This study compared the use of various models to describe growth in lambs of 2 contrasting breeds from birth to slaughter. Live BW records (n = 7559) from 240 Texel and 231 Scottish Blackface (SBF) lambs weighed at 2-wk intervals were modeled. Biologically relevant variables were estimated for each lamb from modified versions of the logistic, Gompertz, Richards, and exponential models, and from linear regression. In both breeds, all nonlinear models fitted the data well, with an average coefficient of determination (R2) of > 0.98. The linear model had a lower average R2 than any of the nonlinear models (< 0.94). The variables used to describe the best 3 models (logistic, Gompertz, and Richards) included estimated final BW (A); maximum ADG (B); age at maximum ADG (C); position of point of inflection in relation to A (D, for Richards only). The Richards and Gompertz models provided the best fit (average R2 = 0.986 to 0.989) in both breeds. Richards estimated an extra variable, allowing increased flexibility in describing individual growth patterns, but the Akaike's information criteria value (which weighs log-likelihood by number of parameters estimated) was similar to that of the Gompertz model. Variables A, B, C, and D were moderately to highly heritable in Texel lambs (h2 = 0.33 to 0.87), and genetic correlations between variables within-model ranged from -0.80 to 0.89, suggesting some flexibility to change the shape of the growth curve when selecting for different variables. In SBF lambs, only variables from the logistic and Gompertz models had moderate heritabilities (0.17 to 0.56), but with high genetic correlations between variables within each model (< -0.88 or > 0.92). Selection on growth variables seems promising (in Texel more than SBF), but high genetic correlations between variables may restrict the possibilities to change the growth curve shape. A random regression model was also fitted to the data to allow predictions of growth rates at relevant time points. Heritabilities for growth rates differed markedly at various stages of growth and between the 2 breeds (Texel: 0.14 to 0.74; SBF: 0.07 to 0.34), with negative correlations between growth rate at 60 d of age and growth rate at finishing. Following these results, future studies should investigate genetic relationships between relevant growth curve variables and other important production traits, such as carcass composition and meat quality.

The aim of this study was to investigate the effects of animal trait, breed combination, and climate on the expressed levels of heterosis in crossbreeding schemes using tropical cattle. A meta-analysis of 42 studies was carried out with 518 heterosis estimates. In total, 62.5% of estimates were found to be significantly different from zero, the majority of which (89.8%) were beneficial for the studied trait. Trait and breed combination were shown to have a significant effect on the size of heterosis (P < 0.001 and P = 0.044, respectively). However, climate did not have a significant effect. Health, longevity, and milk production traits showed the highest heterosis (31.84 ± 10.73%, 35.13 ± 14.35%, and 35.15 ± 3.29%, respectively), whereas fertility, growth, and maternal traits showed moderate heterosis (12.02 ± 4.10%, 12.25 ± 2.69%, and 15.69 ± 3.26%, respectively). Crosses between breeds from different types showed moderate to high heterosis ranging from 9.95 ± 4.53% to 19.53 ± 3.62%, whereas crosses between breeds from the same type did not express heterosis that was significantly different from zero. These results show that heterosis has significant and favorable impact on productivity of cattle farming in tropical production systems, particularly in terms of fitness but also milk production traits.

In this chapter, the main strategies for genetic improvement are discussed. Highlights focused on the structure of livestock breeding industries, selection, crossbreeding, and conservation of genetic resosurces.

Profitability of sheep production systems depends on several different animal characteristics rather than a single trait. Economic selection indexes combine information from more than one trait into an overall score, to maximise genetic gain. Economic values (EVs) are required for each trait in the breeding goal so that selection emphasis is proportional to the economic importance of each trait. Defining clear breeding goals is more complex for hill breeds than for other sectors of the sheep industry because they provide breeding females in addition to lambs for slaughter. The aims of this paper are to i) describe how EVs for breeding goal traits suitable for UK hill sheep were derived for a combination of carcass, maternal and ‘sustainability’ traits using a bio-economic model, and ii) show how these EVs vary between different production systems as a result of the differences in the physical constraints of farm size, pasture availability and the biological limits of sheep in extensive rearing environments.

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