An Evaluation of the Clotting Properties of Three Plant Rennets in the Milks of Different Animal Species

Cynara cardunculus, Carica papaya and Ficus carica extracts are proposed as milk coagulants herein. Their coagulation efficiency was measured in bovine, buffalo, goat and sheep milk incubated at different temperatures. The milk-clotting and proteolytic activities as well as the lactodynamographic parameters were determined considering animal rennet as a reference coagulant. The vegetable coagulant, extracted from C. cardunculus pistils, proved to be the most suitable milk-clotting enzyme for cheesemaking, since it possesses similar milk clotting properties to conventional calf rennet. F. carica latex, but seemed to be a promising alternative coagulant at higher temperatures. The strong proteolytic activity of papain caused poor milk coagulation in all milk samples. To conclude, this result also supports the original hypothesis of this study that the excessive proteolytic nature of plant coagulants can negatively affect the cheesemaking process. The optimization of using a plant rennet in a dairy application can be done by selecting the appropriate plant rennet with a consistent clotting efficiency. These innovative manufacturing processes may also lead to the optimization and production of new cheese varieties.

Control and Monitoring of Milk Renneting Using FT-NIR Spectroscopy as a Process Analytical Technology Tool

Failures in milk coagulation during cheese manufacturing can lead to decreased yield, anomalous behaviour of cheese during storage, significant impact on cheese quality and process wastes. This study proposes a Process Analytical Technology approach based on FT-NIR spectroscopy for milk renneting control during cheese manufacturing. Multivariate Curve Resolution optimized by Alternating Least Squares (MCR-ALS) was used for data analysis and development of Multivariate Statistical Process Control (MSPC) charts. Fifteen renneting batches were set up varying temperature (30, 35, 40 °C), milk pH (6.3, 6.5, 6.7), and fat content (0.1, 2.55, 5 g/100 mL). Three failure batches were also considered. The MCR-ALS models well described the coagulation processes (explained variance ≥99.93%; lack of fit <0.63%; standard deviation of the residuals <0.0067). The three identified MCR-ALS profiles described the main renneting phases. Different shapes and timing of concentration profiles were related to changes in temperature, milk pH, and fat content. The innovative implementation of MSPC charts based on T² and Q statistics allowed the detection of coagulation failures from the initial phases of the process.

Coagulation Traits of Sheep and Goat Milk

Milk production from sheep and goat species is continuously growing worldwide, and its main use is for cheesemaking. Given that the final quality of cheese is linked to the traits of raw milk cheese yield at dairy plants, it is often calculated by using predictive formulas based on fat and protein content. Predictive formulas have been studied for bovine milk and are very effective but not appropriate for sheep and goat milk. Several methods, which simulate the actual coagulation processes, are available at the laboratories. This article reviews the available literature about rennet coagulation and cheese yield traits from sheep and goat milk and the methods used at the laboratory level. In general, if compared to cow milk, sheep and goat milk are characterized by shorter rennet coagulation times and a very limited amount of non-coagulating samples. Curd firmness of sheep milk is almost independent from the rennet coagulation time, and some coagulation traits can be predicted by infrared spectra. In addition, coagulation traits are characterized by appropriate values of heritability to be considered in selective breeding plans. With regard to goat milk, rennet coagulation time and cheese yield are strongly influenced by the breed effect.

Optical monitoring of chemical processes in turbid biogenic liquid dispersions by Photon Density Wave spectroscopy

In turbid biogenic liquid material, like blood or milk, quantitative optical analysis is often strongly hindered by multiple light scattering resulting from cells, particles, or droplets. Here, optical attenuation is caused by losses due to absorption as well as scattering of light. Fiber-based Photon Density Wave (PDW) spectroscopy is a very promising method for the precise measurement of the optical properties of such materials. They are expressed as absorption and reduced scattering coefficients (μ a and μ s', respectively) and are linked to the chemical composition and physical properties of the sample. As a process analytical technology, PDW spectroscopy can sense chemical and/or physical processes within such turbid biogenic liquids, providing new scientific insight and process understanding. Here, for the first time, several bioprocesses are analyzed by PDW spectroscopy and the resulting optical coefficients are discussed with respect to established mechanistic models of the chosen processes. As model systems, enzymatic casein coagulation in milk, temperature-induced starch hydrolysis in beer mash, and oxy- as well as deoxygenation of human donor blood were investigated by PDW spectroscopy. The findings indicate that also for very complex biomaterials (i.e., not well-defined model materials like monodisperse polymer dispersions), obtained optical coefficients allow for the assessment of a structure/process relationship and thus for a new analytical access to biogenic liquid material. This is of special relevance as PDW spectroscopy data are obtained without any dilution or calibration, as often found in conventional spectroscopic approaches.

