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The aim of this study was to assess the accuracy of genomic predictions for 19 traits including feed efficiency, growth, and carcass and meat quality traits in beef cattle. The 10,181 cattle in our study had real or imputed genotypes for 729,068 SNP although not all cattle were measured for all traits. Animals included Bos taurus, Brahman, composite, and crossbred animals. Genomic EBV (GEBV) were calculated using 2 methods of genomic prediction (BayesR and genomic BLUP (GBLUP)) either using a common training dataset for all breeds or using a training dataset comprising only animals of the same breed. Accuracies of GEBV were assessed using 5-fold cross-validation. The accuracy of genomic prediction varied by trait and by method. Traits with a large number of recorded and genotyped animals and with high heritability gave the greatest accuracy of GEBV. Using GBLUP, the average accuracy was 0.27 across traits and breeds, but the accuracies between breeds and between traits varied widely. When the training population was restricted to animals from the same breed as the validation population, GBLUP accuracies declined by an average of 0.04. The greatest decline in accuracy was found for the 4 composite breeds. The BayesR accuracies were greater by an average of 0.03 than GBLUP accuracies, particularly for traits with known genes of moderate to large effect mutations segregating. The accuracies of 0.43 to 0.48 for IGF-I traits were among the greatest in the study. Although accuracies are low compared with those observed in dairy cattle, genomic selection would still be beneficial for traits that are hard to improve by conventional selection, such as tenderness and residual feed intake. BayesR identified many of the same quantitative trait loci as a genomewide association study but appeared to map them more precisely. All traits appear to be highly polygenic with thousands of SNP independently associated with each trait.

A computing strategy to update the inverse of the genomic relationship matrix when new genotypes become available is described. It is shown that re-using results of previous computations can result in substantial reductions in computing time required. For instance, when the number of individuals increased by about 1% for matrices larger than 15,000, the time required for updating was less than 7% of that used for direct inversion from scratch.

The objectives of this study were to use genotypes for 12 commercially available GeneSTAR gene markers on 12,330 animals to estimate gene frequencies of the markers across a range of beef cattle breeds and to determine the effects of these markers on target traits using a subset of animals with both genotypic and phenotypic data (n = 9,414) for at least one trait. Tenderness markers (T1, T2, T3, T4) were assessed against shear force of 2 muscles, marbling markers (M1, M2, M3, M4) were assessed against intramuscular fat percent and marbling score, and the feed-efficiency markers (N1, N2, N3, N4) were assessed on daily feed intake and residual feed intake. Animals used were from 5 beef cattle research populations: Beef Cooperative Research Centre 1 (CRC1) temperate breeds (Angus, Hereford, Murray Grey, Shorthorn; n = 3,721), Beef CRC1 tropical breeds (Brahman, Santa Gertrudis, Belmont Red; n = 3,899), Beef CRC2 tropically adapted genotypes (Brahman and Tropical Composite; n = 4,446), and progeny test programs in Angus (n = 742) and Shorthorn (n = 347). Gene frequencies varied significantly across breeds and markers, with 86% of the markers estimated to be in Hardy-Weinberg equilibrium. Tenderness markers T1 and T2 had significant effects (P 0.05) in CRC1 temperate breeds but was significant (P < 0.0001) in tropically adapted breeds, with a large effect in Brahman. Marker T4 was significant for shear force in 2 CRC1 tropical breeds but with a different favorable allele. The 4 marbling markers were generally not significantly associated with intramuscular fat percent or marbling score across the 5 populations studied. Feed-efficiency markers N3 and N4 were significantly associated with residual feed intake and daily feed intake in the CRC1 temperate data set, in which a subset of the CRC1 data was used in their discovery, but were not significant in the other 4 populations. Markers N1 and N2 were generally not significant, but when they were significant, their direction of effects differed. The 12 GeneSTAR markers were studied in populations consisting of different breeds and genetic variability and showed gene frequencies and estimated effects that varied greatly across traits, suggesting large differences between the markers for their utility as selection tools in these populations.

Records of a Northeastern Thai indigenous cattle line population were used to estimate genetic parameters and annual trends for calf weights. The data set comprised records of 1,922 and 1,489 animals for birth and weaning weight, respectively born from 1993 to 2004. A bivariate analysis was carried out for variance and covariance components estimations using average information restricted maximum likelihood procedure. Average estimated breeding value and maternal breeding value of the animals born in 1993 were set to zero as a base group. Genetic trends of each trait were calculated by regressing average estimated breeding values and maternal breeding values on birth year of calves. Phenotypic trends for each trait were calculated by regressing the yearly adjusted weight on birth year of calves. The results revealed that the estimate of direct heritability, maternal heritability and maternal permanent environmental variance as a proportion of phenotypic variance for birth and weaning weight was 0.40, 0.14 and 0.04; 0.27, 0.05 and 0.23, respectively. Direct heritability was moderately heritable and genetic improvement through selection can be achieved. The estimate of phenotypic, direct genetic, maternal genetic and maternal permanent environmental correlation between birth and weaning weight was 0.48, 0.65, 0.98 and 0.73, respectively. The phenotypic trend, genetic trends of estimated breeding value and maternal breeding value for birth weight was 0.18, 0.04 and 0.01 kg/year, respectively. The phenotypic trend, genetic trends of estimated breeding value and maternal breeding value for weaning weight was -1.36, 0.32 and 0.03 kg/year, respectively. As maternal genetic effect was considerably less important than direct genetic effect, selection for improved weaning weight of this Northeastern Thai indigenous cattle line can place more emphasis on the direct genetic effect.

Weaning weights from 83 389 Limousin calves born between 1993 and 2002 in France and the Trans-Tasman block (Australia/New Zealand) were analysed to compare different strategies for running an international genetic evaluation for the breed. These records were a subset of the complete data for both countries and comprised a sample of herds that had recorded progeny of sires used across both countries. Genetic and phenotypic parameters for weaning weight were estimated within the countries. The estimates of direct genetic heritabilities were higher in France than in the Trans-Tasman block (0.31 vs. 0.22), while direct-maternal genetic correlations were less negative in the Trans-Tasman block (-0.10) than in France (-0.21). Different strategies for an international evaluation were studied, and the correlations between the estimated breeding values (EBV) of national evaluations and these strategies were derived. The international evaluation strategies were a) an animal model on raw performance data with non unity genetic correlations and heterogeneous residual and genetic variances across countries; b) the same animal model applied to pre-corrected (for fixed effects) performance data; and c) a sire model on de-regressed proofs (MACE). Estimates of the genetic correlations between weaning weight in both countries were 0.86 (0.80) for direct (maternal) genetic effects for the first strategy. Estimation of variance components by MACE appeared to be very sensitive to the sample of bulls and their reliability approximations. Variance component estimates obtained using pre-corrected data were inconsistent with estimates on raw data. However, the EBV predicted using pre-corrected data and parameters estimated from the raw data were similar to those predicted from raw data. Correlations between national and international EBV were always high (> 0.90) for sires, whichever genetic effect (direct or maternal) or international evaluation model was considered. The ranking of the bulls in the top 100 is of primary interest in terms of international genetic evaluation. In this study, some re-ranking of sires was observed for the top 100 bulls between countries and between the three international evaluation models. Thus, the origin of top sires may vary according to the implemented international evaluation strategy.

