Genetic Analysis of First Lactation Monthly Test Day Milk Yields, Peak Yield and 305 Days Milk Yield in Murrah Buffaloes

2020 ◽  
Author(s):  
Ekta Rana ◽  
Ashok Kumar Gupta ◽  
Avtar Singh ◽  
Atish Kumar Chakravarty ◽  
Saleem Yousuf ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Milk Yield ◽  
Genetic Parameters ◽  
Correlation Method ◽  
Phenotypic Correlation ◽  
Murrah Buffaloes ◽  
National Dairy Research Institute ◽  
Genetic And Phenotypic Correlations ◽  
Breed Improvement ◽  
Selection Of

Background: The estimates of genetic parameters are useful in determining the appropriate method of selection that could further be implemented in the breed improvement programmes. The present study was, therefore, conducted to estimate the genetic parameters (heritability, genetic and phenotypic correlations) for monthly test day (TD) milk yields, peak yield (PY) and first lactation 305 days milk yield (FL305DMY) in Murrah buffaloes.Methods: Paternal half-sib correlation method was carried out by least-squares maximum likelihood programme to estimate genetic parameters of first lactation 4,209 and 408 records of monthly test day milk yield and peak yield, respectively, of 408 Murrah buffaloes (sired by 62 bulls) calved in between 1993 and 2017 at ICAR-National Dairy Research Institute, Karnal.Result: Heritability of FL305DMY and peak yield was estimated as 0.35±0.17 and 0.33±0.16, respectively. Heritability estimates for mid-lactation monthly test day milk yields were found to be moderate. Genetic correlation of monthly test day milk yields with FL305DMY was positive and highly significant for TD-4 to TD-9 and TD-11. Peak yield showed high genetic and phenotypic association with FL305DMY. High genetic and phenotypic correlation among monthly test day milk yields, peak yield and FL305DMY suggested that TD-4 to TD-9 and TD-11 test day milk yields and peak yield could be used for the selection of elite animals.

scholarly journals Realized Sampling Variances of Estimates of Genetic Parameters and the Difference Between Genetic and Phenotypic Correlations

Genetics ◽  
1996 ◽  
Vol 143 (3) ◽  
pp. 1409-1416 ◽  
Author(s):  
Kenneth R Koots ◽  
John P Gibson
Keyword(s):  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Phenotypic Correlation ◽  
Parameter Estimates ◽  
Sampling Variance ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Heritability Estimates

Abstract A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.

scholarly journals Genetic parameters of production and reproduetive traits in on a farm tested Danish Large White and Landrace swine in Greece

2000 ◽  
Vol 43 (3) ◽  
pp. 287-298
Author(s):  
J. Bizelis ◽  
A. Kominakis ◽  
E. Rogdakis ◽  
F. Georgadopoulou
Keyword(s):  
Maximum Likelihood ◽  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Production Traits ◽  
Likelihood Methods ◽  
Large White ◽  
Reproduction Traits ◽  
Maximum Likelihood Methods ◽  
Genetic And Phenotypic Correlations

Abstract. Production and reproduetive traits in Danish Landrace (LD) and Large White (LW) swine were analysed by restricted maximum likelihood methods to obtain heritabilities as well as genetic and phenotypic correlations. Production traits were: age, backfat thickness (BT), muscle depth (MD) and the ratio BT/MD, adjusted to Standard bodyweight of 85 kg. Reproduction traits were: number of pigs born (NB) and number of pigs weaned (NW) per sow and parity. Heritabilities for age, BT, MD and BT/MD were 0.60, 0.44, 0.51 and 0.42 for LD and 0.36, 0.44, 0.37 and 0.45 for LW, respectively. Genetic correlations between age and BT were −0.22 in LD and – 0.44 in LW. The genetic correlation between age and MD was close to zero in both breeds. Genetic correlation between BT and MD were −0.36 and −0.25 in LD and LW, respectively. Heritabilities for NB were 0.25 in LD and 0.13 in LW while heritabilities for NW were close to zero in both breeds. Genetic correlation between NB and NW was 0.46 and 0.70 in LD and LW, respectively.

