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Genomic selection is a new technology in which selection decisions are based on direct genomic values (DGVs) or genomic enhanced breeding values (GEBVs). The objective of this study was to evaluate the relations between DGVs and several milk traits important for both the nutritional value and processability of milk. This is a new approach and can be used to increase the knowledge on how genomic selection can be used in practice. Morning milk samples from Swedish Holstein cows were analyzed for milk composition and technological properties. DGVs were received for each cow for milk, protein and fat yield, milk index, udder health, Nordic total merit and a quota was calculated between fat and milk yield as well as protein and milk yield. The results show that linear correlations exist (P<0·10) between the studied DGVs and contents and yields of parameters in the protein (P=0·002–0·097), fat (P=0·024–0·055) and mineral profiles (P=0·001–0·099) as well as for cheese characteristics (P=0·004–0·065), thus making it possible to obtain detailed information on milk traits that are not registered in the milk recording scheme. Hence, genomic selection will be an efficient tool for breeding and dairy industry to select cows early in life for targeted milk production.
The relations between cow genetics and milk composition have gained a lot of attention during the past years, however, generally only a few compositional traits have been examined. The aim of this study was to determine if polymorphisms in the leptin (LEP), leptin receptor (LEPR) and acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1) genes as well as genetic polymorphism of β-casein (β-CN), κ-CN and β-lactoglobulin (β-LG) impact several bovine milk composition traits. Individual milk samples from the Swedish Red and Swedish Holstein breeds were analyzed for components in the protein, lipid, carbohydrate and mineral profiles. Cow alleles were determined on the following SNP: A1457G, A252T, A59V and C963T on the LEP gene, T945M on the LEPR gene and Nt984+8(A-G) on the DGAT1 gene. Additionally, genetic variants of β-CN, κ-CN and β-LG were determined. For both the breeds, the same tendency of minor allele frequency was found for all SNPs and protein genes, except on LEPA1457G and LEPC963T. This study indicated significant (P<0·05) associations between the studied SNPs and several compositional parameters. Protein content was influenced by LEPA1457G (G>A) and LEPC963T (T>C), whereas total Ca, ionic Ca concentration and milk pH were affected by LEPA1457G, LEPA59V, LEPC963T and LEPRT945M. However, yields of milk, protein, CN, lactose, total Ca and P were mainly affected by β-CN (A2>A1) and κ-CN (A>B>E). β-LG was mainly associated with whey protein yield and ionic Ca concentration (A>B). Thus, this study shows possibilities of using these polymorphisms as markers within genetic selection programs to improve and adjust several compositional parameters.
The somatic cell count (SCC) in bovine bulk tank milk is presently used as an indicator of raw milk quality, reflecting the udder health status of the herd. During mastitis, SCC increases, mostly owing to an influx of polymorphonuclear leucocytes (PMN) from blood into milk, with a concomitant change in milk composition. Bulk tank milk samples were categorized according to their SCC, as well as polymorphonuclear leucocyte count (PMNC), to study relationships between SCC, PMNC and various raw milk quality traits, i.e. contents of total protein, whey protein, casein, fat and lactose, casein number, proteolysis and rheological properties. The proportion of PMN, obtained by direct microscopy, was significantly higher in samples with high SCC compared with low SCC samples. SCC and PMNC were strongly correlated, yielding a correlation coefficient of 0·85. High SCC samples had lower lactose and casein contents, lower casein number and more proteolysis than low SCC samples. Samples with high PMNC had a lower casein number than low PMNC samples. Samples with high and low SCC or PMNC did not differ in respect to rheological properties. Our results do not indicate that PMNC is a better biomarker than SCC for raw bulk tank milk quality, as previously proposed.
The somatic cell count (SCC) in milk is associated with increasing proteolytic degradation of caseins and it has been suggested that enzymes derived from somatic cells contribute to a lower yield and poorer quality of cheese. It is essential to increase the knowledge on naturally occurring milk proteinase activities to better understand how to improve the technological quality of milk. The aim of this work was to identify peptides actually present in milk as a result of proteolysis at different levels of SCC and to assign these peptides to potential responsible proteases where possible. Peptide fractions were prepared from acid whey by ultrafiltration at a molecular cut-off value of 10 000 Da. The peptides were separated using capillary reversed phase high performance liquid chromatography (RP-HPLC) and identified by matrix-assisted laser desorption/ionization-time of flight tandem mass spectrometry (MALDI-TOF MS/MS). Peptides identified ranged in mass from 1023 to 2000 Da, and originated from αS1-, αS2- or β-casein. Possible responsible proteases that could be suggested when examining the peptide cleavage sites included plasmin, cathepsin B, D and leukocyte elastase. The results indicated that plasmin was primarily responsible for the observed proteolysis in milk at low cell count, whereas the cathepsins and elastase became implicated at elevated cell count. Specificity and activity of cathepsins and elastase has earlier mainly been studied in model systems, whereas less is known about their activities in milk itself. This is also the first indication of involvement of elastase in milk proteolysis through the unequivocal determination of cleavage sites.
Lipid auto-oxidation in milk is affected by a complex interplay of pro- and antioxidants. Several of these compounds are also important nutrients in the human diet and may have other physiological effects in the gastrointestinal tract and other tissues. Among antioxidative enzymes superoxide dismutase catalyses the dismutation of superoxide anion to hydrogen peroxide. The degradation of hydrogen peroxide can be catalysed by catalase and the selenoprotein glutathione peroxidase. The latter enzyme can also degrade lipid peroxides. Lactoferrin may have an important role by binding pro-oxidative iron ions. The occurrence of different forms of these antioxidative proteins in milk and available data on their functional role are reviewed. More remains to be learnt of individual compounds and as an example the potential role of seleno compounds in milk is virtually unknown. Antioxidative vitamins in milk can provide an important contribution to the daily dietary intake. Moreover vitamin E and carotenoids act as fat-soluble antioxidants, e.g. in the milk fat globule membrane, which is regarded as a major site of auto-oxidation. Vitamin C is an important water-soluble antioxidant and interacts in a complex manner with iron and fat-soluble antioxidants. The concentrations of these compounds in milk are affected by cow feeding rations and milk storage conditions. Since milk contains a number of antioxidants many reactions are possible and the specific function of each antioxidant cannot easily be defined. There are indications that other compounds may have antioxidative function and measurement of total antioxidative capacity should be a useful tool in evaluating their relative roles.
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