Feed efficiency and growth are the most important traits in pig production, and very few genetic markers have been reported to be associated with feed efficiency. The suppressor of cytokine signalling-2 (encoded by SOCS2) is the main negative regulator of somatic growth, and the knockout of SOCS2 and naturally mutant mice have high-growth phenotypes. Porcine SOCS2 was selected as a primary positional candidate for feed efficiency, because it is located on chromosome 5q, in the vicinity of a Quantitative Trait Locus (QTL) region for food conversion ratio in pigs. Here, we report five single nucleotide polymorphisms identified by sequencing of the promoter region and exon 1. One PCR-RFLP assay was designed for genotyping the polymorphism c.1667A G (GenBank Accession No AY312266). Association analyses were performed in an Australian mapping resource pedigree population (PRDC-US43) for food conversion ratio, backfat, IGF1 level and growth traits and showed significant effects on average daily gain on test (ADG2) (P 0.01) and marginal association with food conversion ratio (FCR) (P 0.08).

Feed efficiency and growth are the most important traits in pig production, and very few genetic markers have been reported to be associated with feed efficiency. The suppressor of cytokine signalling-2 (encoded by SOCS2) is the main negative regulator of somatic growth, and the knockout of SOCS2 and naturally mutant mice have high-growth phenotypes. Porcine SOCS2 was selected as a primary positional candidate for feed efficiency, because it is located on chromosome 5q, in the vicinity of a Quantitative Trait Locus (QTL) region for food conversion ratio in pigs. Here, we report five single nucleotide polymorphisms identified by sequencing of the promoter region and exon 1. One PCR-RFLP assay was designed for genotyping the polymorphism c.1667A > G (GenBank Accession No AY312266). Association analyses were performed in an Australian mapping resource pedigree population (PRDC-US43) for food conversion ratio, backfat, IGF1 level and growth traits and showed significant effects on average daily gain on test (ADG2) (P < 0.01) and marginal association with food conversion ratio (FCR) (P < 0.08). © 2010 The Authors, Animal Genetics

Data from 1799 Large White and 1522 Landrace boars were used to obtain genetic correlations between production, carcase and meat quality traits. Variance components were obtained by REML procedures applying an average information algorithm. Traits analysed included average daily gain from 3 to 18 weeks of age (ADG1) and average daily gain, feed intake and feed conversion ratio from 18 to 22 weeks of age (ADG2, FDINT, FCR). Carcase traits included two backfat measurements and one muscle depth measurement taken on the live animal using realtime ultrasound and on the carcase using Hennesy Chong equipment. Further carcase traits included weight of the whole back leg (BLW) and weight of the ham (LMW). Meat quality traits included pH recorded 45 min (pH45) and 24 h after slaughter (pH24), colour of the m. longissimus dorsi (CLD) and m. multifidus dorsi(CMD), drip loss percentage (DLP) and intramuscular fat content (IMF). ADG1 was genetically a different trait than ADG2 (genetic correlation (rg): 0.3260.23). Genetic correlations between these two traits and backfat measurements were favourable for ADG1 (rg: 2 0.35 to 2 0.21, 60.13 to 0.22) and unfavourable for ADG2 (rg: 0.29 to 0.48, 60.18 to 0.22). A lighter CLD was genetically related to a higher DLP and a lower pH. Estimates were higher between pH24, CLD and DLP (absolute rg: 0.71 to 0.83, 60.11 to 0.14) than between pH45 and further meat quality traits (absolute rg: 0.12 to 0.44, 60.23 to 0.24). Increasing IMF will improve other meat quality traits (rg: 0.06 to 0.48, 60.19 to 0.24). Growth rate was genetically independent from meat quality traits (rg range: 2 0.31 to 0.35, 60.18 to 0.31) while selection for improved feed efficiency and increased leanness will increase the incidence of PSE meat (absolute rg range: 0.00 to 0.66, 60.14 to 0.31) and reduce IMF (rg: 0.16 to 0.34, 60.15 to 0.27). Meat quality traits should therefore be included in selection indices in order to avoid further deterioration as a result of selection for higher leanness and feed efficiency. © 2000 Elsevier Science B.V. All rights reserved.

The aim of this study was to assess the accuracy of genomic predictions for 19 traits including feed efficiency, growth, and carcass and meat quality traits in beef cattle. The 10,181 cattle in our study had real or imputed genotypes for 729,068 SNP although not all cattle were measured for all traits. Animals included Bos taurus, Brahman, composite, and crossbred animals. Genomic EBV (GEBV) were calculated using 2 methods of genomic prediction [BayesR and genomic BLUP (GBLUP)] either using a common training dataset for all breeds or using a training dataset comprising only animals of the same breed. Accuracies of GEBV were assessed using 5-fold cross-validation. The accuracy of genomic prediction varied by trait and by method. Traits with a large number of recorded and genotyped animals and with high heritability gave the greatest accuracy of GEBV. Using GBLUP, the average accuracy was 0.27 across traits and breeds, but the accuracies between breeds and between traits varied widely. When the training population was restricted to animals from the same breed as the validation population, GBLUP accuracies declined by an average of 0.04. The greatest decline in accuracy was found for the 4 composite breeds. The BayesR accuracies were greater by an average of 0.03 than GBLUP accuracies, particularly for traits with known genes of moderate to large effect mutations segregating. The accuracies of 0.43 to 0.48 for IGF-I traits were among the greatest in the study. Although accuracies are low compared with those observed in dairy cattle, genomic selection would still be beneficial for traits that are hard to improve by conventional selection, such as tenderness and residual feed intake. BayesR identified many of the same quantitative trait loci as a genomewide association study but appeared to map them more precisely. All traits appear to be highly polygenic with thousands of SNP independently associated with each trait.

A computing strategy to update the inverse of the genomic relationship matrix when new genotypes become available is described. It is shown that re-using results of previous computations can result in substantial reductions in computing time required. For instance, when the number of individuals increased by about 1% for matrices larger than 15,000, the time required for updating was less than 7% of that used for direct inversion from scratch.