scholarly journals Genetic Parameters for First Lactation and Lifetime Traits of Nili-Ravi Buffaloes

2021 ◽  
Vol 8 ◽  
Author(s):  
Pooja Tamboli ◽  
Anurag Bharadwaj ◽  
Amit Chaurasiya ◽  
Yogesh Chandrakant Bangar ◽  
Andonissamy Jerome
Keyword(s):  
Genetic Correlation ◽  
Milk Yield ◽  
Phenotypic Correlation ◽  
Productive Life ◽  
Lactation Length ◽  
Service Period ◽  
Reproduction Traits ◽  
Genetic And Phenotypic Correlations ◽  
Breeding Efficiency ◽  
Estimation Of Variance

The data on first lactation and lifetime performance records of 501 Nili-Ravi were collected for a period from 1983 to 2017 (35 years) maintained at ICAR-Central Institute for Research on Buffaloes, Sub-Campus, Nabha, Punjab. The data were analyzed to calculate heritability, genetic and phenotypic correlation for first lactation traits, viz., Age at First Calving (AFC), First Lactation Total Milk Yield (FLTMY), First Lactation Standard (305 days or less) Milk Yield (FLSMY), First Peak Milk Yield (FPY), First Lactation Length (FLL), First Dry Period (FDP), First Service Period (FSP) and First Calving Interval (FCI), Herd Life (HL), Productive Life (PL), Productive Days (PD), Unproductive Days (UD), Breeding Efficiency (BE), Total Lifetime Milk Yield (Total LTMY), Standard Lifetime Milk Yield (Standard LTMY), Milk Yield Per Day of Productive Life (MY/PL), Milk Yield Per Day of Productive Days (MY/PD), and Milk Yield Per Day of Herd Life (MY/HL). For estimation of variance component and heritability separately for each trait, the uni-trait animal model was equipped, whereas to estimate genetic and phenotypic correlations between traits, bi-trait animal models were fitted. The estimates of heritability for production and reproduction traits of Nili-Ravi were medium, i.e., 0.365 ± 0.087, 0.353 ± 0.071, 0.318 ± 0.082, 0.354 ± 0.076, and 0.362 ± 0.086 for FLSMY, FDP, FSP, FCI, and AFC, respectively. The estimates of heritability were low, i.e., 0.062 ± 0.088, 0.123 ± 0.090, 0.158 ± 0.090, 0.155 ± 0.091, and 0.129 ± 0.091 for HL, PL, PD, Total LTMY, and Standard LTMY and high, i.e., 0.669 ± 0.096 for BE. Genetic correlation for FLTMY was high with FLL (0.710 ± 0.103), and genetic correlation of FLTMY was high and positive with HL, Total LTMY, MY/PL, and MY/PD while low and positive with PL. Genetic correlation of AFC was low and negative with PL, PD, UD, BE, Total LTMY, Standard LTMY, MY/PL, and MY/PD and negative with MY/HL. Significant positive phenotypic association of FPY was seen with FLTMY, FLSMY, FLL, AFC, HL, Total LTMY, and Standard LTMY. Higher heritability of first lactation traits especially FPY suggests sufficient additive genetic variability, which can be exploited under selection and breeding policy in order to improve overall performance of Nili-Ravi buffaloes.

scholarly journals Repeatability and Phenotypic Correlation Among Semen Quality Traits in Holstein Bulls

2018 ◽  
Vol 42 (4) ◽  
Author(s):  
Argi Argiris ◽  
Siswanto Imam Santoso ◽  
Yon Supri Ondho ◽  
Edy Kurnianto
Keyword(s):  
Artificial Insemination ◽  
Semen Quality ◽  
Intraclass Correlation ◽  
Correlation Method ◽  
Phenotypic Correlation ◽  
Quality Traits ◽  
Frozen Semen ◽  
Holstein Bulls ◽  
Fresh Semen ◽  
Selection Of

