Maria Glantz

Importance of casein micelle size and milk composition for milk gelation.

The economic output of the dairy industry is to a great extent dependent on the processing of milk into other milk-based products such as cheese. The yield and quality of cheese are dependent on both the composition and technological properties of milk. The objective of this study was to evaluate the importance and effects of casein (CN) micelle size and milk composition on milk gelation characteristics in order to evaluate the possibilities for enhancing gelation properties through breeding. Milk was collected on 4 sampling occasions at the farm level in winter and summer from dairy cows with high genetic merit, classified as elite dairy cows, of the Swedish Red and Swedish Holstein breeds. Comparisons were made with milk from a Swedish Red herd, a Swedish Holstein herd, and a Swedish dairy processor. Properties of CN micelles, such as their native and rennet-induced CN micelle size and their zeta-potential, were analyzed by photon correlation spectroscopy, and rennet-induced gelation characteristics, including gel strength, gelation time, and frequency sweeps, were determined. Milk parameters of the protein, lipid, and carbohydrate profiles as well as minerals were used to obtain correlations with native CN micelle size and gelation characteristics. Milk pH and protein, CN, and lactose contents were found to affect milk gelation. Smaller native CN micelles were shown to form stronger gels when poorly coagulating milk was excluded from the correlation analysis. In addition, milk pH correlated positively, whereas Mg and K correlated negatively with native CN micellar size. The milk from the elite dairy cows was shown to have good gelation characteristics. Furthermore, genetic progress in relation to CN micelle size was found for these cows as a correlated response to selection for the Swedish breeding objective if optimizing for milk gelation characteristics. The results indicate that selection for smaller native CN micelles and lower milk pH through breeding would enhance gelation properties and may thus improve the initial step in the processing of cheese.

The occurrence of noncoagulating milk and the association of bovine milk coagulation properties with genetic variants of the caseins in 3 Scandinavian dairy breeds

Substantial variation in milk coagulation properties has been observed among dairy cows. Consequently, raw milk from individual cows and breeds exhibits distinct coagulation capacities that potentially affect the technological properties and milk processing into cheese. This variation is largely influenced by protein composition, which is in turn affected by underlying genetic polymorphisms in the major milk proteins. In this study, we conducted a large screening on 3 major Scandinavian breeds to resolve the variation in milk coagulation traits and the frequency of milk with impaired coagulation properties (noncoagulation). In total, individual coagulation properties were measured on morning milk collected from 1,299 Danish Holstein (DH), Danish Jersey (DJ), and Swedish Red (SR) cows. The 3 breeds demonstrated notable interbreed differences in coagulation properties, with DJ cows exhibiting superior coagulation compared with the other 2 breeds. In addition, milk samples from 2% of DH and 16% of SR cows were classified as noncoagulating. Furthermore, the cows were genotyped for major genetic variants in the αS1- (CSN1S1), β- (CSN2), and κ-casein (CSN3) genes, revealing distinct differences in variant frequencies among breeds. Allele I of CSN2, which had not formerly been screened in such a high number of cows in these Scandinavian breeds, showed a frequency around 7% in DH and DJ, but was not detected in SR. Genetic polymorphisms were significantly associated with curd firming rate and rennet coagulation time. Thus, CSN1S1 C, CSN2 B, and CSN3 B positively affected milk coagulation, whereas CSN2 A(2), in particular, had a negative effect. In addition to the influence of individual casein genes, the effects of CSN1S1-CSN2-CSN3 composite genotypes were also examined, and revealed strong associations in all breeds, which more or less reflected the single gene results. Overall, milk coagulation is under the influence of additive genetic variation. Optimal milk for future cheese production can be ensured by monitoring the frequency of unfavorable variants and thus preventing an increase in the number of cows producing milk with impaired coagulation. Selective breeding for variants associated with superior milk coagulation can potentially increase raw milk quality and cheese yield in all 3 Scandinavian breeds.

Revealing the Size, Conformation, and Shape of Casein Micelles and Aggregates with Asymmetrical Flow Field-Flow Fractionation and Multiangle Light Scattering

Casein (CN) micelles are naturally occurring colloidal protein aggregates present in a dispersed state in milk. In this paper we aim to obtain a detailed description of physicochemical properties of CN micelles over the entire size distribution using asymmetrical flow field-flow fractionation (AsFlFFF) connected to multiangle light scattering (MALS) and refractive index (RI) detection. Conclusions are drawn on the colloidal level regarding shape and conformation by comparison with models of colloidal particles. By using AsFlFFF-MALS-RI, it is concluded that the CN micelles are highly polydisperse with an average rms radius and hydrodynamic radius of 177 and 116 nm, respectively. The results show that the majority of CN micelles have a spherical shape, whereas a low concentration exists of larger and elongated aggregates. By comparison with models of aggregates of colloidal particles, the aggregates are shown to be anisotropic, e.g., aggregating linearly (threadlike) or in a sheet, rather than forming randomly spherical clusters. The results show that the characterization of colloidal dispersions with AsFlFFF-MALS-RI and the comparison with theoretical models are of a general character and, thus, of fundamental importance for colloidal dispersions.