Ambiguous paternity can be incorporated into the mixed model equations (MME) by including the average numerator relationship matrix (average A), which averages the true sire-offspring relationship over the putative sires. A previous study has shown that some overestimation of genetic trend results from this substitution. A population of 40 breeding females and 2 breeding males was simulated 1000 times with either random mating or sequential selection continuing for eight breeding cycles. In the selection case, candidates were ranked on estimated breeding values (EBVs) calculated from the MME with an animal model and the average A. Variances of the EBVs and prediction errors were computed. The results showed that the average A incorrectly perceives both the variance of family sizes among males and the variance loss due to selection to be smaller. This leads to an overestimation of genetic trend. ZUSAMMENFASSUNG: Auswirkung der durchschnittlichen genetischen Verwandtschaftsmatrix auf die Zuchtwertschätzung in einer Population mit Paarungen mehrerer Vatertiere Zweifelhafte väterliche Abstammung kann in die Mischmodellgleichung (MME) mittels durch- schnittlicher Numerator Verwandtschaftsmatrix (Durchschnitt A) eingebaut werden, die die durchschnittlichen wahren Verwandtschaften der in Frage kommenden Vatertiere beinhaltet. Eine frühere Untersuchung hat gezeigt, daß der genetische Trend dadurch eine gewisse Überschätzung erfährt. Eine Population aus 40 weiblichen und 2 männlichen Zuchttieren wurde 1000 mal simuliert, entweder unter Panmixie oder unter sequentieller Selektion durch acht Zuchtzyklen. Im Selektionsfall wurden die Kandidaten nach dem geschätzten Zuchtwert (EBV) rangiert der aus MME des Tiermodells mit durchschnittlicher A geschätzt worden ist. Varianzen der EBV und Schätzungsfehler wurden berechnet. Es zeigt sich, daß durchschnittliche A die Varianzen der Familiengrößen zwischen Vatertieren und den Varianzverlust durch Selektion als zu gering erfaßt, was zu einer Überschätzung des genetischen Trends führt.

Summary Ambiguous paternity can be incorporated into the mixed model equations (MME) by including the average numerator relatinship matrix (average A), which averages the true sire-offspring relationship over the putative sires. A previous study has shown that some overestimation of genetic trend results from this substitution. A population of 40 breeding females and 2 breeding males was simulated 1,000 times with either random mating or sequential selection continuing for 8 breeding cycles. In the selection case candidates were ranked on estimated breeding values (EBVs) calculated from the MME with an animal model and the average A. Variances of the EBVs and prediction errors were computed. The results showed the average A incorrectly perceives both the variance of family sizes among males and the variance loss due to selection to be smaller. This will lead to an overestimation of genetic trend. Zusammenfassung Folgerungen aus der Anwendung einer durchschnittlichen Verwandtschaftsmatrix bei der Zuchtwertschatzung fur eine Population mit mehreren Vatern in einer Paarungsgruppe In den Mischmodellgleichungen kann eine unklare vaterliche Abstammung durch die Verwendung einer durchschnittlichen Verwandtschaftsmatrix, die die Abstammung zu gleichen Teilen uber die moglichen Vater aufteilt, berucksichtigt werden. Eine fruhere Arbeit hat gezeigt, das diese Masnahme zu einer gewissen Uberschatzung des genetischen Fortschritts fuhrt. Eine Population mit 40 weiblichen und 2 mannlichen Tieren wurde 1000mal uber 8 Paarungsperioden simuliert und zwar mit und ohne gerichteter Selektion. Im Falle der Selektion wurden die Tiere aufgrund der mit einem Tiermodell und der durchschnittlichen Verwandtschaftsmatrix geschatzten Zuchtwerte geordnet. Die Varianzen der Zuchtwerte und der Schatzfehler wurden berechnet. Die Ergebnisse zeigen, das durch eine durch-schnittliche Verwandtschaftsmatrix die Varianz der Grose der Nachkommensgruppen der Vater und der Verlust an genetischer Varianz aufgrund der Selektion unterschatzt wird. Dies fuhrt zu einer Uberschatzung des genetischen Fortschritts.

The objectives of this study were to use genotypes for 12 commercially available GeneSTAR gene markers on 12,330 animals to estimate gene frequencies of the markers across a range of beef cattle breeds and to determine the effects of these markers on target traits using a subset of animals with both genotypic and phenotypic data (n = 9,414) for at least one trait. Tenderness markers (T1, T2, T3, T4) were assessed against shear force of 2 muscles, marbling markers (M1, M2, M3, M4) were assessed against intramuscular fat percent and marbling score, and the feed-efficiency markers (N1, N2, N3, N4) were assessed on daily feed intake and residual feed intake. Animals used were from 5 beef cattle research populations: Beef Cooperative Research Centre 1 (CRC1) temperate breeds (Angus, Hereford, Murray Grey, Shorthorn; n = 3,721), Beef CRC1 tropical breeds (Brahman, Santa Gertrudis, Belmont Red; n = 3,899), Beef CRC2 tropically adapted genotypes (Brahman and Tropical Composite; n = 4,446), and progeny test programs in Angus (n = 742) and Shorthorn (n = 347). Gene frequencies varied significantly across breeds and markers, with 86% of the markers estimated to be in Hardy-Weinberg equilibrium. Tenderness markers T1 and T2 had significant effects (P0.0001) on shear force, with the size and direction of effects consistent across the range of breeds for the 3 populations with phenotypes. However, sizes of marker effects differed across muscles and reduced upon tenderstretch hanging. Marker T3 was not significant (P0.05) in CRC1 temperate breeds but was significant (P0.0001) in tropically adapted breeds, with a large effect in Brahman. Marker T4 was significant for shear force in 2 CRC1 tropical breeds but with a different favorable allele. The 4 marbling markers were generally not significantly associated with intramuscular fat percent or marbling score across the 5 populations studied. Feed-efficiency markers N3 and N4 were significantly associated with residual feed intake and daily feed intake in the CRC1 temperate data set, in which a subset of the CRC1 data was used in their discovery, but were not significant in the other 4 populations. Markers N1 and N2 were generally not significant, but when they were significant, their direction of effects differed. The 12 GeneSTAR markers were studied in populations consisting of different breeds and genetic variability and showed gene frequencies and estimated effects that varied greatly across traits, suggesting large differences between the markers for their utility as selection tools in these populations.