Effect of microparticulated whey proteins on milk coagulation properties

The enhancement of milk coagulation properties (MCP) and the reuse of whey produced by the dairy industry are of great interest to improve the efficiency of the cheese-making process. Native whey proteins (WP) can be aggregated and denatured to obtain colloidal microparticulated WP (MWP). The objective of this study was to assess the effect of MWP on MCP; namely, rennet coagulation time (RCT), curd-firming time, and curd firmness 30 min after rennet addition. Six concentrations of MWP (vol/vol; 1.5, 3.0, 4.5, 6.0, 7.5, and 9.0%) were added to 3 bulk milk samples (collected and analyzed during 3 d), and a sample without MWP was used as control. Within each day of analysis, 6 replicates of MCP for each treatment were obtained, changing the position of the treatment in the rack. For control samples, 2 replicates per day were performed. In addition to MCP, WP fractions were measured on each treatment during the 3 d of analysis. Milk coagulation properties were measured on 144 samples by using a Formagraph (Foss Electric, Hillerød, Denmark). Increasing the amount of MWP added to milk led to a longer RCT. In particular, significant differences were found between RCT of the control samples (13.5 min) and RCT of samples with 3.0% (14.6 min) or more MWP. A similar trend was observed for curd-firming time, which was shortest in the control samples and longest in samples with 9.0% MWP (21.4 min). No significant differences were detected for curd firmness at 30 min across concentrations of MWP. Adjustments in cheese processing should be made when recycling MWP, in particular during the coagulation process, by prolonging the time of rennet activity before cutting the curd.

Short communication: Factors affecting coagulation properties of Mediterranean buffalo milk

The aim of this study was to investigate sources of variation of milk coagulation properties (MCP) of buffalo cows. Individual milk samples were collected from 200 animals in 5 herds located in northern Italy from January to March 2010. Rennet coagulation time (RCT, min) and curd firmness after 30 min from rennet addition (a(30), mm) were measured using the Formagraph instrument (Foss Electric, Hillerød, Denmark). In addition to MCP, information on milk yield, fat, protein, and casein contents, pH, and somatic cell count (SCC) was available. Sources of variation of RCT and a(30) were investigated using a linear model that included fixed effects of herd, days in milk (DIM), parity, fat content, casein content (only for a(30)), and pH. The coefficient of determination was 51% for RCT and 48% for a(30). The most important sources of variation of MCP were the herd and pH effects, followed by DIM and fat content for RCT, and casein content for a(30). The relevance of acidity in explaining the variation of both RCT and a(30), and of casein content in explaining that of a(30), confirmed previous studies on dairy cows. Although future research is needed to investigate the effect of these sources of variation on cheese yield, findings from the present study suggest that casein content and acidity may be used as indicator traits to improve technological properties of buffalo milk.

Effects of different storage conditions, the farm and the stage of lactation on renneting parameters of goat milk investigated using the Formagraph method

This study evaluated the effect of storage on renneting properties of goat milk investigated using the Formagraph method. Milk samples from 169 goats in three farms (F1, F2 and F3) were analysed during an entire lactation (45, 75, 105, 135 and 165 days in milking DIM), to obtain renneting parameters, both from fresh milk and after storage with Bronopol and freezing at −20°C and −80°C. As regards fresh milk, mean values of clotting time were between 12·51 (45 DIM) and 13·29 min (105 DIM and F2), the curd firming time between 1·77 (45 DIM) and 2·15 min (F1) and curd firmness between 42·09 (165 DIM) and 49·55 mm (45 DIM). No statistical difference was recorded after storage. After regression analysis, all prediction models showed significance value at P<0·001 with the highest R2 value for clotting time, 0·710 (fresh vs. frozen milk at −20°C), and the lowest for clot firmness, 0·281 (fresh vs. frozen milk at −80°C). Results demonstrated that assessment of goat milk coagulation properties using the Formagraph method is also achievable after freezing or Bronopol addition.

