M. Penasa

Invited review: Genetics and modeling of milk coagulation properties

Milk coagulation properties (MCP) are conventionally measured using computerized renneting meters, mechanical or optical devices that record curd firmness over time (CF(t)). The traditional MCP are rennet coagulation time (RCT, min), curd firmness (a(30), mm), and curd-firming time (k(20), min). The milk of different ruminant species varies in terms of CF(t) pattern. Milk from Holstein-Friesian and some Scandinavian cattle breeds yields higher proportions of noncoagulating samples, samples with longer RCT and lower a(30), and samples for which k(20) is not estimable, than does milk from Brown Swiss, Simmental, and other local Alpine breeds. The amount, proportion, and genetic variants (especially κ-casein) of milk protein fractions strongly influence MCP and explain variable proportions of the observed differences among breeds and among individuals of the same breed. In addition, other major genes have been shown to affect MCP. Individual repeatability of MCP is high, whereas any herd effect is low; thus, the improvement of MCP should be based principally on selection. Exploitable additive genetic variation in MCP exists and has been assessed using different breeds in various countries. Several models have been formulated that either handle noncoagulating samples or not. The heritability of MCP is similar to that of other milk quality traits and is higher than the heritability of milk yield. Rennet coagulation time and a(30) are highly correlated, both phenotypically and genetically. This means that the use of a(30) data does not add valuable information to that obtainable from RCT; both traits are genetically correlated mainly with milk acidity. Moreover, a(30) is correlated with casein content. The major limitations of traditional MCP can be overcome by prolonging the observation period and by using a novel CF(t) modeling, which uses all available information provided by computerized renneting meters and allows the estimation of RCT, the potential asymptotic curd firmness, the curd-firming rate, and the syneresis rate. Direct measurements of RCT obtained from both mechanical and optical devices show similar heritabilities and exhibit high phenotypic and genetic correlations. Moreover, mid-infrared reflectance spectroscopy can predict MCP. The heritabilities of predicted MCP are higher than those of measured MCP, and the 2 sets of values are strongly correlated. Therefore, mid-infrared reflectance spectroscopy is a reliable and cheap method whereby MCP can be improved at the population level; this is because such spectra are already routinely acquired from the milk of cows enrolled in milk recording schemes.

Invited review: Mid-infrared spectroscopy as phenotyping tool for milk traits1

Interest in methods that routinely and accurately measure and predict animal characteristics is growing in importance, both for quality characterization of livestock products and for genetic purposes. Mid-infrared spectroscopy (MIRS) is a rapid and cost-effective tool for recording phenotypes at the population level. Mid-infrared spectroscopy is based on crossing matter by electromagnetic radiation and on the subsequent measure of energy absorption, and it is commonly used to determine traditional milk quality traits in official milk laboratories. The aim of this review was to focus on the use of MIRS to predict new milk phenotypes of economic relevance such as fatty acid and protein composition, coagulation properties, acidity, mineral composition, ketone bodies, body energy status, and methane emissions. Analysis of the literature demonstrated the feasibility of MIRS to predict these traits, with different accuracies and with margins of improvement of prediction equations. In general, the reviewed papers underlined the influence of data variability, reference method, and unit of measurement on the development of robust models. A crucial point in favor of the application of MIRS is to stimulate the exchange of data among countries to develop equations that take into account the biological variability of the studied traits under different conditions. Due to the large variability of reference methods used for MIRS calibration, it is essential to standardize the methods used within and across countries.

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.

Reproducibility and Repeatability of Measures of Milk Coagulation Properties and Predictive Ability of Mid-Infrared Reflectance Spectroscopy