Summary Relationships between breeding values (BVs) for milk protein, fat and yield of Australian Holstein-Friesian bulls and their plasma concentrations of growth hormone (GH), free fatty acids (FFA), urea (UR), glucose (GL) and insulin (IN) are examined and compared with published results from 16 other investigations. A total of 210 bulls from 3 AI centres were sampled 1985–88 before and after 3 days of fasting; 100 were also measured 24 hours after resumption of feeding. Plasma FFA and UR generally rose in response to fasting (98% and 80% of bulls), while IN, GH and GL declined (83%, 64% and 63%). GH, IN and UR had generally returned to normal 24 hours after refeeding, FFA remained a little elevated and GL, decreasing with fasting, tended to be higher than before fasting. BVs were available for 162 bulls. GH and increase in FFA were positively correlated with BVs (P < 0.002); UR before fasting was weakly negatively related (P < 0.05). However, overall variability, especially between centres and years, makes it unlikely these measurements alone could effectively predict BVs. After refeeding, mean GH, decrease in FFA and increase in GL were positively correlated, suggesting that animals with higher BVs had faster recovery rates or larger overshoots. This analysis was based on only 60 bulls from 1 centre, but effects were reasonably consistent over two years of measurement. An index derived from physiological data in the previous (following) year gave correlations within sampling group of 0.66 (0.49) with BVs of animals tested in 1988 (1987), accounting for 40% (9%) of variation after fitting parental BVs. It is not known if consistency will also be found between AI centres. If so, correlations of 0.5 between physiological indices and BVs might be expected, explaining about 25% of variation, though additional sampling and an improved experimental protocol could improve this percentage. Zusammenfassung Beziehungen zwischen Milchzuchtwert und physiologische Reaktionen auf Hunger und Wiederfutterung bei Bullen Die Zusammenhange zwischen Zuchtwerten (ZW) fur Milcheiweis, Milchfett und Milchmenge und Plasmakonzentrationen von Wachstumshormon (GH), freien Fettsauren (FFA), Harnstoff (UR), Glukose (GL) und Insulin (IN) australischer Holstein-Friesian Bullen wurden untersucht und mit Ergebnissen aus 16 anderen Arbeiten verglichen. Zwischen 1985 und 1988 wurden Messungen an 210 Bullen aus 3 KB-Stationen vor und nach einer dreitagigen Hungerperiode vorgenommen; an 100 Bullen wurden auch Messungen 24 Stunden nach Wiederaufnahme der Futterung erhoben. Die Plasmakonzentrationen der FFA und von UR nahmen als Reaktion auf die Hungerperiode im allgemeinen zu (bei 98% und 80% der Bullen), wahrend IN, GH und GL zuruckgingen (83%, 64% und 63%). GH, IN und UR kehrten 24 Stunden nach Wiederaufnahme der Futterung im allgemeinen wieder auf normale Werte zuruck, die FFA blieben ein wenig erhoht und GL, nach einer Abnahme wahrend der Hungerperiode, hatte die Tendenz zu erhohten Werten im Vergleich zu jenen vor der Hungerperiode. Fur 162 Bullen waren ZW vorhanden. GH und die Zunahme bei den FFA waren positiv mit den ZW korreliert (P < 0.002); UR vor der Hungerperiode hatte eine leicht negative Beziehung zu den ZW (P < 0.05). Doch die Gesamtvariabilitat, insbesondere zwischen Stationen und Jahren, last es als unwahrscheinlich erscheinen, das die ZW aus diesen Meswerten allein genugend genau vorhergesagt werden konnten. Nach Wiederaufnahme der Futterung wiesen die mittlere GH-Konzentration, der Ruckgang in der FFA-Konzentration und der Anstieg bei GL positive Korrelationen mit den ZW auf, was darauf hindeutet, das Tiere mit hoheren ZW sich schneller erholen oder grosere Uberreaktionen zeigen. Diese Untersuchung beruhte nur auf 60 Bullen aus einer Station, doch die Ergebnisse zweier Jahre waren ziemlich gleichlautend. Ein Index gebildet mit physiologischen Daten aus dem vorhergehenden (nachfolgenden) Jahr ergab Korrelationen innerhalb der Prufgruppen von 0.66 (0.49) mit den ZW der 1988 (1987) gepruften Tiere. Nachdem die ZW der Eltern berucksichtigt wurden, konnte 40% (9%) der Variation erklart werden. Es kann nicht gesagt werden, ob diese Ubereinstimmung auch zwischen KB–Stationen gefunden werden kann. In diesem Falle konnten Korrelationen von 0.5 zwischen den physiologischen Indices und den ZW erwartet werden, was ungefahr 25% der Variation erklaren wurde. Zusatzliche Probeerhebungen und ein verbessertes Versuchsprotokoll konnten diesen Prozentsatz erhohen.

This paper presents results from a mapping experiment to detect quantitative trait loci (QTL) for resistance to Haemonchus contortus infestation in merino sheep. The primary trait analysed was faecal worm egg count in response to artificial challenge at 6 months of age. In the first stage of the experiment, whole genome linkage analysis was used for broad-scale mapping. The animal resource used was a designed flock comprising 571 individuals from four half-sib families. The average marker spacing was about 20 cM. For the primary trait, 11 QTL (as chromosomal/family combinations) were significant at the 5% chromosome-wide level, with allelic substitution effects of between 0.19 and 0.38 phenotypic standard deviation units. In general, these QTL did not have a significant effect on faecal worm egg count recorded at 13 months of age. In the second stage of the experiment, three promising regions (located on chromosomes 1, 3 and 4) were fine-mapped. This involved typing more closely spaced markers on individuals from the designed flock as well as an additional 495 individuals selected from a related population with a deeper pedigree. Analysis was performed using a linkage disequilibrium-linkage approach, under additive, dominant and multiple QTL models. Of these, the multiple QTL model resulted in the most refined QTL positions, with resolutions of < 10 cM achieved for two regions. Because of the moderate size of effect of the QTL, and the apparent age and/or immune status specificity of the QTL, it is suggested that a panel of QTL will be required for significant genetic gains to be achieved within industry via marker-assisted selection. Refereed/Peer-reviewed