Mid-infrared spectroscopy predictions as indicator traits in breeding programs for enhanced coagulation properties of milk

The aims of this study were to investigate variation of milk coagulation property (MCP) measures and their predictions obtained by mid-infrared spectroscopy (MIR), to investigate the genetic relationship between measures of MCP and MIR predictions, and to estimate the expected response from a breeding program focusing on the enhancement of MCP using MIR predictions as indicator traits. Individual milk samples were collected from 1,200 Brown Swiss cows (progeny of 50 artificial insemination sires) reared in 30 herds located in northern Italy. Rennet coagulation time (RCT, min) and curd firmness (a(30), mm) were measured using a computerized renneting meter. The MIR data were recorded over the spectral range of 4,000 to 900 cm(-1). Prediction models for RCT and a(30) based on MIR spectra were developed using partial least squares regression. A cross-validation procedure was carried out. The procedure involved the partition of available data into 2 subsets: a calibration subset and a test subset. The calibration subset was used to develop a calibration equation able to predict individual MCP phenotypes using MIR spectra. The test subset was used to validate the calibration equation and to estimate heritabilities and genetic correlations for measured MCP and their predictions obtained from MIR spectra and the calibration equation. Point estimates of heritability ranged from 0.30 to 0.34 and from 0.22 to 0.24 for RCT and a(30), respectively. Heritability estimates for MCP predictions were larger than those obtained for measured MCP. Estimated genetic correlations between measures and predictions of RCT were very high and ranged from 0.91 to 0.96. Estimates of the genetic correlation between measures and predictions of a(30) were large and ranged from 0.71 to 0.87. Predictions of MCP provided by MIR techniques can be proposed as indicator traits for the genetic enhancement of MCP. The expected response of RCT and a(30) ensured by the selection using MIR predictions as indicator traits was equal to or slightly less than the response achievable through a single measurement of these traits. Breeding strategies for the enhancement of MCP based on MIR predictions as indicator traits could be easily and immediately implemented for dairy cattle populations where routine acquisition of spectra from individual milk samples is already performed.

Prediction of coagulation properties, titratable acidity, and pH of bovine milk using mid-infrared spectroscopy

This study investigated the potential application of mid-infrared spectroscopy (MIR 4,000-900 cm(-1)) for the determination of milk coagulation properties (MCP), titratable acidity (TA), and pH in Brown Swiss milk samples (n = 1,064). Because MCP directly influence the efficiency of the cheese-making process, there is strong industrial interest in developing a rapid method for their assessment. Currently, the determination of MCP involves time-consuming laboratory-based measurements, and it is not feasible to carry out these measurements on the large numbers of milk samples associated with milk recording programs. Mid-infrared spectroscopy is an objective and nondestructive technique providing rapid real-time analysis of food compositional and quality parameters. Analysis of milk rennet coagulation time (RCT, min), curd firmness (a(30), mm), TA (SH degrees/50 mL; SH degrees = Soxhlet-Henkel degree), and pH was carried out, and MIR data were recorded over the spectral range of 4,000 to 900 cm(-1). Models were developed by partial least squares regression using untreated and pretreated spectra. The MCP, TA, and pH prediction models were improved by using the combined spectral ranges of 1,600 to 900 cm(-1), 3,040 to 1,700 cm(-1), and 4,000 to 3,470 cm(-1). The root mean square errors of cross-validation for the developed models were 2.36 min (RCT, range 24.9 min), 6.86 mm (a(30), range 58 mm), 0.25 SH degrees/50 mL (TA, range 3.58 SH degrees/50 mL), and 0.07 (pH, range 1.15). The most successfully predicted attributes were TA, RCT, and pH. The model for the prediction of TA provided approximate prediction (R(2) = 0.66), whereas the predictive models developed for RCT and pH could discriminate between high and low values (R(2) = 0.59 to 0.62). It was concluded that, although the models require further development to improve their accuracy before their application in industry, MIR spectroscopy has potential application for the assessment of RCT, TA, and pH during routine milk analysis in the dairy industry. The implementation of such models could be a means of improving MCP through phenotypic-based selection programs and to amend milk payment systems to incorporate MCP into their payment criteria.

Use of the Foodtexture Puff Device to Monitor Milk Coagulation

The further automation of cheese-making on an industrial level requires the development of sensor devices to monitor the gelation process and especially the firming phase. In this paper, the Foodtexture Puff Device (FPD) is tested for its ability to monitor the gelation process by comparing it with classical rheometry (G' and G'') in a series of coagulations at different initial milk pH (6.01 to 6.61). The FPD measures the deformation of the surface of the milk during coagulation after applying an air puff directed on this surface. The maximal and minimal deformation values and the deformation range were calculated. A nonlinear model of the registered characteristics with the time point from adding rennet until the end of the gelation process was fitted on the FPD data and also on the classic rheology parameters. It was concluded that the FPD monitored the coagulation process in the same way as the rheology. Moreover, the start point of the coagulation process as well as the strength of the coagulum could be estimated nondestructively. Therefore, the presented technology together with the nonlinear model may be a basis for the development of an industrial monitoring device.