scholarly journals Estimation of genomic breeding values for milk yield in UK dairy goats

2015 ◽  
Vol 98 (11) ◽  
pp. 8201-8208 ◽  
Author(s):  
S. Mucha ◽  
R. Mrode ◽  
I. MacLaren-Lee ◽  
M. Coffey ◽  
J. Conington
Keyword(s):  
Milk Yield ◽  
Dairy Goats ◽  
Genomic Breeding ◽  
Breeding Values

scholarly journals Estimation and comparison of conventional and genomic breeding values in Holstein cattle of Antioquia, Colombia

2015 ◽  
pp. 4739-4753 ◽  
Author(s):  
Juan Zambrano A ◽  
Juan Rincón F ◽  
Albeiro López H ◽  
Julián Echeverri Z
Keyword(s):  
Linear Regression ◽  
Milk Yield ◽  
Conventional Method ◽  
Regression Coefficient ◽  
Rank Correlation ◽  
Breeding Value ◽  
Fat Percentage ◽  
Linear Regression Coefficient ◽  
Genomic Breeding ◽  
Breeding Values

ABSTRACT Objetive. To estimate and compare breeding values (EBV) using the conventional method (BLUP) and genomic breeding values (MEBV and GEBV) estimated through bayes C method for milk yield and milk quality traits in dairy cattle in Antioquia, Colombia. Materials and methods. Two methods were used to estimate breeding values: BLUP to estimate conventional breeding value (EBV) and bayes C to estimate genomic values (MEBV and GEBV). The traits evaluated were: milk yield (PL), protein percentage (PPRO), fat percentage (PGRA) and score somatic cell (SCS). The methods (BLUP and bayes C) were compared using Person correlation (rp), Spearman rank correlation (rs) and linear regression coefficient (b). Results. The Pearson and Spearman correlations among EBVs and genomic values (MEBV and GEBV) (rpMEBV;EBV and rsGEBV;EBV) were greater than 0.93 and the linear regression coefficients of EBVs on genomic values (MEBV and GEBV) (bMEBV;EBV, and bGEBV;EBV) ranged between 0.954 and 1.051 in all traits evaluated. Conclusions. The predictions of genomic values (MEBV and GEBV), using bayes C method were consistent with the predictions of the EBVs estimate through the conventional method (BLUP) in conditions of high Colombian tropic, allowing to obtain high associations between the breeding values.

Random regression animal models for genetic evaluation of test-day milk yield and milking duration in Saudi dairy goats

2018 ◽  
Author(s):  
A.A. Amin
Keyword(s):  
Milk Yield ◽  
Genetic Correlations ◽  
Random Regression ◽  
Dairy Goats ◽  
Data Set ◽  
Breeding Values ◽  
Sample Test ◽  
Early Production ◽  
Daily Milk Yield ◽  
Daily Milk

Random regression animal model was applied for analyzing the relationships between daily milk yield (MK) and milking duration (DR) in dairy goats comparing with reviewed estimates in dairy cows. The current analyzed data involved 17345 sample test-day records from multiparous Saudi dairy goats. A cubic random regression was applied for representing additive genetic variances in all studied traits across all different days in milk (12 groups). Based on multi-lactation random regression data-set analysis, the role of inheritance was greatest during the later stages of lactation. Heritability estimates of daily milk yield (h2MK) ranged from 0.15 to 0.54. While estimates of heritability for milking duration (h2DR) were very low during the first 60 days of lactation, being not more than 0.04. During the 2nd half of lactation the estimates of h2DR ranged from 0.35 to 0.39. Results of genetic variations for lactation records during early production life showed that highest milk harvest with intermediate milking rate could be achieved. Estimates of expected breeding values for milk yield and milking duration increased in different rates with progressing days in milk groups. These results indicated that individual selection results would be favorably achieved during the late part of lactation. Additive genetic correlations between measures of all traits at different lactation months continuously decreased as the interval between test days increased. Additive genetic correlations between milking duration and milk yield were positive and considerably high. Correlations between expected breeding values of both traits ranged from 0.41 to 0.83 (mean = 0.69) across different lactation months. More details on estimates of breeding values, estimates of permanent environmental and additive genetic correlations for all traits were tabulated.