Data on Angus (ANG), Charolais (CHA), Hereford (HER), Limousin (LIM) and Simmental (SIM) cattle were used to estimate genetic parameters for calving difficulty (CD), birthweight (BWT) and gestation length (GL) using threshold-linear models and to examine the effect of inclusion of random effect of sire × herd interaction (SxH) in the models. For models without SxH, estimated heritabilities for direct genetic effect of CD were 0.24 (±0.02), 0.22 (±0.04), 0.31 (±0.02), 0.22 (±0.04) and 0.17 (±0.01) for ANG, CHA, HER, LIM and SIM, respectively, whereas maternal heritabilities ranged from 0.13 to 0.20. Estimated heritabilities for direct genetic effect of BWT were 0.38 (±0.01), 0.37 (±0.03), 0.46 (±0.01), 0.35 (±0.02) and 0.36 (±0.01) for ANG, CHR, HER, LIM and SIM, respectively, whereas maternal heritabilities ranged from 0.08 to 0.11. Estimated heritabilities for direct genetic effect of GL were 0.59 (±0.02), 0.42 (±0.04), 0.50 (±0.03), 0.45 (±0.04) and 0.42 (±0.03) for ANG, CHR, HER, LIM and SIM, respectively, whereas maternal heritabilities ranged from 0.03 to 0.09. Genetic correlations between direct genetic effects of CD with BWT were highly positive and with GL were moderately positive for all five breeds. Estimated genetic correlations between direct genetic effects and maternal genetic effects (rdm) ranged across the five breeds from –0.40 (±0.05) to –0.16 (±0.02), –0.41 (±0.03) to –0.27 (±0.08) and –0.47 (±0.10) to –0.06 (±0.12) for BWT, GL and CD, respectively. Fitting SxH interaction as additional random effect significantly increased the log-likelihood for analyses of BWT, GL and CD of all breeds, except for GL of CHA. The estimated heritabilities were less than or equal to the estimates obtained with models omitting SxH. The rdm increased (i.e. became less negative) for BWT, GL and CD of all five breeds. However, the increase for GL was not substantially high in comparison to the increase observed for BWT and CD. Genetic parameters obtained for BWT, GL and CD, by fitting SxH as an additional random effect, are more appropriate to use in the genetic evaluation of calving ease in BREEDPLAN.

Data (n = 2,658) from live animal ultrasonic measures from 17 Angus herds were used to evaluate a multiplicative mixed model that incorporates scaling factors to correct for across-herd heterogeneity of variance. Traits included were ribeye muscle area (EMA), surface fat at the P8 site (P8), surface fat between the 12th and 13th ribs (RIB12), and weight at scanning (WEIGHT). Cattle ranged in age from 501 to 698 d and represented 291 contemporary groups. Data were initially analyzed using single-trait, animal model, Method R procedures to estimate variance components and heritabilities (h 2 ). These estimates were incorporated into a multiplicative mixed model that simultaneously estimates breeding values (EBV) and heterogeneity factors. Reestimation of h 2 after scaling the data with the correction factors was explored to obtain a measure of the improvement in the genetic evaluation and to detect changes in ranking of individuals and herds. Initial h 2 estimates for EMA, P8, RIB12, and WEIGHT were.36,.39,.29, and.48, respectively. Scaling factors ranged from.25 for P8 in a herd with eight records to 1.96 for RIB12 in a herd with 86 individuals. Re-estimates of h 2 increased by an average of 4.2% for all the traits as a result of correcting for heterogeneity. Deviations of new scaling factors were within expectations. Correlations between EBV with and without heterogeneity correction were greater than.97 for all the traits. However, some substantial re-rankings of herds were observed for some traits in the smaller herds.

Genetic parameters of four ultrasound live-scan traits and five carcass traits of Australian Angus cattle were examined with regard to sex and age of the scanned individuals. Live-scans were subdivided according to whether the observation was obtained from a bull or a heifer. In addition, two age subset (‘young’ and ‘old’) within sex were formed by k-means clustering around two centres within sex according to the age at scanning. REML estimates for heritabilities, genetic, residual and phenotypic correlations for each trait and trait combination were derived from a series of uni-, bi- and tri-variate analysis. Statistically significant age effects could be found for heritablities of scan intra-muscular fat content in heifers and scan fat depth at P8 site and scan rib fat depth in bulls, and for genetic correlations between the scan traits fat depth at P8 site, rib fat depth and eye muscle area. However, differences in heritablities between age sets within sex did not exceed 0.05, and genetic correlations between scan traits of ‘young’ and ‘old’ animals were at least 0.9. Differences between genetic correlations of abattoir carcass traits and ‘young’ and ‘old’ live-scan traits, respectively, were not significant due to high standard errors but up to 0.44. The larger of these differences were found for combinations of scan-traits and non-target carcass traits and not for combination of scan-traits and their actual carcass target traits. Thus, although some results suggest an age effect on the genetic parameters of scan traits, the extent of this effect is of limited impact on breeding value accuracy and genetic gain of scan traits. Furthermore, a possible age effect on correlations to economically important carcass traits need to be underpinned by more carcass traits observations in order to get unambiguous results allowing to draw consequences of scanning younger individuals for accuracy of breeding values and genetic gain in carcass traits.

A method for multiple-trait genetic evaluation for categorical and continuous traits was generalized to a polychotomous rather than a binary trait and to several continuous traits rather than one. Any missing data pattern was allowed. Breeding values were estimated based on an animal model with fixed and random effects differing among traits. Equations in location parameters were solved iteratively within each Fisher scoring step. In each round of scoring, new solutions of the residual covariances among the categorical and the continuous traits were computed based on maximum likelihood estimation and used to reevaluate all partial regression coefficients of liability on the continuous traits for each missing data pattern. Simulation was used to assess the estimation of the residual covariances. The other dispersion parameters were treated as known because their estimation has been treated elsewhere and is analogous to restricted maximum likelihood.

The advantages of using a univariate threshold animal model (TAM) over the conventional linear animal model (AM) in the development of a genetic evaluation system for feet and leg traits of Angus cattle were explored. The traits were scored on a scale of 1–9 with scores 5 and 6 being the most desirable. The genetic parameters and estimated breeding values for front feet angle (FA), rear feet angle (RA), front feet claw set (FC), rear feet claw set (RC), rear leg hind view (RH) and rear leg side view (RS) were compared from AM and TAM. In order to predict breeding values to identify the animals with intermediate optimum, the scores were categorised to form three groups to differentiate the desirable group (5–6) from the other two groups with less desirable feet and leg appearances (1–4 and 7–9). The AM and TAM were used to estimate genetic parameters for the grouped data as well as the original score data. A TAM using the group data was used to predict the probability and breeding value for the desirable intermediate group. For the original score data, estimated heritabilities on the underlying scale, using TAM, were 0.50, 0.46, 0.35, 0.44, 0.32 and 0.22 for FA, FC, RA, RC, RH and RS, respectively, and were 0.01–0.18 higher than the heritabilities estimated using AM. Genetic correlation between the six traits using a bivariate TAM with all scores ranged from 0.02 to 0.50 with front and rear angles had the highest genetic correlation at 0.50. For all six traits, proportion in the intermediate desirable group was higher than the other two groups combined. The low annual genetic change observed for all six traits over the 10 years of data recording reflected the lack of directional selection to improve the traits in Angus cattle. For genetic evaluation of feet and leg traits with an intermediate optimum, TAM is a preferred method for estimating genetic parameters and predicting breeding values for the desirable category. The TAM has now been implemented for regular estimated breeding value analysis of feet and leg traits of Angus cattle.