The influence of feed and herd on fatty acid composition in 3 dairy breeds (Danish Holstein, Danish Jersey, and Swedish Red)

The composition of milk fat from dairy cows is related to both genetic and environmental factors. Here, the effect of feed and herd was examined in 3 Scandinavian breeds, namely Danish Holstein-Friesian (DH), Danish Jersey (DJ), and Swedish Red (SR). In total, milk samples from 1,298 cows kept in indoor housing systems were collected from 61 conventional dairy herds in Denmark and Sweden. The fatty acid (FA) composition of milk was determined by gas chromatography and the content of α-tocopherol by HPLC. Based on the 17 individual FA determined, distinct FA profiles were observed for all breeds using univariate and multivariate statistics. The DJ cows were characterized by higher levels of saturated short-chain FA; in contrast, DH cows had higher content of unsaturated C18 FA, whereas higher levels of primarily C14:0, C14:1, C18:1 cis-9, and C18:3n-3 were evident in SR cows. This variation in milk fat composition across breeds was further reflected in different desaturase indices, which were generally higher in SR cows. In addition, α-tocopherol differed significantly among breeds, with DJ cows having the highest content. Herd-specific feeding plans were collected, and different feed items were separated into 4 broad feed categories, including grass products, maize silage, grain, and concentrate. The pronounced differences in overall feed composition among breeds were, to a large extent, due to regional differences between countries, with SR receiving higher levels of grain and grass silage compared with the Danish breeds. Within breeds, differences in feeding regimens among herds were furthermore higher in SR. Significant correlations between feed category and individual FA were observed in all breeds. Furthermore, variance components were estimated and used to determine the proportion of phenotypic variation that could be explained by herd. The herd effect for individual FA was generally lower for DH compared with the 2 other breeds. In addition, very low herd effects were shown for C14:1 and C16:1 in all breeds, suggesting that the content of these FA is mainly genetically regulated.

Effects of breed and casein genetic variants on protein profile in milk from Swedish Red, Danish Holstein, and Danish Jersey cows

In selecting cows for higher milk yields and milk quality, it is important to understand how these traits are affected by the bovine genome. The major milk proteins exhibit genetic polymorphism and these genetic variants can serve as markers for milk composition, milk production traits, and technological properties of milk. The aim of this study was to investigate the relationships between casein (CN) genetic variants and detailed protein composition in Swedish and Danish dairy milk. Milk and DNA samples were collected from approximately 400 individual cows each of 3 Scandinavian dairy breeds: Swedish Red (SR), Danish Holstein (DH), and Danish Jersey (DJ). The protein profile with relative concentrations of α-lactalbumin, β-lactoglobulin, and α(S1)-, α(S2)-, κ-, and β-CN was determined for each milk sample using capillary zone electrophoresis. The genetic variants of the α(S1)- (CSN1S1), β- (CSN2), and κ-CN (CSN3) genes for each cow were determined using TaqMan SNP genotyping assays (Applied Biosystems, Foster City, CA). Univariate statistical models were used to evaluate the effects of composite genetic variants, α(S1)-β-κ-CN, on the protein profile. The 3 studied Scandinavian breeds differed from each other regarding CN genotypes, with DH and SR having similar genotype frequencies, whereas the genotype frequencies in DJ differed from the other 2 breeds. The similarities in genotype frequencies of SR and DH and differences compared with DJ were also seen in milk production traits, gross milk composition, and protein profile. Frequencies of the most common composite α(S1)-β-κ-CN genotype BB/A(2)A(2)/AA were 30% in DH and 15% in SR, and cows that had this genotype gave milk with lower relative concentrations of κ- and β-CN and higher relative concentrations of αS-CN, than the majority of the other composite genotypes in SR and DH. The effect of composite genotypes on relative concentrations of the milk proteins was not as pronounced in DJ. The present work suggests that a higher frequency of BB/A(1)A(2)/AB, together with a decrease in BB/A(2)A(2)/AA, could have positive effects on DH and SR milk regarding, for example, the processing of cheese.

Effect of polymorphisms in the leptin, leptin receptor, and acyl-coenzyme A:diacylglycerol acyltransferase 1 (DGAT1) genes and genetic polymorphism of milk proteins on cheese characteristics.

