scholarly journals Genetic Parameters of Milk Yield in Bulgarian Dairy Synthetic Population Sheep

Author(s):  
Jivko Krastanov ◽  
Nevyana Stancheva ◽  
Теоdora Angelova ◽  
Georgi Kalaydzhiev ◽  
Stayka Laleva ◽  
...  
2021 ◽  
Vol 37 (4) ◽  
pp. 263-277
Author(s):  
Georgi Kalaydzhiev

Dominating in recent years in Bulgaria are the sheep from the Bulgarian Dairy Synthetic Population (BDSP) and its crosses with other dairy breeds. This in turn leads to significant, scientifically based genetic and phenotypic diversity and different levels of productivity. The aim of the study is to research and characterize the genotypic parameters of the main productive and reproductive traits in sheep from the Bulgarian dairy synthetic population and its crosses with the breeds Lacaune and Assaf. The study includes a total of 3212 ewes reared in 15 farms, as from Bulgarian dairy synthetic population - 1114 ewes, BDSP crosses with Assaf - 1052 ewes and BDSP crosses with Lacaune - 1046 ewes, born in the period from 2014 to 2019 including. Studied trait were: milk yield for a standard 120-day period of I, II and III lactation, biological fertility of the 1st, 2nd and 3rd lambing and the trait - live weight of different age categories. The statistical model used was based on the model of animal /Animalmodel /, using the software product VCE and PEST (Groeneveld). Heritability in the main selection trait milk yield of the 1st, 2nd and 3rd lactation reaches from low to moderate and medium values. The lowest level of genetic diversity is in BDSP - h? varies from 0.125 to 0.157, in BDSP x Assaf from 0.131 to 0.202, and with the highest genetic diversity in the studied trait are ewes BDSP x Lacaune, respectively from 0.342 to 0.397. The rates of fertility in all three studied groups were from low to moderate h? - in BDSP from 0.133 to 0.156, in BDSP x Lacaune - from 0.040 to 0.112 and in BDSP x Assaf - from 0.100 to 0.122.


2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 305-307
Author(s):  
Andre C Araujo ◽  
Leonardo Gloria ◽  
Paulo Abreu ◽  
Fabyano Silva ◽  
Marcelo Rodrigues ◽  
...  

Abstract Hamiltonian Monte Carlo (HMC) is an algorithm of the Markov Chain Monte Carlo (MCMC) method that uses dynamics to propose samples that follow a target distribution. This algorithm enables more effective and consistent exploration of the probability interval and is more sensitive to correlated parameters. Therefore, Bayesian-HMC is a promising alternative to estimate individual parameters of complex functions such as nonlinear models, especially when using small datasets. Our objective was to estimate genetic parameters for milk traits defined based on nonlinear model parameters predicted using the Bayesian-HMC algorithm. A total of 64,680 milk yield test-day records from 2,624 first, second, and third lactations of Saanen and Alpine goats were used. First, the Wood model was fitted to the data. Second, lactation persistency (LP), peak time (PT), peak yield (PY), and total milk yield [estimated from zero to 50 (TMY50), 100(TMY100), 150(TMY150), 200(TMY200), 250(TMY250), and 300(TMY300) days-in-milk] were predicted for each animal and parity based on the output of the first step (the individual phenotypic parameters of the Wood model). Thereafter, these predicted phenotypes were used for estimating genetic parameters for each trait. In general, the heritability estimates across lactations ranged from 0.10 to 0.20 for LP, 0.04 to 0.07 for PT, 0.26 to 0.27 for PY, and 0.21 to 0.28 for TMY (considering the different intervals). Lower heritabilities were obtained for the nonlinear function parameters (A, b and l) compared to its predicted traits (except PT), especially for the first and second lactations (range: 0.09 to 0.18). Higher heritability estimates were obtained for the third lactation traits. To our best knowledge, this study is the first attempt to use the HMC algorithm to fit a nonlinear model in animal breeding. The two-step method proposed here allowed us to estimate genetic parameters for all traits evaluated.


2017 ◽  
Vol 149 ◽  
pp. 209-213 ◽  
Author(s):  
Mauricio Valencia-Posadas ◽  
Yessica Torrero-Garza ◽  
José Antonio Torres-Vázquez ◽  
César Andrés Ángel-Sahagún ◽  
Abner Josué Gutiérrez-Chávez ◽  
...  