This study aimed to examine the impact of early weaning on residual feed intake, and other production and carcass traits, in a group of cattle subjected to early or conventional weaning treatments, but otherwise managed as contemporaries. Shorthorn (n = 140) calves were randomly allocated by sex and sire to early and conventional weaning treatments. Early weaned animals (n = 69) were weaned at an average of 123 days of age and 145 kg liveweight, while conventionally weaned steers and heifers (n = 71) were 259 days old at weaning and 273 kg. Following conventional weaning, animals were managed as contemporaries through backgrounding, and entered feedlot finishing at a mean age of 353 and 408 days for heifers and steers, respectively, for finishing and feed intake testing. At the conclusion of feed intake testing hip height was measured, and animals were ultrasound scanned to assess fat depth, eye muscle area and percent intramuscular fat. Early weaned animals were significantly lighter (P < 0.001) than their conventionally weaned contemporaries, when weighed at conventional weaning. The weight difference observed at conventional weaning of 19.4 kg between treatment groups persisted throughout the experiment, with significant (P < 0.05) differences of 17.1, 15.6 and 15.8 kg at feedlot entry, and the start and end of the feed intake test period, respectively. Weaning treatment also approached significance for daily feed intake (P = 0.06), with early weaned animals tending to eat less than their conventionally weaned contemporaries (daily feed intake = 11.6 and 12.0 kg, respectively). Weaning treat\ment did not significantly affect feed efficiency whether measured as residual feed intake (P = 0.64) or feed conversion ratio (P = 0.27). None of the other traits measured were significantly affected by weaning treatment. These data showed that early weaning, as implemented for this experiment, resulted in animals that were lighter than their conventionally weaned contemporaries through backgrounding and finishing. Weaning treatment did not, however, influence feed efficiency or the post-weaning growth and carcass composition traits measured for this experiment.

The magnitude of genotype × environment interactions (G × E) were estimated for growth, real time ultrasound scanned carcass and reproductive traits in Angus cattle. Traits measured in the states of Victoria and Queensland were assumed as different traits and the genetic correlations between them were estimated. Estimated heritabilities across states were similar for all traits. However, additive genetic variances of fat depth at the P8 (rump) site for bulls (BP8), intramuscular fat percent at the 12/13th rib for bulls (BIMF) and heifers (HIMF) were significantly different between states. Estimated genetic correlations across states for direct genetic effects were high for growth traits and ranged from 0.89 to 1.00. For the maternal genetic effects the correlations across states ranged from 0.66 to 0.87. The across state correlations for scanned traits were also high. The exception was for BIMF (0.65), where measurement procedures were observed to influence the result. The genetic correlation between the states increased to 0.94 when the records of bulls with low IMF value were removed. For reproductive traits, the estimated genetic correlations ranged from 0.97 to 1.00. These results indicated little evidence of G × E for growth, ultrasound scanned carcass and reproductive traits of Angus cattle from Victoria and Queensland. Combining performance data across states in a national genetic evaluation is appropriate and it is expected that the progeny of Angus cattle would rank similarly across states.

Both wool and sheep meat industries are interested in sheep that have a high reproduction performance and are resistant to internal parasites, in addition to the traditional traits. There is considerable interest in breeding sheep for wool, carcass, reproductive and internal parasite resistance traits simultaneously. The objective of this study was to estimate single trait genetic parameters for 40 traits recorded in Merino sheep, covering bodyweight, carcass, wool, reproduction and internal parasite resistance traits. This also involved determining the appropriate models. The results from this study will be used to review the genetic parameters used in the routine genetic evaluations conducted by Sheep Genetics. The most appropriate models included a maternal genetic effect and covariance between direct and maternal genetic effects for most of the bodyweight traits, greasy and clean fleece weight, fibre diameter and coefficient of variation of fibre diameter. The permanent environment due to the dam was not included for any trait. There was considerable genetic variation in most traits analysed; lowest heritabilities (0.09–0.10) were found for number of lambs born and weaned per lambing opportunity, and highest heritabilities (0.62–0.77) for fibre diameter. The estimated heritabilities and genetic variances, in combination with the estimated correlations, indicate that there is potential to make genetic improvement in most traits currently recorded in Australian Merino sheep.

Insulin-like growth factor-I (IGF-I) concentration measured in the blood plasma of 6520 seedstock Angus beef cattle (3622 bulls and 2898 heifers) from eastern Australia between 2002 and 2004 was used to estimate the heritability of IGF-I and phenotypic and genetic correlations with net feed intake (NFI) and other production traits. The average concentration of IGF-I was 314 ng/mL measured at the average age of 242 days. A moderate heritability of 0.35 was estimated for IGF-I. IGF-I was further defined as being measured either at, or prior to, weaning (average age of 201 days) or post-weaning (average age 310 days). The genetic correlation between IGF-I recorded at the different ages was 1.0 ± 0.04. IGF-I and NFI were found to have a genetic correlation of 0.41 ± 0.21. IGF-I had positive genetic correlations of 0.22 ± 0.14, 0.19 ± 0.14, and 0.26 ± 0.15 with ultrasound-scanned subcutaneous fat depth at the rump (P8) and 12/13th rib (RIB) sites and intramuscular fat % (IMF), respectively. Corresponding phenotypic correlations were 0.14, 0.13, and 0.12, respectively, for P8, RIB, and IMF. IGF-I had low to moderate negative genetic correlations with growth traits. Direct genetic correlations for IGF-I of –0.22 ± 0.08, –0.17 ± 0.09 and –0.10 ± 0.14 were estimated with birth (BWT), 200-day (WT200), and 400-day (WT400) weights, respectively. Genetic correlations between the direct component of IGF-I and maternal components of BWT and WT200 were 0.15 ± 0.13 and 0.31 ± 0.11, respectively. Phenotypic correlations of the direct component of IGF-I with the direct components of BWT, WT200, and WT400 were –0.10, 0.06, and 0.16, respectively. Ultrasound-scanned eye muscle area (EMA) and IGF-I had genetic and phenotypic correlations of –0.22 ± 0.15 and 0.13, respectively. This study showed that IGF-I is heritable and genetically correlated with important production traits. The genetic correlations indicate that selection for lower IGF-I concentrations would result in cattle that have lower NFI (i.e. more feed efficient), are leaner, with increased growth, and possibly decreased maternal weaning weight.

