CFmax) but did not modify the interval between rennet addition and CFmax or time to CFmax.

Modeling of coagulation, curd firming, and syneresis of milk from Sarda ewes

This study investigated the modeling of curd-firming (CF) over time (CF(t)) of sheep milk. Milk samples from 1,121 Sarda ewes from 23 flocks were analyzed for coagulation properties. Lactodynamographic analyses were conducted for up to 60 min, and 240 CF individual observations from each sample were recorded. Individual sample CFt equation parameters (RCT(eq), rennet coagulation time; CF(P), asymptotic potential value of curd firmness; k(CF), curd-firming instant rate constant; and k(SR), curd syneresis instant rate constant) were estimated, and the derived traits (CF(max), the point at which CF(t) attained its maximum level, and tmax, the time at which CF(max) was attained) were calculated. The incidence of noncoagulating milk samples was 0.4%. The iterative estimation procedure applied to the individual coagulation data showed a small number of not-converged samples (4.4%), which had late coagulation and an almost linear pattern of the ascending part of the CF(t) curve that caused a high value of CF(P), a low value of k(CF), and a high value of k(SR). Converged samples were classified on the basis of their CF(t) curves into no-k(SR) (18.0%), low-k(SR) (72.6%), and high-k(SR) (4.5%). A CF(t) that was growing continuously because of the lack of the syneresis process characterized the no-k(SR) samples. The high-k(SR) samples had a much larger CFP, a smaller k(CF), and an anticipation of tmax, whereas the low-k(SR) samples had a fast k(CF) and a slower k(SR). The part of the average CF(t) curves that showed an increase was similar among the 3 different syneretic groups, whereas the part that decreased was different because of the expulsion of whey from the curd. The traditional milk coagulation properties recorded within 30 min were not able to detect any appreciable differences among the 4 groups of coagulating samples, which could lead to a large underestimation of the maximum CF of all samples (if predicted by a30), with the exception of the no-k(SR) samples. Large individual variability was found and was likely caused by the effects of the dairy system, such as flock size (on CF(max), t(max), and % ewes with no-k(SR) milk), flock within flock size (representing 11 to 43% of total variance for % ewes with no-k(SR) milk and CF(max), respectively), days in milk (on all model parameters and CF(max)), parity (on RCT(eq), k(SR), and CF(max)), daily milk yield (on RCT(eq) and CF(max)), and position of the individual pendulum that significantly affected model parameters and derived traits. In conclusion, the results showed that the modeling of coagulation, curd-firming, and syneresis is a suitable tool to achieve a deeper interpretation of the coagulation and curd-firming processes of sheep milk and also to study curd syneresis.