43 Single and Multiple-breed Genomic Predictions for Conformation Traits of Canadian Dairy Goats

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 27-28
Author(s):  
Erin Massender ◽  
Luiz F Brito ◽  
Laurence Maignel ◽  
Hinayah R Oliveira ◽  
Mohsen Jafarikia ◽  
...  
Keyword(s):  
Single Step ◽  
Dairy Goats ◽  
Genomic Breeding ◽  
Breeding Values ◽  
Suspensory Ligament ◽  
Full Dataset ◽  
Expected Gain ◽  
Breed Difference ◽  
Estimated Breeding Values ◽  
Theoretical Accuracy

Abstract The use of multiple-breed models can increase the accuracy of estimated breeding values (EBV) when few phenotypes are available for a trait. However, pooling breeds is not always beneficial for genomic evaluations due to the low consistency of gametic phase between individual breeds. The objective of this study was to compare the expected gain in accuracy of single-step genomic breeding values (GEBV) for conformation traits of Canadian Alpine and Saanen goats predicted using single and multiple-breed models. The traits considered were body capacity, dairy character, feet and legs, fore udder, general appearance, rear udder, suspensory ligament, and teats, all recorded by trained classifiers, using a 1 to 9 scale. The full datasets included a total of 7,500 phenotypes for each trait (5,158 Alpine and 2,342 Saanen) and 1,707 50K genotypes (833 Alpine, 874 Saanen). Standard errors of prediction (SEP) were obtained for EBV and GEBV predicted using single-trait animal models on full or validation datasets. Breed difference was accounted for as a fixed effect in the multiple-breed models. Average theoretical accuracies were calculated from the SEP. For Saanen, with fewer records, expected accuracies of EBV and GEBV for the validation animals (selection candidates) were consistently higher for the multiple-breed models. Trait specific gains in theoretical accuracy of GEBV relative to EBV for the selection candidates ranged from 30 to 48% for Alpine and 41 to 61% for Saanen. Averaged across all traits, GEBV predicted from the full dataset were 32 to 38% more accurate than EBV for genotyped animals and the largest gains were found for does without conformation records (49 to 55%) and bucks without daughter records (56 to 82%). Overall, the implementation of genomic selection would substantially increase selection accuracy for young breeding candidates and, consequently, the rate of genetic improvement for conformation traits in Canadian dairy goats.

scholarly journals Effects of condensed tannin-amended cassava silage blend diets on feeding behavior, digestibility, nitrogen balance, milk yield and milk composition in dairy goats

animal ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 100015
Author(s):  
T.V.C. Nascimento ◽  
R.L. Oliveira ◽  
D.R. Menezes ◽  
A.R.F. de Lucena ◽  
M.A.Á. Queiroz ◽  
...  
Keyword(s):  
Feeding Behavior ◽  
Milk Yield ◽  
Nitrogen Balance ◽  
Condensed Tannin ◽  
Milk Composition ◽  
Dairy Goats

scholarly journals GPS Coordinates for Modelling Correlated Herd Effects in Genomic Prediction Models Applied to Hanwoo Beef Cattle

Animals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 2050
Author(s):  
Beatriz Castro Dias Cuyabano ◽  
Gabriel Rovere ◽  
Dajeong Lim ◽  
Tae Hun Kim ◽  
Hak Kyo Lee ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Genomic Prediction ◽  
Prediction Models ◽  
Phenotypic Expression ◽  
Genetic Evaluation ◽  
Genomic Breeding ◽  
Breeding Values ◽  
Korean Cattle ◽  
Evaluation Programs ◽  
The Impact

It is widely known that the environment influences phenotypic expression and that its effects must be accounted for in genetic evaluation programs. The most used method to account for environmental effects is to add herd and contemporary group to the model. Although generally informative, the herd effect treats different farms as independent units. However, if two farms are located physically close to each other, they potentially share correlated environmental factors. We introduce a method to model herd effects that uses the physical distances between farms based on the Global Positioning System (GPS) coordinates as a proxy for the correlation matrix of these effects that aims to account for similarities and differences between farms due to environmental factors. A population of Hanwoo Korean cattle was used to evaluate the impact of modelling herd effects as correlated, in comparison to assuming the farms as completely independent units, on the variance components and genomic prediction. The main result was an increase in the reliabilities of the predicted genomic breeding values compared to reliabilities obtained with traditional models (across four traits evaluated, reliabilities of prediction presented increases that ranged from 0.05 ± 0.01 to 0.33 ± 0.03), suggesting that these models may overestimate heritabilities. Although little to no significant gain was obtained in phenotypic prediction, the increased reliability of the predicted genomic breeding values is of practical relevance for genetic evaluation programs.