The purpose of this research was to analysis the value of repeatability and correlation among the traits affecting the production of frozen semen from Holstein’s bull in Indonesia. Repeatability and correlation were calculated based on the data of frozen semen production of 15.699 records from 44 Holstein bulls at Singosari Artificial Insemination Center (SAIC) and 8.935 records from 39 Holstein bulls at Lembang Artificial Insemination Center (LAIC). Repeatability for volume, motility, fresh semen concentration and frozen semen production was evaluated by intraclass correlation method. The repeatability values of LAIC for volume, motility, fresh semen concentration and frozen semen production were 0.60; 0.54; 0.37 and 0.47. The repeatability values of SAIC for volume, motility, fresh semen concentration and frozen semen production were 0.54; 0.30; 0.43 and 0.29. The linear correlation value between volume, motility and fresh semen concentration with the amount of semen produced per collections were 0.41, 0.36, and 0.58. Concentration was the most factors influencing the number of frozen semen produced. The effectiveness of the selection of Holstein's frozen semen producing could be determined by the value of repeatability and the phenotypic correlation among semen quality traits such as volume, motility, concentration and frozen semen production.

scholarly journals Estimation of genetic parameters of weekly test-day milk yields and first lactation 305-day milk yield in Murrah buffaloes

2014 ◽  
Vol 7 (12) ◽  
pp. 1094-1098 ◽  
Author(s):  
Saroj Kumar Sahoo ◽  
Avtar Singh ◽  
A. K. Gupta ◽  
A. K. Chakravarty ◽  
Manvendra Singh ◽  
...  
Keyword(s):  
Milk Yield ◽  
Genetic Parameters ◽  
Murrah Buffaloes ◽  
Estimation Of Genetic Parameters

Genetic parameters among lactational performance traits in Murrah buffaloes

2015 ◽  
Author(s):  
A. Godara ◽  
D. Singh ◽  
S. S. Dhaka
Keyword(s):  
Genetic Correlation ◽  
Milk Yield ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Research Centre ◽  
Murrah Buffaloes ◽  
Performance Traits ◽  
Lactational Performance ◽  
Almost All ◽  
Animal Sciences

The data pertinent to lactational performance traits on Murrah buffaloes calved during period 1987 to 2002, progeny of 52 sires maintained at Buffalo Research Centre, LLR University of Veterinary and Animal Sciences, Hisar were considered. The estimates of heritability were obtained low to moderate for almost all lactational performance traits. All the first lactation traits viz., AC1, SP, CI, MY, LL, PY, DAPY and MY/LL had moderate to high positive genetic correlations among themselves except PY with CI and DAPY with AC1, which is negative. Age at calving (AC2) had moderate positive genetic correlation with second lactational performance traits like SP, MY, LL, PY, MY/LL and MY/CI and had negative correlations with DAPY and DP. Moreover, third lactational traits like milk yield, LL, PY, DAPY, MY/LL and MY/CI had high positive genetic correlations among themselves. However, age at calving during fourth lactation had positive genetic correlations with all the traits except CI, DAPY and DP which had negative genetic correlations with it. It is inferred that information on sip performance and other relatives coupled with better husbandry practices would be required to bring desirable improvement in these lactational performance traits.

SIMULTANEOUS ESTIMATION OF GENETIC PARAMETERS OF LIFETIME REPRODUCTIVE TRAITS IN MICE

1988 ◽  
Vol 68 (4) ◽  
pp. 1291-1295 ◽  
Author(s):  
J. NAGAI ◽  
C. Y. LIN ◽  
A. J. McALLISTER
Keyword(s):  
Genetic Parameters ◽  
Mixed Model ◽  
Reproductive Traits ◽  
Bivariate Analysis ◽  
Simultaneous Estimation ◽  
Mixed Model Analysis ◽  
Reproductive Life ◽  
Genetic And Phenotypic Correlations ◽  
Estimation Of Genetic Parameters ◽  
Selection Of