The objectives of the study were to estimate the reproducibility and repeatability of milk coagulation properties (MCP) measured by a computerized renneting meter (CRM) and to evaluate the predictive ability of mid-infrared spectroscopy (MIRS) as an innovative technology for the assessment of rennet coagulation time (RCT, min) and curd firmness (a(30), mm). Four samples without addition of preservative (NP) and 4 samples with Bronopol addition (PS) were collected from each of 83 Holstein-Friesian cows. Six hours after collection, 2 replicated measures of MCP were obtained with CRM using 1 NP and 1 PS sample from each cow. Mid-infrared spectra of the remaining NP and PS samples from each animal were recorded after 6 h, 4 d, and 8 d after sampling. Two groups of calibration equations were developed using MIRS spectra and CRM measures of MCP as reference data obtained from analysis of NP and PS, respectively. Reproducibility and repeatability of CRM measures were obtained from REML estimation of variance components on the basis of a linear model including the fixed effects of herd and days in milk class and the random effects of cows, sample treatment (addition or no addition of preservative), and the interaction between cow and sample treatment. Coefficient of reproducibility is an indicator of the agreement between 2 measurements of MCP for the same milk sample preserved with or without addition of Bronopol. Coefficient of repeatability is an indicator of the agreement between repeated measures of MCP. Pearson correlations between MCP measures for NP and PS were 0.97 and 0.83 for RCT and a(30), respectively. Reproducibility of CRM measures under different preserving conditions of milk was 93.5% for RCT and 64.6% for a(30). Repeatabilities of RCT and a(30) measures were 95.7 and 77.3%, respectively. Based on the estimated cross-validation standard errors and coefficients of determination and ratios of standard errors of cross-validation to standard deviation of reference data, the predictive ability of MIRS calibration equations was moderate for RCT and unsatisfactory for a(30.) Predictive ability of equations based on spectra and MCP measures of PS was greater than that of equations based on data of NP. The study did not provide conclusive evidence on the effectiveness of MIRS as a predictive tool for MCP and it requires an enlargement of the variability of milk sampling circumstances. Because the relevance of MIRS predictions in relation to breeding programs for MCP based on indicator traits relies on the genetic variation of MIRS predictions and on phenotypic and genetic correlations between MIRS predictions and MCP measures, additional specific investigations on these topics are needed.

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.

Genetic parameters of coagulation properties, milk yield, quality, and acidity estimated using coagulating and noncoagulating milk information in Brown Swiss and Holstein-Friesian cows

The aim of this study was to estimate heritabilities of rennet coagulation time (RCT) and curd firmness (a(30)) and their genetic correlations with test-day milk yield, composition (fat, protein, and casein content), somatic cell score, and acidity (pH and titratable acidity) using coagulating and noncoagulating (NC) milk information. Data were from 1,025 Holstein-Friesian (HF) and 1,234 Brown Swiss (BS) cows, which were progeny of 54 HF and 58 BS artificial insemination sires, respectively. Milk coagulation properties (MCP) of each cow were measured once using a computerized renneting meter and samples not exhibiting coagulation within 31 min after rennet addition were classified as NC milk. For NC samples, RCT was unobserved. Multivariate analyses, using Bayesian methodology, were performed to estimate the genetic relationships of RCT or a(30) with the other traits and statistical inference was based on the marginal posterior distributions of parameters of concern. For analyses involving RCT, a right-censored Gaussian linear model was used and records of NC milk samples, being censored records, were included as unknown parameters in the model implementing a data augmentation procedure. Rennet coagulation time was more heritable [heritability (h(2))=0.240 and h(2)=0.210 for HF and BS, respectively] than a(30) (h(2)=0.148 and h(2)=0.168 for HF and BS, respectively). Milk coagulation properties were more heritable than a single test-day milk yield (h(2)=0.103 and h(2)=0.097 for HF and BS, respectively) and less heritable than milk composition traits whose heritability ranged from 0.275 to 0.275, with the only exception of fat content of BS milk (h(2)=0.108). A negative genetic correlation, lower than -0.85, was estimated between RCT and a(30) for both breeds. Genetic relationships of MCP with yield and composition were low or moderate and favorable. The genetic correlation of somatic cell score with RCT in BS cows was large and positive and even more positive were those of RCT with pH and titratable acidity in both breeds, ranging from 0.80 to 0.94. Including NC milk information in the data affected the estimated correlations and decreased the uncertainty associated with the estimation process. On the basis of the estimated heritabilities and genetic correlations, enhancement of MCP through selective breeding with no detrimental effects on yield and composition seems feasible in both breeds. Milk acidity may play a role as an indicator trait for indirect enhancement of MCP.

Effectiveness of mid-infrared spectroscopy to predict fatty acid composition of Brown Swiss bovine milk

Mid-infrared spectroscopy (MIR) is used to predict fatty acid (FA) composition of individual milk samples (n=267) of Brown Swiss cows. FAs were analyzed by gas chromatography as a reference method. Samples were scanned (4000 to 900 cm-1) by MIR, and predictive models were developed using modified partial least squares regressions with full cross-validation. The methods using a first derivative or multiplicative scatter corrected plus first derivative resulted, on average, in the best predictions. Coefficients of correlation between measured and predicted C8:0, C10:0, C12:0, C14:0, anteiso-C17:0, c9-C18:1, and medium- and long-chain FA, and saturated, monounsaturated and unsaturated FA ranged from 0.71 to 0.77, suggesting that prediction models can be implemented in milk recording schemes to routinely collect information on FA composition from the whole Brown Swiss population for breeding purposes.