scholarly journals Oxidative status in dairy goats: periparturient variation and changes in subclinical hyperketonemia and hypocalcemia

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Yan Huang ◽  
Jing Wen ◽  
Yezi Kong ◽  
Chenxu Zhao ◽  
Siqi Liu ◽  
...  
Keyword(s):  
Milk Yield ◽  
Redox Homeostasis ◽  
Redox Status ◽  
Oxidative Status ◽  
The Body ◽  
Production Performance ◽  
Lactation Period ◽  
Dairy Goats ◽  
Periparturient Period ◽  
Total Antioxidant

Abstract Background A better comprehension of the redox status during the periparturient period may facilitate the development of management and nutritional solutions to prevent subclinical hyperketonemia (SCHK) and subclinical hypocalcemia (SCHC) in dairy goats. We aimed to evaluate the variation in the redox status of dairy goats with SCHK and SCHC during their periparturient periods. Guanzhong dairy goats (n = 30) were assigned to SCHK (n = 10), SCHC (n = 10), and healthy (HEAL, n = 10) groups based on their blood β-hydroxybutyrate (BHBA) and calcium (Ca) concentrations. Blood were withdrawn from goats every week from 3 weeks before the expected parturition date to 3 weeks post-kidding. On the same day, the body condition scores (BCS) were evaluated, and the milk yield was recorded for each goat. The metabolic profile parameters and the indicators of oxidative status were determined by using the standard biochemical techniques. Results In comparison with the HEAL goats, SCHK and SCHC goats presented with a more dramatic decline of BCS post-kidding and a significant decrease in the milk yield at 2- and 3-weeks postpartum, ignoring the obvious increase at 1-week postpartum. The levels of non-esterified fatty acids (NEFA) peaked at parturition, exhibiting significantly higher levels from 1-week prepartum to the parturition day in the SCHK and SCHC groups. The malondialdehyde (MDA) concentration was increased in the SCHK goats from 1-week antepartum until 3-weeks postpartum, with its concentration being significantly higher in the SCHC goats at parturition. The hydrogen peroxide (H2O2) concentration was significantly lower in the SCHK and SCHC goats from 2-weeks antepartum to 1-week post-kidding. The total antioxidant capacity (T-AOC) and the superoxide dismutase (SOD) level were decreased at 1-week antepartum in the SCHK and SCHC goats, respectively. The glutathione peroxidase (GSH-Px) level was increased in the SCHK and SCHC goats during the early lactation period. Conclusions The SCHK and SCHC goats exerted more efforts to maintain their redox homeostasis and to ensure the production performance than the HEAL goats during their periparturient period, probably owing to more intense fat mobilization and lipid peroxidation in the former.

Reasons for keeping dairy goats in Tanzania, and possible goals for a sustainable breeding program

2017 ◽  
Vol 57 (2) ◽  
pp. 338 ◽  
Author(s):  
Z. C. Nziku ◽  
G. C. Kifaro ◽  
L. O. Eik ◽  
T. Steine ◽  
T. Ådnøy
Keyword(s):  
Milk Yield ◽  
Production Systems ◽  
Holistic Approach ◽  
Breeding Program ◽  
Dairy Goat ◽  
Dairy Goats ◽  
Quantitative And Qualitative Research ◽  
Animal Identification ◽  
Breeding Goals ◽  
And Performance

This research aimed at describing reasons for keeping dairy goats in Tanzania, and possible goals for a sustainable breeding program. Three districts, each representing a unique dairy goat breed population, were selected for the study. The Saanen, Toggenburg and Norwegian were the main dairy goat breeds in Arumeru, Babati, and Mvomero districts, respectively. A total of 125 dairy goat farmers were interviewed. A holistic approach of both quantitative and qualitative research methods was used to study the perceptions of farmers. More milk yield, sale of breeding stock and manure were the highest ranked reasons for keeping dairy goats. The reasons were coherent to the production systems. The three most preferred traits for improvement were milk yield, adaptability and twinning ability. These preferences were absolutely important in the context of the referred production system. Selection of replacement stock, animal identification and performance recording were the main challenges emphasised by farmers. The present study views these challenges as a result of knowledge gaps in animal breeding that require solutions. Based on result findings it is suggested that the milk yield and survival traits should be the primary dairy goat breeding goals. Generally, there are possibilities for developing sustainable dairy goat breeding programs in the surveyed areas given relevant breeding goals are incorporated. The design of simple and manageable dairy goat breeding schemes is necessary.

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