Heritabilities and correlations between the length of reproductive life and number of parturitions during lifetime in mice were estimated from bivariate full-sib mixed-model analysis. Heritability estimates from sire components were low (0.01) for the two traits and those from dam components were slightly higher (0.06 and 0.05). Estimates of genetic and phenotypic correlations ranged from 0.89 to 0.99. It was concluded that the two traits are virtually the same trait biologically. Implication of these results for selection of lifetime production in mice and dairy cattle is discussed. Key words: Genetic parameters, reproductive trait, bivariate analysis

scholarly journals Estimation of genetic parameters for milk yield in Murrah buffaloes by Bayesian inference

2010 ◽  
Vol 93 (2) ◽  
pp. 784-791 ◽  
Author(s):  
F.C. Breda ◽  
L.G. Albuquerque ◽  
R.F. Euclydes ◽  
A.B. Bignardi ◽  
F. Baldi ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Milk Yield ◽  
Genetic Parameters ◽  
Murrah Buffaloes ◽  
Estimation Of Genetic Parameters

scholarly journals Correlation between the breeding indicators of black and white cows in Bulgaria

2004 ◽  
Vol 20 (1-2) ◽  
pp. 17-21
Author(s):  
V. Gaidarsca ◽  
N. Rusev ◽  
Y. Popova
Keyword(s):  
Protein Content ◽  
Milk Yield ◽  
Fat Content ◽  
Primary Objective ◽  
Phenotypic Correlation ◽  
Milk Productivity ◽  
Black And White ◽  
Butter Fat ◽  
Genetic And Phenotypic Correlations

The objective of this study was to estimate coefficients of variability heritability, genetic and phenotypic correlations between indicators of milk productivity in relation to milk yield and fat content, butter fat and protein content in milk. The foremost quality of 21st century Holstein cow is efficiency (Beaulieu, 1993). She must continue to increase both life production and production per year, preserving the quality. Due to the use of optimum breeding programs the rates of the genetic improvement of milk production have increased nearly twice in the 1990 as compared to those in the 1970 according to Aleksiev et.al. (1991), Vankov (1978), Vankov et.al. (1982) and Kennedy,(1991). A primary objective of this study was to determine coefficients of variability, heritability, genetic and phenotypic correlation between indicators of milk productivity in relation to milk yield and fat content, butter fat and protein content in milk. Heritability, genetic and phenotype correlation of milk productivity and protein content in milk of Bulgarian Black and White cows White were estimated, using the linear statistical model (Harvey 1977).

Prediction of First Lactation 305-day Milk Yield Based on Bimonthly Test Day Milk Yield Records in Murrah Buffaloes

2020 ◽  
Author(s):  
Ekta Rana ◽  
Ashok Kumar Gupta ◽  
Avtar Singh ◽  
Anand Prakash Ruhil ◽  
Ravinder Malhotra ◽  
...  
Keyword(s):  
Milk Yield ◽  
Absolute Error ◽  
Ratio Method ◽  
Average Error ◽  
Interval Method ◽  
Machine Learning Methods ◽  
Murrah Buffaloes ◽  
Artificial Neural Network Ann ◽  
Error Percentage ◽  
Selection Of

The present study was conducted on 2100 first lactation bimonthly test day milk yield (BTDY) records of 350 Murrah buffaloes calved in between 1993 and 2017 at ICAR-NDRI, Karnal. A total of 6 BTDY records were taken from each animal at an interval of 60 days, from 6th day to 305th day of lactation. The prediction of First Lactation 305-Day Milk Yield (FL305DMY) was done by utilizing five conventional and machine learning methods viz., Centering Date Method (CDM), Test Interval Method (TIM), Ratio Method (RM), Multiple Linear Regression (MLR) and Artificial Neural Network (ANN). Error in prediction was estimated by absolute error, percentage absolute error, average error, percentage average error, Root Mean Square Error (RMSE) and percentage RMSE. MLR was found to be the best method with the least error in prediction (5.71% RMSE), followed by ANN (5.77% RMSE). The accuracy (R2) of MLR equation including all 6 BTDY records was 91.86%. The best MLR equation for an early prediction of FL305DMY included 3 BTDY records viz., BTDY-2 (65th day), BTDY-3 (125th day) and BTDY-4 (185th day) with 85.29% R2. The study compared the conventional and computational methods for prediction of first lactation milk yield which could be used for early selection of the animals.

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