Effect of milk composition and coagulation traits on Grana Padano cheese yield under field conditions

The aim of this study was to assess the effect of chemical composition, coagulation properties, pH, and titratable acidity (TA, SH°/50 ml) of vat milk on Grana Padano cheese yield (CY) under field conditions. Twelve cheese-making sessions were carried out from February to December 2009 in a dairy cooperative of Grana Padano Consortium (Italy), for a total of 96 vats of milk processed. For each vat, samples of raw milk were collected and analysed for quality traits (fat, protein, and casein contents), pH, TA, and milk coagulation properties (MCP), measured as rennet coagulation time (RCT, min), curd-firming time (k(20), min), and curd firmness (a(30), mm). Cheese yield was expressed as kilograms of cheese per 100 kg milk transformed, and was measured after 2 d of drainage. Fat, protein, and casein contents were positively and strongly correlated with CY (coefficients of correlation, r = 0.72, 0.88, and 0.84, respectively; P < 0.001). Coagulation properties were moderately and significantly (P < 0.001) related to CY: milk that coagulated earlier and had stronger a(30) was associated to greater CY. Cheese yield was analysed with a model that accounted for fixed effects of cheese-making day, fat and protein content, TA, and a(30). Significance was found for all the effects (P < 0.05). Milk characterised by high values of a(30) resulted in higher CY than milk with low values of a 30, indicating that MCP could be used as indicators of cheese-making efficiency. Future research should investigate the relationships between MCP and quality of cheese, and explore the feasibility of including MCP in multiple component milk pricing system for Grana Padano cheese production.

Short communication: Influence of composite casein genotypes on additive genetic variation of milk production traits and coagulation properties in Holstein-Friesian cows

The aim of the study was to quantify the effects of composite beta- and kappa-casein (CN) genotypes on genetic variation of milk coagulation properties (MCP); milk yield; fat, protein, and CN contents; somatic cell score; pH; and titratable acidity (TA) in 1,042 Italian Holstein-Friesian cows. Milk coagulation properties were defined as rennet coagulation time (RCT) and curd firmness (a(30)). Variance components were estimated using 2 animal models: model 1 included herd, days in milk, and parity as fixed effects and animal and residual as random effects, and model 2 was model 1 with the addition of composite beta- and kappa-CN genotype as a fixed effect. Genetic correlations between RCT and a(30) and between these traits and milk production traits were obtained with bivariate analyses, based on the same models. The inclusion of casein genotypes led to a decrease of 47, 68, 18, and 23% in the genetic variance for RCT, a(30), pH, and TA, respectively, and less than 6% for other traits. Heritability of RCT and a(30) decreased from 0.248 to 0.143 and from 0.123 to 0.043, respectively. A moderate reduction was found for pH and TA, whereas negligible changes were detected for other milk traits. Estimates of genetic correlations were comparable between the 2 models. Results show that composite beta- and kappa-CN genotypes are important for RCT and a(30) but cannot replace the recording of MCP themselves.

Use of near infrared transmittance spectroscopy to predict fatty acid composition of chicken meat.

In the present study, near infrared transmittance (NIT) spectroscopy was tested as a potential analytical technique to predict the FA profile of ground chicken breast (Pectoralis superficialis) considering the wavelengths between 850 and 1050 nm. Calibration equations were built using reference data expressed as (i) percentage of total FA and (ii) absolute concentration, i.e., mg of FA in 100 g of fresh meat. Calibrations developed on FA expressed in absolute concentration were much more accurate than those developed on percentage of total FA. The highest performances were obtained for two groups of FA, namely saturated and monounsaturated (R(CV)(2) of 0.90 and 0.93, and SE(CV) of 53.59 and 70.13 mg of FA on 100 g of meat, respectively), and for few individual FA (palmitic acid, oleic acid), having R(CV)(2) higher than 0.9. Sample pre-processing (milling) and different spectra pre-treatments were necessary to maximise the performance. Polyunsaturated FA were the hardest components to determine (R(CV)(2) of 0.62 and SE(CV) of 61.96 mg of FA on 100g of meat) and results suggest that NIT spectroscopy cannot be referred to as reliable method to predict these constituents.