Persistence in milk, fat and protein production of primiparous Holstein cows by random regression models

Biassus, Igor de Oliveira; Cobuci, Jaime Araújo; Costa, C. N.; Rorato, Paulo Roberto Nogara; Neto, José Braccini; Cardoso, Leandro Lunardini

doi:10.1590/s1516-35982010001200009

Cited by 16 publications

(24 citation statements)

References 16 publications

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“…Heritability estimates for partial, total 305 days milk yield and different persistency measures are given in Table 4. Part2 and Part3 have the highest (0.307 ± 0.015) and lowest (0.232 ± 0.014) heritabilities for partial milk yield, respectively, and the heritability estimates for 305 days milk yield was 0.305 ± 0.005, which is similar to those obtained by Khorshidie et al, (2012), Cobuci et al, (2005) and Biassus et al, (2010). The level of milk yield has an important influence on persistency.…”

Section: Resultssupporting

confidence: 84%

“…Jakobsen et al, (2002) obtained values from 0.09 to 0.24 for persistency of milk yield while Cole and VanRaden (2006) reported heritabilities ranging from 0.10 to 0.11 for persistency of milk yield. Different heritabilities of persistency can be attributed to differences in the definition of the trait and differences in statistical methods used in the calculation of persistency (Biassus et al, 2010;Jakobsen et al, 2002). According to Jakobsen et al, (2002) a good persistency measure should have a high heritability and must be uncorrelated with 305 days milk yield because there is an antagonistic relationship between persistency and 305 days yield.…”

Section: Journal Of Agricultural Studiesmentioning

confidence: 99%

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Evaluation of Different Measures of Milk Yield Persistency in Iranian Holstein Dairy Cows

Torshizi¹,

Mashhadi²

2016

JAS

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Test-day lactation records of primiparous Holstein cows over an eleven-year period were evaluated for persistency and estimates of its heritability and correlation with other lactation traits computed. In this study, 435390 test day records of the first lactation Holstein cows that calved between 2001 and 2011 from 659 herds were analyzed using various procedures of SAS. Per1% (dividing total milk yield between 101-200 days by the yield of the first 100 days of lactation) measure was preferred in the selection of animals for milk yield persistency because of higher heritability (0.084 ± 0.009) and the lower phenotypic correlation with 305 days milk yield (0.424) compare to other persistency measures. The result showed that cows which calved during summer and autumn had slightly higher persistency in comparison to cows that calved in spring or winter. The persistency can be affected by the age at first calving, as cows that calved at a younger age had lower persistency.

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Section: Resultssupporting

confidence: 84%

Section: Journal Of Agricultural Studiesmentioning

confidence: 99%

Evaluation of Different Measures of Milk Yield Persistency in Iranian Holstein Dairy Cows

Torshizi¹,

Mashhadi²

2016

JAS

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“…For the persistency of F % and P %, h 2 estimates were low. Given that h 2 of persistency varied significantly depending on definition (Biassus et al, 2010), it could be stated that persistency's definition was not optimal for this trait as it was for MY and for P %. However, the SE obtained in this study showed that these estimates of h 2 differ from zero.…”

Section: Resultsmentioning

confidence: 99%

Linking first lactation survival to milk yield and components and lactation persistency in Tunisian Holstein cows

et al. 2019

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Genetic parameters were estimated for first lactation survival defined as a binary trait (alive or dead to second calving) and the curve shape traits of milk yield, fat and protein percentages using information from 25 981 primiparous Tunisian Holsteins. For each trait, shape curves (i.e. peak lactation, persistency), level of production adjusted to 305 days in milk (DIMs) for total milk yield (TMY), and average fat (TF %) and protein (TP %) percentages were defined. Variance components were estimated with a linear random regression model under three bivariate animal models. Production traits were modelled by fixed herd × test-day (TD) interaction effects, fixed classes of 25 DIMs × age of calving × season of calving interaction effects, fixed classes of pregnancy, random environment effects and random additive genetic effects. Survival was modelled by fixed herd × year of calving interaction effects and age of calving × season of calving interaction effects, random permanent environment effects, and random additive genetic effects. Heritability (hnormal2) estimates were 0.03 (±0.01) for survival and 0.23 (±0.01), 0.31 (±0.01) and 0.31 (±0.01) for TMY, TF % and TP %, respectively. Genetic correlations between survival and TMY, TF % and TP % were 0.26 (±0.08), -0.24 (±0.06) and -0.13 (±0.06), respectively. Genetic correlations between survival and persistency for fat and protein percentages were -0.35 (±0.09) and -0.19 (±0.09), respectively. Cows that had higher persistencies for fat and protein percentages were more likely not to survive.