Genetic evaluation for beef cattle in Australia has been performed using an animal model with best linear unbiased prediction since 1984. The evaluation procedures have evolved from simple to more complex models and from few to a large number of traits, including traits for reproduction, growth and carcass characteristics. This paper describes in detail the current beef cattle genetic evaluation system ‘BREEDPLAN’ used for the Australian beef cattle industry, the traits analysed and underlying models, and presents a short overview of the challenges and planned developments of coming years.

Insulin-like growth factor-I (IGF-I) is a naturally occurring polypeptide produced in the liver, muscle and fat tissues. It is known to be associated with growth and development during the postnatal growth period. Evidence for strong genetic correlations between juvenile IGF-I and performance traits would suggest this physiological measure would be useful as an early selection criterion. This paper reports estimates of genetic parameters from 9 trials where IGF-I was measured in juvenile pigs. All trials involved populations undergoing active selection for improved performance (e.g. efficient lean meat growth). Juvenile IGF-I was moderately heritable (average h2: 0.31) and influenced by common litter effects (average c2: 0.15). Genetic correlations (rg) between juvenile IGF-I and backfat (BF), feed intake (FI) or feed conversion ratio (FCR) traits were generally large and positive: rg averaged 0.57, 0.41 and 0.65, respectively. Phenotypic correlations (rp) between juvenile IGF-I and BF, FI or FCR were much lower (rp averaged 0.21, 0.09, and 0.15, respectively) as residual correlations between IGF-I and these performance traits were low, consistent with being measured at very different times. Correlations (genetic or phenotypic) between juvenile IGF-I and growth traits (e.g. lifetime daily gain or test daily gain) were relatively low, with average values within ± 0.09 of zero. Results from the trials reported here, and several physiological studies, indicate that information on juvenile IGF-I concentration can be used as an early physiological indicator of performance traits traditionally measured later in life. There is a clear role for juvenile IGF-I to facilitate pre-selection and more accurate selection of livestock for hard to measure traits, such as FCR, in pig breeding programs.

Estimates of covariance components among all 22 traits considered in the current multi-trait genetic evaluation of Australian Hereford cattle were obtained. Traits included 5 weight traits, 8 traits measured through live ultrasound scanning, 3 traits related to reproductive performance, and 6 carcass traits. Estimates were obtained by restricted maximum likelihood, carrying out a series of bivariate analyses. Data for each analysis were selected attempting to maximise the number of animals or animal-parent pairs that had both traits recorded. Estimates were pooled using a weighted 'iterative summing of expanded part matrices' procedure, which ensured positive semi-definite covariance matrices. Models of analyses for individual traits closely resembled those used in genetic evaluation. Results generally agreed with literature results, although estimates of genetic parameters for carcass traits that had few records available tended to fluctuate. Except for 'days to calving', heritability estimates were moderate to high for all traits. Genetic parameters for early growth were different to those for other breeds, with maternal effects for weaning weight being considerably more important and the heritability somewhat lower. AR K. M eyer et al Hera

A model beef cattle breeding scheme consisting of a breeding unit and a commercial unit was used to evaluate the impact on genetic gain and profitability of incorporating feed intake measurements as an additional selection criterion in breeding programmes. Costs incurred by the breeding unit were compared with returns generated in the commercial unit, with bulls from the breeding unit being used as sires in the commercial unit. Two different market objectives were considered — a grass-fed product for the Australian domestic market, and a grain-fed product for the Japanese market. Breeding units utilising either artificial insemination or natural service were also considered. A base scenario was modelled incorporating a range of criteria available to Australian cattle breeders. A second scenario incorporated selection of sires for the breeding unit using a 2-stage selection process, with a proportion of bulls selected after weaning for measurement of (residual) feed intake. Measurement of feed intake of bulls improved accuracy of breeding unit sire selection by 14–50% over the equivalent base scenario, and genetic gain in the breeding objective was improved for all scenarios, with gains ranging from 8 to 38% over the base scenario. After accounting for the cost of measuring feed intake ($150–450), additional profit was generated from inclusion of feed intake measurement on a proportion of bulls for all breeding schemes considered. Profit was generally maximised where 10–20% of bulls were selected at weaning for measurement of intake, with improvement in profit ranging from 9 to 33% when optimal numbers of bulls were selected for intake measurement.

A deterministic approach was used to evaluate the effect of incorporating direct and indirect measures of feed intake as additional selection criteria in breeding schemes for Hereford cattle. A 2-tier nucleus breeding scheme consisting of a nucleus and a commercial sector was assumed. Four breeding objectives specific to Australian Hereford cattle were considered. These addressed production systems that targetted 4 markets (Domestic Supermarket, 'Hereford Prime', Short-fed Export, and Long-fed Export). The breeding objectives differed especially in the feed cost involved for differing amounts of grain finishing and in the extent to which marbling is valued by the market (from none to quite a lot). The breeding schemes evaluated differed in the measures available for use as selection criteria. The schemes ranged from one that utilised growth, scanned carcass and fertility criteria currently available to Australian cattle breeders (Scheme 1) to one which also incorporated residual feed intake (RFI) and blood serum insulin-like growth factor I (IGF-1) criteria (Scheme 5). The latter scheme included selection of sires for the nucleus using a 2-stage selection process, with a proportion of bulls selected after weaning for measurement of RFI. Schemes utilising either IGF-1 or RFI or both as criteria generated additional genetic gain and profitability for each breeding objective. Profit was optimal across all the Hereford cattle breeding objectives when the top 5% of bulls was measured for RFI after being selected on an index incorporating IGF-1 and other information available on the bull and its relatives at a young age. Further increase in the proportion of bulls measured for RFI for consideration in the second selection stage resulted in a slow decline in profit per cow in the population and a flat response in genetic gain. In the absence of more breed-specific information, these results may also have application in breeds other than Herefords.

