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.

Milk coagulation properties (MCP) are an important aspect in assessing cheese-making ability. Several studies showed that favorable conditions of milk reactivity with rennet, curd formation rate, and curd strength, as well as curd syneresis, have a positive effect on the entire cheese-making process and subsequently on the ripening of cheese. Moreover, MCP were found to be heritable, but little scientific literature is available about their genetic aspects. The aims of this study were to estimate heritability of MCP and genetic correlations among MCP and milk production and quality traits. A total of 1,071 Italian Holstein cows (progeny of 54 sires) reared in 34 herds in Northern Italy were sampled from January to July 2004. Individual milk samples were collected during the morning milking and analyzed for coagulation time (RCT), curd firmness (a30), pH, titratable acidity, fat, protein, and casein contents, and somatic cell count. About 10% of individual milk samples did not coagulate in 31 min, so they were removed from the analyses. Estimates of heritability for RCT and a30 were 0.25 +/- 0.04 and 0.15 +/- 0.03, respectively. Estimates of genetic correlations between MCP traits and milk production traits were negligible except for a30 with protein and casein contents (0.44 +/- 0.10 and 0.53 +/- 0.09, respectively). Estimates of genetic correlations between MCP traits and somatic cell score were strong and favorable, as well as those between MCP and pH and titratable acidity. Selecting for high casein content, milk acidity, and low somatic cell count might be an indirect way to improve MCP without reducing milk yield and quality traits.

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.

This work reports on use of the recently described amplified fragment length polymorphism (AFLP) technology for DNA fingerprinting in cattle. The AFLP technology produces molecular markers through the high-stringency polymerase chain reaction (PCR)-amplification of restriction fragments that are ligated to synthetic adapters and amplified using primers, complementary to the adapters, which carry selective nucleotides at their 3' ends. While, for plants, the double digestion of genomic DNA with EcoRI and MseI is suggested, in mammals the enzyme combination EcoRI/TaqI produces clearer and more polymorphic AFLP patterns. In a sample of 47 Italian Holstein genotypes, 16 EcoRI/TaqI primer combinations identified 248 polymorphic bands in a species known for its low level of restriction polymorphism. In spite of the low information content carried by each AFLP polymorphism (average polymorphism information content = 0.31), the number of fragments revealed by each primer combination increased significantly the level of genetic information gained in each experiment. AFLP patterns are reproducible in independent experiments and polymorphic fragments segregate in cattle families according to Mendelian rules.

The objective of this study was to estimate genetic parameters for conjugated linoleic acid (CLA) and other selected milk fatty acid (FA) content and for unsaturation ratios in the Italian Holstein Friesian population. Furthermore, the relationship of milk FA with milk fat and protein content was considered. One morning milk sample was collected from 990 Italian Holstein Friesian cows randomly sampled from 54 half-sib families, located in 34 commercial herds in the North-eastern part of Italy. Each sample was analyzed for milk percentages of fat and protein, and for single FA percentages (computed as FA weight as a proportion of total fat weight). Heritabilities were moderate for unsaturated FA, ranging from 0.14 for C16:1 to 0.19 for C14:1. Less than 10% of heritability was estimated for each saturated FA content. Heritability for index of desaturation, monounsaturated FA and CLA/trans-11 18:1 ratio were 0.15, 0.14, and 0.15, respectively. Standard errors of the heritability values ranged from 0.02 to 0.06. Genetic correlations were high and negative between C16:0 and C18:0, as well as between C14:0 and C18:0. Genetic correlations of index of desaturation were high and negative with C14:0 and C16:0 (-0.70 and -0.72, respectively), and close to zero (0.03) with C18:0. The genetic correlation of C16:0 with fat percentage was positive (0.74), implying that selection for fat percentage should result in a correlated increase of C16:0, whereas trans-11 C18:1 and cis-9, trans-11 C18:2 contents decreased with increasing fat percentage (-0.69 and -0.55, respectively). Genetic correlations of fat percentage with 14:1/14 and 16:1/16 ratios were positive, whereas genetic correlations of fat percentage with 18:1/18 and CLA/trans-11 18:1 ratios were negative. These results suggest that it is possible to change the milk FA composition by genetic selection, which offers opportunities to meet consumer demands regarding health aspects of milk and dairy products.

The aim of the study was to estimate the effect of the composite CSN2 and CSN3 genotypes on milk coagulation, quality, and yield traits in Italian Holstein cows. A total of 1,042 multiparous Holstein cows reared on 34 commercial dairy herds were sampled once, concurrently with monthly herd milk recording. The data included the following traits: milk coagulation time; curd firmness; pH and titratable acidity; fat, protein, and casein contents; somatic cell score; and daily milk, fat, and protein yields. A single-trait animal model was assumed with fixed effects of herd, days in milk, parity, composite casein genotype of CSN2 and CSN3 (CSN2-CSN3), and random additive genetic effect of an animal. The composite genotype of CSN2-CSN3 showed a strong effect on both milk coagulation traits and milk and protein yields, but not on fat and protein contents and other milk quality traits. For coagulation time, the best CSN2-CSN3 genotypes were those with at least one B allele in both the CSN2 and CSN3 loci. The CSN3 locus was associated more strongly with milk coagulation traits, whereas the CSN2 locus was associated more with milk and protein yields. However, because of the tight linkage between the 2 loci, the composite genotypes, or haplotypes, are more appropriate than the single-locus genotypes if they were considered for use in selection.

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Samples of herd milk (506) were analyzed to assess sources of variation for milk coagulation properties (MCP) for 5 different dairy cattle breeds. Data were recorded in 55 single-breed dairy herds in the Trento province, a mountain area in northeast Italy. The 5 cattle breeds were Holstein-Friesian (8 herds), Brown Swiss (16 herds), Simmental (10 herds), Rendena (13 herds), and Alpine Gray (8 herds). Herd milk samples were analyzed for the MCP traits, milk rennet coagulation time (RCT), curd-firming time, and curd firmness (a30), as well as protein and fat percentages, somatic cell count, Soxhlet-Henkel acidity, and bacterial count. An ANOVA was performed to study the effect of breed, herd within breed, DIM, month of lactation, protein and fat percentages, somatic cell score, titratable acidity, and log bacterial count within breed on MCP. Breed was the most important source of variation. In particular, the Rendena breed showed the best MCP traits at 13.5 min and 27.0 mm for RCT and a30, respectively. The Holstein-Friesian breed had the worst coagulation properties at 18.0 min and 17.5 mm for RCT and a30, respectively. The other 3 breeds showed intermediate coagulation properties. The RCT values were better at the beginning of lactation, whereas RCT and a30 values were better in September and October (14.3 min and 25.7 mm, respectively). Among the composition traits, only the titratable acidity affected MCP traits of herd milk positively.