2019 ◽  
Author(s):  
Nuzul Widyas ◽  
Nada Mahfudhoh ◽  
Subiakti ◽  
Sigit Prastowo

2019 ◽  
Vol 32 (2) ◽  
pp. 100-106 ◽  
Author(s):  
Farzane Shokri-Sangari ◽  
Hadi Atashi ◽  
Mohammad Dadpasand ◽  
Fateme Saghanejad

Background: Lactation persistency influences cow health and reproduction and has an impact on the feed costs of dairy farms. Objective: To estimate (co)variance components and genetic parameters of 100- and 305-d milk yield, and lactation persistency in Holstein cows in Iran. Methods: Records collected from January 2000 to December 2012 by the Animal Breeding Center of Iran (Karaj, Iran) were used. The following four measures of lactation persistency were used: P21: Ratio of milk yield in the second 100-d in milk (DIM) divided by that of the first 100-d. P31: Ratios of milk yield in the third100-d divided by that of the first 100-d. PW: The persistency measure derived from the incomplete gamma function. PJ: The difference between milk yield in day 60th and 280th of lactation. Results: The estimated heritability of lactation persistency for the three first parities (first, second, and third lactation) ranged from 0.01 to 0.06, 0.02 to 0.10, and 0.01 to 0.12, respectively. Genetic correlations among lactation persistency measures for the three first parities ranged from 0.77 to 0.98, 0.65 to 0.98, and 0.58 to 0.98, respectively; while corresponding values for genetic correlations among lactation persistency with 305-d milk production ranged from 0.18 to 0.63, 0.32 to 0.75, and 0.41 to 0.71, respectively. The estimated repeatability for lactation persistency measures ranged from 0.06 to 0.20. Conclusion: The moderate positive genetic correlation between lactation persistency and 305-d milk yield indicates that selection for increasing milk yield can slightly improve lactation persistency.Key words: dairy cattle, heritability, lactation curve, milk yield, persistency, repeatability. ResumenAntecedentes: La persistencia de la lactancia tiene una gran influencia en la salud, la reproducción y los costos de alimentación de las granjas lecheras. Objetivo: Estimar los componentes de (co)varianza y los parámetros genéticos de la producción de leche a 100 y 305 d, asi como la persistencia de la lactancia en vacas Holstein en Irán. Métodos: Se utilizaron registros recopilados entre enero de 2000 y diciembre de 2012 por el Centro de cría de animales de Irán (Karaj, Irán). Se utilizaron las siguientes cuatro medidas de persistencia de la lactancia: P21: Proporción de producción de leche en los segundos 100-d en leche (DIM) dividida por la de los primeros 100-d. P31: Proporcion de producción de leche en los terceros 100-d dividido por el de los primeros 100-d. PW: medida de persistencia derivada de la función gamma incompleta. PJ: diferencia entre el rendimiento de leche en el 60 y el 280 día de lactancia. Resultados: La heredabilidad estimada de la persistencia de la lactancia para los tres primeros partos (primera, segunda y tercera lactancia) varió de 0,01 a 0,06; 0,02 a 0,10; y 0,01 a 0,12, respectivamente. Las correlaciones genéticas entre las medidas de persistencia de lactancia para los tres primeros partos variaron de 0,77 a 0,98; 0,65 a 0,98; y 0,58 a 0,98, respectivamente; mientras que los valores correspondientes para las correlaciones genéticas entre la persistencia de la lactancia con la producción de leche a 305 d variaron de 0,18 a 0,63; 0,32 a 0,75; y 0,41 a 0,71, respectivamente. La repetibilidad estimada para las medidas de persistencia de la lactancia varió de 0,06 a 0,20. Conclusión: La correlación genética positiva moderada entre la persistencia de la lactancia y la producción de leche a 305-d indica que la selección para aumentar la producción de leche puede mejorar ligeramente la persistencia de la lactancia.Palabras clave: curva de lactancia, ganado lechero, heredabilidad, persistencia, producción de leche, repetibilidad. ResumoAntecedentes: A persistência da lactação tem grande influência nos custos de saúde, reprodução e alimentação em fazendas leiteiras. Objetivo: Estimar os componentes da variância (co)variância e os parâmetros genéticos da produção de leite de 100 e 305 d e a persistência da lactação em vacas Holandesas no Irã. Métodos: Os dados utilizados foram registros coletados de janeiro de 2000 a dezembro de 2012 pelo Centro de Criação de Animais do Irã (Karaj, Irã). As seguintes quatro medidas de persistência de lactação foram utilizadas: P21: Razão da produção de leite no segundo 100-d em leite (DIM) dividido pelo primeiro 100-d. P31: Razões da produção de leite na terceira 100d dividida pela da primeira 100-d. PW: A medida de persistência derivada da função gama incompleta. PJ: A diferença entre a produção de leite no 60º e 280º dia de lactação. Resultados: A hereditariedade estimada da persistência da lactação para as três primeiras paridades (primeira, segunda e terceira lactação) variou de 0,01 a 0,06; 0,02 a 0,10; e 0,01 a 0,12, respectivamente. As correlações genéticas entre as medidas de persistência da lactação para as três primeiras paridades variaram de 0,77 a 0,98; 0,65 a 0,98; e 0,58 a 0,98, respectivamente; enquanto os valores correspondentes para correlações genéticas entre a persistência da lactação com produção de leite de 305d variaram de 0,18 a 0,63; 0,32 a 0,75; e 0,41 a 0,71, respectivamente. A repetibilidade estimada para medidas de persistência de lactação variou de 0,06 a 0,20. Conclusão: A correlação genética positiva moderada entre a persistência da lactação e a produção de leite de 305d indicou que a seleção para aumentar a produção de leite melhoraria ligeiramente a persistência da lactação.Palavras-chave: curva de lactação, gado de leite, hereditariedade, persistência, produção de leite, repetibilidade.