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“…Costa et al (2008), Biassus et al (2011), and Cobuci et al (2011) studied the use of random regression models with Legendre polynomials, in order to determine the best order for genetic evaluation of Holstein cattle in Brazil, and to substitute the current 305-day lactation model. However, there are few studies on milk and its components, as fat and protein, in tropical countries as Brazil, using random regression models in the genetic evaluations of Holstein breed (Costa et al, 2008;Biassus et al, 2010). In general, the random regression models using Legendre polynomials of fourth, fifth and sixth orders have been indicated as a good option for conducting genetic evaluations of Holstein cattle; however, there are no comparisons between random regression and lactation models as for the advantages in the gain of reliability of breeding values from studies on Brazilian Holsteins (Costa et al, 2008;Biassus et al, 2010Biassus et al, , 2011.…”

Section: Introductionmentioning

confidence: 99%

Reliability of breeding values between random regression and 305-day lactation models

Padilha

Cobuci

Daltro

et al. 2016

Pesq. agropec. bras.

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-The objective of this work was to verify the gain in reliability of estimated breeding values (EBVs), when random regression models are applied instead of conventional 305-day lactation models, using fat and protein yield records of Brazilian Holstein cattle for future genetic evaluations. Data set contained 262,426 test-day fat and protein yield records, and 30,228 fat and protein lactation records at 305 days from first lactation. Single trait random regression models using Legendre polynomials and single trait lactation models were applied. Heritability for 305-day yield from lactation models was 0.24 (fat) and 0.17 (protein), and from random regression models was 0.20 (fat) and 0.21 (protein). Spearman correlations of EBVs, between lactation models and random regression models, for 305-day yield, ranged from 0.86 to 0.97 and 0.86 to 0.98 (bulls), and from 0.80 to 0.89 and 0.81 to 0.86 (cows), for fat and protein, respectively. Average increase in reliability of EBVs for 305-day yield of bulls ranged from 2 to 16% (fat) and from 4 to 26% (protein), and average reliability of cows ranged from 24 to 38% (fat and protein), which is higher than in the lactation models. Random regression models using Legendre polynomials will improve genetic evaluations of Brazilian Holstein cattle due to the reliability increase of EBVs, in comparison with 305-day lactation models.Index terms: breeding value, correlation, Legendre polynomials, reliability. Confiabilidade de valores genéticos entre modelos de regressão aleatória e de lactação aos 305 diasResumo -O objetivo deste trabalho foi verificar o ganho em confiabilidade dos valores genéticos estimados (VGE), quando os modelos de regressão aleatória são aplicados em lugar dos modelos convencionais de lactação até os 305 dias, tendo-se utilizado registros de produção de gordura e proteína de bovinos da raça Holandesa no Brasil, para futuras avaliações genéticas. O conjunto de dados continha 262.426 registros de produção de gordura e proteína no dia do controle e 30.228 registros de produção acumulada de gordura e proteína até os 305 dias de lactação. Aplicaram-se modelos de regressão aleatória unicaracterística, com os polinômios de Legendre, e modelos unicaracterística de lactação aos 305 dias. A herdabilidade estimada para as produções até os 305 dias pelos modelos de lactação foi 0,24 (gordura) e 0,17 (proteína), e, pelos modelos de regressão aleatória, foi 0,20 (gordura) e 0,21 (proteína). Correlações de Spearman dos VGEs entre os modelos de lactação e de regressão aleatória, para a produção aos 305 dias, variaram de 0,86 a 0,97 e 0,86 a 0,98 (touros) e de 0,80 a 0,89 e 0,81 a 0,86 (vacas), quanto à gordura e à proteína, respectivamente. O aumento médio em confiabilidade dos VGEs para a produção aos 305 dias variou de 2 a 16% (gordura) e de 4 a 26% (proteína), em touros, e variou de 24 a 38% (gordura e proteína) em vacas, o que é superior àquela obtida pelos modelos de lactação. Os modelos de regressão aleatória com uso dos polinômios de Legendre melhorarão a av...

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Persistence in milk, fat and protein production of primiparous Holstein cows by random regression models

Cited by 16 publications

References 16 publications

Evaluation of Different Measures of Milk Yield Persistency in Iranian Holstein Dairy Cows

Evaluation of Different Measures of Milk Yield Persistency in Iranian Holstein Dairy Cows

Linking first lactation survival to milk yield and components and lactation persistency in Tunisian Holstein cows

Reliability of breeding values between random regression and 305-day lactation models

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