In order to estimate genetic parameters, abattoir carcass data on 1,713 Angus and 1,007 Hereford steers and heifers were combined with yearling live-animal ultrasound measurements on 8,196 Angus and 3,405 Hereford individuals from seedstock herds. Abattoir measures included carcass weight (CWT), percentage of retail beefyield (RBY), near-infrared measured intramuscular fat percentage (CIMF), preslaughter scanned eye muscle area (CEMA), and subcutaneous fat depth at the 12th rib (CRIB) and at the P8 site (CP8). Ultrasound scans on yearling animals included 12th-rib fat depth (SRIB), rump fat depth at the P8 site (SP8), eye muscle area (SEMA), and percentage of intramuscular fat (SIMF). Records on CWT were adjusted to 650-d slaughter age, and the remaining abattoir traits were adjusted to 300-kg CWT. Scan data were analyzed treating records on males and females as different traits. Multivariate analyses were performed on a variety of trait combinations using animal model and REML algorithm. Heritability (h2) estimates for CWT, RBY, CIMF, CP8, CRIB, and CEMA were .31, .68, .43, .44, .28, and .26, respectively, for Angus and .54, .36, .36, .08, .27, .38, respectively, for Hereford. Pooled across sexes, h2 estimates for SIMF, SP8, SRIB, and SEMA were .33, .55, .51, and .42, respectively, for Angus and .20, .31, .18, and .38, respectively, for Hereford. Genetic correlations (r(g)) between the same pair of carcass traits measured at yearling through scanning and directly at the abattoir were moderate to strongly positive, suggesting that selection using yearling ultrasound measurements of seedstock cattle should result in predictable genetic improvement for abattoir carcass characteristics. Estimates of r(g) between the scanned fat measurements and RBY were negative, ranging from -.85 for Angus heifers to -.05 for Hereford heifers. Also, the estimates of r(g) between SEMA and the fat records measured at the abattoir were negative and ranged from -.94 in Hereford heifers to -.02 in Angus heifers.

Weaning weight records of 12 563 Santa Gertrudis calves were used to estimate (co)variance components using a bivariate restricted maximum likelihood analysis. The analysis considered measurements on animals born in favourable production environments as Trait 1 and animals born in unfavourable production environments as Trait 2. Estimates of variance components for weaning weight across production environments were similar in magnitude. An additive genetic correlation of 0·64 between production environments was significantly different from unity, suggesting that there was a genotype production environment interaction. However, when a sire contemporary group interaction effect was included in the model, the genetic correlation between Trait 1 and Trait 2 was not significantly different from unity. These results suggest that the ranking of Santa Gertrudis sires across production environments was caused by changes in ranking from one contemporary group to the next rather than changes in ranking across production environments.

Estimates of (co)variance components and genetic parameters were obtained for a preweaning weight, recorded between 2 and 5 months after birth, and the subsequent gain till weaning for two herds in a selection experiment in Western Australia. Analyses were carried out both accounting for age at weighing and assuming birth dates and thus ages were unknown. On adjusting for the interval between weighings, preweaning gain appeared to be independent of age and equally heritable to weaning weight. Estimates of the direct genetic correlation between preweaning gain and weaning weight (adjusted for age) were 0.9 or higher, while both genetic and permanent environmental maternal correlations were close to unity. Implications for the use of preweaning weight as an alternative selection criterion to weaning weight when birth dates are not recorded are discussed.

Planning calculations for the further development of beef performance tests for dual-purpose cattle have been conducted. Daily gain, feed conversion, growth capacity and muscle proportion of shrunk live weight are considered as economic traits of beef performance. The genetic improvement of beef performance is obtained through the selection of bulls for use in artificial insemination. Testing methods for the bulls are individual performance and progeny tests with male and female progenies in station and field, respectively. In addition, combinations of several testing methods are considered. Mainly the effects of the relationships between test and production environment are investigated. For the planning calculations the economic, biological and technical parameters for breeding are orientated at the breeding plan of Simmental (Fleckvieh) in Baden-Wurttemberg (West Germany). The following results were obtained: 1. 1. With an extension of the beef performance tests a lasting improvement of the monetary genetic gain and profit can be achieved. Moreover the proportion of the beef performance in the total genetic gain can be considerably increased. 2. 2. The restricted testing capacity in station should largely be used for the performance testing of young bulls from planned matings. 3. 3. For the attainment of optimal testing conditions for the performance testing of young bulls in station it is advisable to increase the selection intensity and to enlarge the testing capacity. 4. 4. The performance testing of young bulls in station should be complemented by a progeny test for beef. The method of the progeny test must be adapted to the regional production system. 5. 5. The testing environment in station should be adapted to the commercial production environment, to avoid genotype-environment interactions. With the given parameters this is especially true for a longer test period. 6. 6. The discussion deals with factors for the efficiency of the testing methods for beef performance.

An efficient algorithm is described for computing restricted maximum likelihood estimates of variance components in a class of models. The class of models is characterized by effects to be absorbed, which are nested within herds, other fixed effects, random sire effects, one other group of random effects nested within herds, and a random residual. The model can be generalized to account for relationships among sires. Matrix inversion is not used. A realistic example is presented.

Heritabilities and genetic and phenotypic correlations have been estimated for first-lactation test day production, based on a total of 502 453 test day records. Traits analysed were milk yield, fat yield and fat content for New South Wales, Victoria and Tasmania, and protein yield and content for Victoria. Univariate analyses examined monthly records for models fitting herd-year-season and herd-test-day effects, respectively. Multivariate analyses considered successive subsets of the data, increasing the minimum number of test records per cow sequentially. Heritability estimates from multivariate analyses of tests at individual days were on average 0.19, 0.12, 0.26, 0.14 and 0.35 for the 5 traits, respectively, i.e. as high as estimates for total lactations in Australia, obtained in a previous analysis. Genetic correlations between consecutive tests were of the order 0.8–0.9. Both genetic and phenotypic correlations decreased with increasing time between tests. A canonical decomposition of the estimated covariance matrices between and within sires yielded linear functions of 5 or more test day records with heritabilities of the order 0.3–0.4 and genetic correlations of unity with lactation production. These ‘canonical indices’ may provide alternative selection criteria for the improvement of dairy performance.

Estimates of genetic parameters were obtained for weight, hip height, heart girth and shoulder to pin length measurements on Thai swamp buffalo, recorded at birth and weaning. Direct heritability estimates were 0·26 for weights at both ages and were low for skeletal measurements, ranging from 0·11 to 0·19. Low values could, in part at least, be caused by inaccuracies in recording. All traits were subject to maternal effects, permanent environmental maternal effects on traits recorded at weaning explaining proportionately up to 0·14 of the total variation. Estimates of genetic (direct and maternal) and permanent environmental correlations between traits recorded at the same time were high throughout, ranging from 0·83 to 0·97 for additive genetic effects and being close to unity otherwise. Except for heart girth measured at weaning, there appeared to be comparatively little genetic association between traits recorded at different times, direct additive correlation estimates ranging from 0·18 to 0·55 in contrast to estimates of 0·38 to 0·65 for correlations with heart girth at weaning.