1997 ◽  
Vol 65 (3) ◽  
pp. 353-360 ◽  
Author(s):  
J. E. Pryce ◽  
R. F. Veerkamp ◽  
R. Thompson ◽  
W. G. Hill ◽  
G. Simm

AbstractThe purpose of this study was to estimate genetic parameters for measures offertility and several health disorders in dairy cows. Data consisted of 33732 records, of which 9163 were on heifers, on 305-day milk yield, health disorders and inseminations. Measures offertility were calculated from calving and insemination dates and included calving interval, days to first service and conception to first service. Health disorders included milk fever, mastitis and lameness. Genetic and phenotypic (co)variances were estimated using restricted maximum likelihood. Heritability estimates for both health disorders and fertility traits were low, ranging from 0·003 to 0·080. All genetic correlations between 305-day milk yield and health and fertility traits, in cows and heifers together, were antagonistic implying that selection for milk yield may have caused a deterioration in health and fertility. The unfavourable correlation between milk yield and health and fertility traits, plus the economic importance of the latter, suggests that future breeding goals should be expanded to include some health disorders and fertility.


2011 ◽  
Vol 79 (1) ◽  
pp. 60-65 ◽  
Author(s):  
Rúsbel R Aspilcueta-Borquis ◽  
Fernando Baldi ◽  
Francisco R Araujo Neto ◽  
Lucia G Albuquerque ◽  
Milthon Muñoz-Berrocal ◽  
...  

The objective of this study was to apply factor analysis to describe lactation curves in dairy buffaloes in order to estimate the phenotypic and genetic association between common latent factors and cumulative milk yield. A total of 31 257 monthly test-day milk yield records from buffaloes belonging to herds located in the state of São Paulo were used to estimate two common latent factors, which were then analysed in a multi-trait animal model for estimating genetic parameters. Estimates of (co)variance components for the two common latent factors and cumulated 270-d milk yield were obtained by Bayesian inference using a multiple trait animal model. Contemporary group, number of milkings per day (two levels) and age of buffalo cow at calving (linear and quadratic) as covariate were included in the model as fixed effects. The additive genetic, permanent environmental and residual effects were included as random effects. The first common latent factor (F1) was associated with persistency of lactation and the second common latent factor (F2) with the level of production in early lactation. Heritability estimates for F1 and F2 were 0·12 and 0·07, respectively. Genetic correlation estimates between F1 and F2 with cumulative milk yield were positive and moderate (0·63 and 0·52). Multivariate statistics employing factor analysis allowed the extraction of two variables (latent factors) that described the shape of the lactation curve. It is expected that the response to selection to increase lactation persistency is higher than the response obtained from selecting animals to increase lactation peak. Selection for higher total milk yield would result in a favourable correlated response to increase the level of production in early lactation and the lactation persistency.


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