Estimation of genetic parameters for milk production in the first three lactations

Teepker, G.; Swalve, Hermann H.

doi:10.1016/0301-6226(88)90072-3

Cited by 18 publications

(12 citation statements)

References 11 publications

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“…The large residual variance associated with the third lactation could be due to changes in the mean lactation milk yield and other sources of variation not accounted for in the models such as length of the dry and gestation periods influencing subsequent lactations. Increased residual variance in later lactations has also been reported (Teepker and Swalve, 1988;Rekaya et al, 1999).…”

Section: Resultsmentioning

confidence: 73%

Genetic and phenotypic parameters for test day milk yield of Sahiwal cattle in the semi-arid tropics

Ilatsia

Muasya

Muhuyi

et al. 2007

Animal

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A total of 19 376 test day (TD) milk yield records from the first three lactations of 1618 cows daughters of 162 sires were used to estimate genetic and phenotypic parameters and determine the relationship between daily milk yield and lactation milk yield in the Sahiwal cattle in Kenya. Variance components were estimated using animal models based on a derivative free restricted maximum likelihood procedure. Variance components were estimated using various univariate and multi-trait fixed regression test day models (TDM) that defined contemporary groups either based on the year-season of calving (YSCV) or on the year-season of TD milk sampling (YSTD). Variance components were influenced by CG which resulted in differences in heritability and repeatability estimates between TDM. Models considering YSTD resulted in higher additive genetic variances and lower residual variances compared with models in which YSCV was considered. Heritability estimates for daily yield ranged from 0.28 to 0.46, 0.38 to 0.52 and 0.33 to 0.52 in the first, second and third lactation, respectively. In the first and second lactation, the heritability estimates were highest between TD 2 and TD 4. Genetic correlations among daily milk yields ranged from 0.41 to 0.93, 0.50 to 0.83 and 0.43 to 86 in the first, second and third lactation, respectively. The phenotypic correlations were correspondingly lower. Genetic correlations were different from unit when fitting multi-trait TDM. Therefore, a multiple trait model would be more ideal in determining the genetic merit of dairy sires and bulls based on daily yield records. Genetic and phenotypic correlations between daily yield and lactation yields were high and positive. Genetic correlations ranged from 0.84 to 0.99, 0.94 to 1.00 and 0.94 to 0.97 in the first, second and third lactations, respectively. The corresponding phenotypic correlation estimates ranged from 0.50 to 0.85, 0.50 to 0.83 and 0.53 to 0.87. The high genetic correlation between daily yield and lactation yield imply that both traits are influenced by similar genes. Therefore daily yields records could be used in genetic evaluation in the Sahiwal cattle breeding programme.

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Section: Resultsmentioning

confidence: 73%

Genetic and phenotypic parameters for test day milk yield of Sahiwal cattle in the semi-arid tropics

Ilatsia

Muasya

Muhuyi

et al. 2007

Animal

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“…This was also observed by de Roos (personal communication). With lactation models, Tong et al [28], Teepker and Swalve [27] or Schutz et al [25] found that the heritability of fat or protein content was close to 0.50. This was also found in this study with a TDM.…”

Section: Estimation Of Parameters In the First Three Lactationsmentioning

confidence: 99%

Estimation of genetic parameters for test day records of dairy traits in the first three lactations

2005

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-Application of test-day models for the genetic evaluation of dairy populations requires the solution of large mixed model equations. The size of the (co)variance matrices required with such models can be reduced through the use of its first eigenvectors. Here, the first two eigenvectors of (co)variance matrices estimated for dairy traits in first lactation were used as covariables to jointly estimate genetic parameters of the first three lactations. These eigenvectors appear to be similar across traits and have a biological interpretation, one being related to the level of production and the other to persistency. Furthermore, they explain more than 95% of the total genetic variation. Variances and heritabilities obtained with this model were consistent with previous studies. High correlations were found among production levels in different lactations. Persistency measures were less correlated. Genetic correlations between second and third lactations were close to one, indicating that these can be considered as the same trait. Genetic correlations within lactation were high except between extreme parts of the lactation. This study shows that the use of eigenvectors can reduce the rank of (co)variance matrices for the test-day model and can provide consistent genetic parameters. genetic parameters / test-day model / dairy traits / reduced rank

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“…A further growth in the demand for milk protein in comparison with the other milk components such as fat and lactose is anticipated due to the expected change in consumer habits. Milk protein yield is mainly dependent on milk yield (correlation 0.83), but also on milk protein concentration (correlation 0.06) (Teepker and Swalve, 1988). However, increases in milk yield are not only associated with increased milk protein production, but in general also with the energy-demanding production of milk fat and lactose in the mammary gland.…”

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confidence: 99%

Composition of major proteins in cow milk differing in mean protein concentration during the first 155 days of lactation and the influence of season as well as short-term restricted feeding in early and mid-lactation

Gellrich¹,

Meyer²,

Wiedemann³

2014

CZECH J ANIM SCI

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A variety of proteins contributes greatly to the unique nutritional and functional quality of dairy cow milk. Particularly, milk casein content and composition have substantial influence on the processing capabilities. In the present study, milk of 23 multiparous Holstein-Friesian cows, grouped as high-(3.49 ± 0.05%; n = 11) and low-protein (3.03 ± 0.05%; n = 12) cows, was sampled approximately weekly during the first 155 days of lactation to determine the course of relative milk protein composition (α-lactalbumin; β-lactoglobulin; α-, β-, and κ-casein). Furthermore, feed restrictions by 30% of dry matter intake in early and mid-lactation as well as experimental tissue biopsies were conducted to observe their effect on milk protein composition. Milk protein composition was relatively stable and displayed similar concentration patterns throughout the experimental period between both groups. Mean relative concentrations of α-, β-, κ-casein, α-lactalbumin, and β-lactoglobulin were 34.2, 31.4, 16.0, 2.1, and 9.7% of total protein, respectively. Feed restrictions did not alter milk protein composition, whereas the season influenced α-and β-casein as well as α-lactalbumin. Further, effects were observed in both groups at times of unfamiliar stressful situations caused by taking liver or muscle biopsies. As a result, the relative concentration of β-casein increased. Therefore, acute stress factors may lead to a deviation in milk protein composition and should be avoided.

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Estimation of genetic parameters for milk production in the first three lactations

Cited by 18 publications

References 11 publications

Genetic and phenotypic parameters for test day milk yield of Sahiwal cattle in the semi-arid tropics

Genetic and phenotypic parameters for test day milk yield of Sahiwal cattle in the semi-arid tropics

Estimation of genetic parameters for test day records of dairy traits in the first three lactations

Composition of major proteins in cow milk differing in mean protein concentration during the first 155 days of lactation and the influence of season as well as short-term restricted feeding in early and mid-lactation

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