Efficiency of selection for different cumulative milk, fat and protein yields in first lactation

Wilmink, J.B.M.

doi:10.1016/0301-6226(87)90067-4

Cited by 50 publications

(52 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In such a context, Jamrozik and Schaeffer (1997) reported very high heritability estimates using TDM, but negative genetic correlations among test days in early and late lactation when using Ali and Schaeffer (1987) curve to adjust the additive genetic effect, assuming the non-hereditary animal effect constant. Later, Jamrozik et al (1997a and b), using the Wilmink (1987) curve reported more realistic heritability estimates at the beginning and end of lactation, indicating the importance of adequate modeling of the non-hereditary animal effect in random regression models. Brotherstone et al (2000) reported that the parametric curves of Ali and Schaeffer (1987) and Wilmink (1987) were more adequate in adjusting the milk yields first lactation Holstein cows when compared with Legendre orthogonal polynomials.…”

Section: Introductionmentioning

confidence: 99%

“…Later, Jamrozik et al (1997a and b), using the Wilmink (1987) curve reported more realistic heritability estimates at the beginning and end of lactation, indicating the importance of adequate modeling of the non-hereditary animal effect in random regression models. Brotherstone et al (2000) reported that the parametric curves of Ali and Schaeffer (1987) and Wilmink (1987) were more adequate in adjusting the milk yields first lactation Holstein cows when compared with Legendre orthogonal polynomials.…”

Section: Introductionmentioning

confidence: 99%

“…The parametric functions of Ali and Schaeffer (1987) and Wilmink (1987) have been used in the adjustment of RRM, as they allow the modeling of the lactation curve and simultaneously characterise the covariance structure among the test day yields (Jamrozik and Schaeffer, 1997;Brotherstone et al, 2000). The implementation of RRM for genetic evaluations of dairy cattle depends on the estimates of the covariance components and genetic parameters for the traits included in the breeding program.…”

Section: Introductionmentioning

confidence: 99%

“…The implementation of RRM for genetic evaluations of dairy cattle depends on the estimates of the covariance components and genetic parameters for the traits included in the breeding program. The objective of this study is to evaluate and to compare the parametric logarithmic function proposed by Ali and Schaeffer (1987) and the exponential function proposed by Wilmink (1987) and a combination of the Legendre polynomial of second order and Wilmink function to adjust test day milk yields of first lactation Holstein cows using RRM.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Genetic parameters for test day milk yields of first lactation Holstein cows by random regression models

Melo

Packer²,

Costa³

et al. 2007

Animal

View full text Add to dashboard Cite

Covariance components for test day milk yield using 263 390 first lactation records of 32 448 Holstein cows were estimated using random regression animal models by restricted maximum likelihood. Three functions were used to adjust the lactation curve: the five-parameter logarithmic Ali and Schaeffer function (AS), the three-parameter exponential Wilmink function in its standard form (W) and in a modified form (W*), by reducing the range of covariate, and the combination of Legendre polynomial and W (LEG þ W). Heterogeneous residual variance (RV) for different classes (4 and 29) of days in milk was considered in adjusting the functions. Estimates of RV were quite similar, rating from 4.15 to 5.29 kg 2 . Heritability estimates for AS (0.29 to 0.42), LEG þ W (0.28 to 0.42) and W* (0.33 to 0.40) were similar, but heritability estimates used W (0.25 to 0.65) were highest than those estimated by the other functions, particularly at the end of lactation. Genetic correlations between milk yield on consecutive test days were close to unity, but decreased as the interval between test days increased. The AS function with homogeneous RV model had the best fit among those evaluated.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Genetic parameters for test day milk yields of first lactation Holstein cows by random regression models

Melo

Packer²,

Costa³

et al. 2007

Animal

View full text Add to dashboard Cite

show abstract

“…Among the non-linear parametric functions, Wilmink (Wilmink, 1987) and Ali and Schaeffer (ALI & SCHAEFFER, 1987) are the most important. According to BROTHERSTONE et al (2000), the functions of Ali and Schaeffer and Wilmink are more appropriate for adjusting the lactation curve of primiparous Holstein cows, compared to orthogonal Legendre polynomials with the same number of parameters.…”

Section: Objetivou-se Comparar As Funções De Wilmink E Ali E Schaeffementioning

confidence: 99%

Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians

Dornelles

Rorato

Gama³

et al. 2016

Cienc. Rural

View full text Add to dashboard Cite

show abstract

Complement component 3: characterization and association with mastitis resistance in Egyptian water buffalo and cattle

El-Halawany

Shawky

Al-Tohamy

et al. 2017

J Genet

View full text Add to dashboard Cite

Mastitis is an infectious disease of the mammary gland that leads to reduced milk production and change in milk composition. Complement component C3 plays a major role as a central molecule of the complement cascade involving in killing of microorganisms, either directly or in cooperation with phagocytic cells. C3 cDNA were isolated, from Egyptian buffalo and cattle, sequenced and characterized. The C3 cDNA sequences of buffalo and cattle consist of 5025 and 5019 bp, respectively. Buffalo and cattle C3 cDNAs share 99% of sequence identity with each other. The 4986 bp open reading frame in buffalo encodes a putative protein of 1661 amino acids-as in cattle-and includes all the functional domains. Further, analysis of the C3 cDNA sequences detected six novel single-nucleotide polymorphisms (SNPs) in buffalo and three novel SNPs in cattle. The association analysis of the detected SNPs with milk somatic cell score as an indicator of mastitis revealed that the most significant association in buffalo was found in the C>A substitution (ss: 1752816097) in exon 27, whereas in cattle it was in the C>T substitution (ss: 1752816085) in exon 12. Our findings provide preliminary information about the contribution of C3 polymorphisms to mastitis resistance in buffalo and cattle.

show abstract

Efficiency of selection for different cumulative milk, fat and protein yields in first lactation

Cited by 50 publications

References 17 publications

Genetic parameters for test day milk yields of first lactation Holstein cows by random regression models

Genetic parameters for test day milk yields of first lactation Holstein cows by random regression models

Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians

Complement component 3: characterization and association with mastitis resistance in Egyptian water buffalo and cattle

Contact Info

Product

Resources

About