Breeding objectives for pasture‐fed Uruguayan beef cattle

Urioste, J. I.; Ponzoni, R. W.; Aguirrezabala, M.; Rovere, G.; Saavedra, D.

doi:10.1111/j.1439-0388.1998.tb00357.x

Cited by 21 publications

(17 citation statements)

References 15 publications

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“…These estimates are similar to the repeatability of 0.61 and heritability of 0.36 for cow weight at weaning reported by Suarez & Crook (2007), their study being based on approximately 25000 weight records for Simmental (of which the current data comprised a subset). It is also similar to the results obtained by Urioste et al (1998) in pasture-fed Uruguayan beef cattle as well as those of Nephawe (2004) in Bonsmara cattle using random regression models. The estimates are, however, lower than those Mwansa et al (2002) in Hereford cows and Nephawe et al (2004) in Hereford Angus cows.…”

Section: Figure 1 the Relationship Between Cow Age Class (In Years) Asupporting

confidence: 77%

Genetic parameters for cow weight at calving and at calf weaning in South African Simmental cattle (Short communication)

Crook¹,

Neser²,

Bradfield³

2010

SA J. An. Sci.

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A study was conducted to compare mature cow weight in the South African Simmental population when defined as the weight of the cow at calving or the weight of the cow at weaning of the calf. Data included in the analysis were 14458 records for cow weight at calving (CWT-C) representing 6534 cows and 18871 records for cow weight at weaning (CWT-W) representing 8395 cows. All cows were born between 1968 and 1996, while all calves were born between 1977 and 1998. The following effects had a significant influence on the traits and were included in the genetic analysis: Cow age in years fitted as a covariate term (linear and quadratic) and contemporary group fitted as a fixed effect. Contemporary group was defined as the unique combination of herd, birth year of calf, month of weighing, breeder-defined management group code for the calf and supplementary feeding code for the cow (for CWT-W). All analyses were done using ASREML, first fitting uni-trait and then bi-variate animal models that made provision for up to four weights per cow. The estimated genetic correlation obtained between the two cow weight traits was 0.95 ± 0.03, with a residual correlation of 0.61 ± 0.02. The heritability estimates for CWT-C and CWT-W from this analysis were 0.29 ± 0.04 and 0.37 ± 0.04, respectively. From a breeding perspective, these results confirm that little benefit is to be gained from weighing cows at calving if cows are to be weighed at weaning. If cow weights are to be recorded for an indication of cow maintenance costs, then weight at weaning is the more reliable and practical measure to record.

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Section: Figure 1 the Relationship Between Cow Age Class (In Years) Asupporting

confidence: 77%

Genetic parameters for cow weight at calving and at calf weaning in South African Simmental cattle (Short communication)

Crook¹,

Neser²,

Bradfield³

2010

SA J. An. Sci.

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“…However, profitability of beef production in a beef herd is directly related to a high reproductive rate. Female reproductive traits appear to be the most economically important characters in many production systems (Newman et al, 1992;Phocas et al, 1998;Urioste et al, 1998). Hence, fertility should be included as part of the breeding objectives for beef cattle.…”

Section: Introductionmentioning

confidence: 99%

Genetic variability in calving success in Aberdeen Angus cows under extensive recording

Urioste

Chang

Naya

et al. 2007

Animal

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Data from 2032 Uruguayan Aberdeen Angus cows under extensive management and recording practices were analysed with Bayesian threshold-liability sire models, to assess genetic variability in calving success (CS), defined as a different binary trait for each of the second (CS2), third (CS3) and fourth (CS4) calving opportunities. Sire (herd) variances ranged from 0.08 to 0.11 (0.10 to 0.20) and heritability from 0.27 to 0.35, with large credibility intervals. Correlations between herd effects on CS at different calving opportunities were positive. Genetic correlation between CS2 and CS4 was positive (0.68), whereas those involving adjacent calving opportunities (CS2-CS3 and CS3-CS4) were negative, at 20.39 and 20.54, respectively. The residual correlation CS2-CS3 was negative (20.32). The extent of uncertainty associated with the posterior estimates of the parameters was further evaluated through simulation, assuming different true values (20.4, 20.2, 10.2 and 10.4) for the genetic correlations and changes in the degree of belief parameters of the inverse Wishart priors for the sire covariance matrix. Although inferences were not sharp enough, CS appears to be moderately heritable. The quality of data recording should be improved, in order to effect genetic improvement in female fertility.

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“…The definition of breeding objectives must be the first step in the outset of a genetic improvement program (Urioste et al, 1998;Smith, 1985;Ponzoni, 1986;Fewson, 1993), and traits considered in the breeding objective are the basis for the formulation of a profit function from which economic values are derived (Vercesi Filho, 1998). The economic importance of biological traits to be included in a breeding objective is assessed by their economic weights, defined as the expected increase in herd annual profit resulting from a unit increase in a trait due to selection (Jorge Júnior et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Breeding objectives and economic values for traits of low input family-based beef cattle production system in the State of Rio Grande do Sul

et al. 2012

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-The objectives of this study were to define breeding objectives and derive economic weights for production traits in family-based beef cattle systems, assess the sensitivity of these weights to changes in market and husbandry indicators and estimate the expected genetic changes in the selection criteria proposed. Based on data from the production systems, farms revenues and expenses, obtained from interviews and meetings with producers, a bioeconomic model was derived, relating biological traits of animals with the financial result of the production system based on calf-crop, selling male calves and culling cows for finishing. Traits considered in the model as breeding goals were weaning rate, weaning weight and cow weight. The economic weights, obtained by the partial derivative of the bioeconomic model with respect to the trait in question, assessed on the average value of the remaining traits, were R$ 73.21% for weaning rate, R$ 17.07/kg for weaning weight and R$ 4.75/kg for cow weight. An index for joint selection of these three criteria would allocate 89.5% of importance to weaning rate, 6.9% for weaning weight and 3.6% for cow weight. In this way, for every R$ 100.00 of genetic gain in this index, there would be an increase of 1.4% in weaning rate, but with reduction of 0.004 kg in weaning weight and 0.665 kg in cow weight due to negative genetic association between these traits. The proposed index and the relative importance identified for the economic traits can guide the selection decisions of smallholders, both in the choice of their animals and in the acquisition of bulls, cumulatively increasing the productivity of their herds.

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Breeding objectives for pasture‐fed Uruguayan beef cattle

Cited by 21 publications

References 15 publications

Genetic parameters for cow weight at calving and at calf weaning in South African Simmental cattle (Short communication)

Genetic parameters for cow weight at calving and at calf weaning in South African Simmental cattle (Short communication)

Genetic variability in calving success in Aberdeen Angus cows under extensive recording

Breeding objectives and economic values for traits of low input family-based beef cattle production system in the State of Rio Grande do Sul

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