Cheese production has increased worldwide during the last decade and is expected to increase within the coming decade as well. Despite this, the relations between cow genetics and cheese characteristics are not fully known. The aim of this study was to determine if polymorphisms in the leptin (LEP), leptin receptor (LEPR), and acyl-coenzyme A:diacylglycerol acyltransferase 1 (DGAT1) genes as well as genetic variants of β-casein (β-CN), κ-CN, and β-lactoglobulin (β-LG) affect technological properties important for cheese production and, hence, could act as genetic makers for cheese quality. Individual milk samples from the Swedish Red and the Swedish Holstein breeds were analyzed for sizes of CN micelles and fat globules as well as rennet-induced gel strength, gelation time, and yield stress. Model cheeses were produced to study yield, hardness, and pH of the cheeses. The A1457G, A252T, A59V, and C963T single nucleotide polymorphisms (SNP) were analyzed on the LEP gene, the T945M SNP on the LEPR gene, and the Nt984+8(A-G) SNP on the DGAT1 gene. In addition, genetic variants of β-CN, κ-CN, and β-LG were determined. The results indicate that technological properties were influenced by the LEPR(T945M) polymorphism, which had an association with gel strength, yield stress, and cheese hardness (T > C). However, also LEP(A252T) was shown to affect gel strength (T > A), whereas the LEP(A59V) had an effect on fat globule size (T > C). For the milk protein genes, favorable effects were found for the A and B variants of β-LG and κ-CN, respectively, on gel strength, gelation time, and yield stress. In addition, the B variant of κ-CN was shown to be associated with smaller CN micelles than the A variant. Thus, the results demonstrate potential genetic markers for cheese characteristics. However, milk composition traits also affected the obtained results, thus making it necessary to thoroughly assess the different aspects regarding the influence of gene effects on cheese characteristics before directly selecting for certain alleles or genetic variants to improve the processing and quality of cheese.

Effects of animal selection on milk composition and processability

One goal of animal breeding is to increase the economic output through increased production, improved milk quality, and cow health. The objective of this study was to evaluate genetic progress in relation to milk composition, processability, and yield as a correlated response to selection for the Swedish breeding objective. Dairy cows with high genetic merit, classified as elite dairy cows, of the Swedish Red and Swedish Holstein breeds were used. Milk samples were collected on the farm level in winter and summer from a research herd at Nötcenter Viken, a bovine research farm in Sweden. Comparisons were made with milk from a Swedish Red herd, a Swedish Holstein herd, and a Swedish dairy processor in the same geographical area. Protein, lipid, and carbohydrate profiles as well as minerals were analyzed, and technological properties, including rennet-induced gelation characteristics, lipid oxidation, total antioxidant capacity, and fat globule size, were determined. Higher yields were found for elite cows for components of the protein, lipid, and carbohydrate profiles as well as for minerals, implying genetic progress in relation to milk yield; however, the content of some milk components (e.g., lipid and whey protein contents) had decreased on average. Milk from the elite cows had good gelation characteristics, but was more susceptible to lipid autooxidation and had a lower total antioxidant capacity. These results demonstrate that milk composition and processing characteristics could be used to adjust breeding practices to optimize the quality and stability of milk and dairy products.

Bovine chromosomal regions affecting rheological traits in acid-induced skim milk gels

The production of fermented milk products has increased worldwide during the last decade and is expected to continue to increase during the coming decade. The quality of these products may be optimized through breeding practices; however, the relations between cow genetics and technological properties of acid milk gels are not fully known. Therefore, the aim of this study was to identify chromosomal regions affecting acid-induced coagulation properties and possible candidate genes. Skim milk samples from 377 Swedish Red cows were rheologically analyzed for acid-induced coagulation properties using low-amplitude oscillation measurements. The resulting traits, including gel strength, coagulation time, and yield stress, were used to conduct a genome-wide association study. Single nucleotide polymorphisms (SNP) were identified using the BovineHD SNPChip (Illumina Inc., San Diego, CA), resulting in almost 621,000 segregating markers. The genome was scanned for putative quantitative trait loci (QTL) regions, haplotypes based on highly associated SNP were inferred, and the additive genetic effects of haplotypes within each QTL region were analyzed using mixed models. A total of 8 genomic regions were identified, with large effects of the significant haplotype explaining between 4.8 and 9.8% of the phenotypic variance of the studied traits. One major QTL was identified to overlap between gel strength and yield stress, the QTL identified with the most significant SNP closest to the gene coding for κ-casein (CSN3). In addition, a chromosome-wide significant region affecting yield stress on BTA 11 was identified to be colocated with PAEP, coding for β-lactoglobulin. Furthermore, the coagulation properties of the genetic variants within the 2 genes were compared with the coagulation properties identified by the patterns of the haplotypes within the regions, and it was discovered that the haplotypes were more diverse and in one case slightly better at explaining the phenotypic variance. Besides these significant QTL comprising the 2 milk proteins, 3 additional genes are proposed as possible candidates, namely RAB22A, CDH13, and STAT1, and all have previously been found to be expressed in the mammary gland. To our knowledge, this is the first attempt to map QTL regions for acid-induced coagulation properties.

Effect of polymorphisms in the leptin, leptin receptor and acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1) genes and genetic polymorphism of milk proteins on bovine milk composition.

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.

Genomic selection in relation to bovine milk composition and processability.

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.