Research and development to provide systems for effective derivation and use of selection indexes has been conducted for the Australian beef industry since the late 1980s. This paper reports on development successes and presents evidence of increasing rates of industry genetic gain in beef production profitability. Key factors in success are identified and include the ability of the index development process to capture the full context of selection. The level of performance recording in many cases is the primary limitation to effective index use. Issues that will be more important in future applications of indexes are discussed. They include the need for more specific selection for environments, for extending the breeding objective to encompass additional industry sectors and aims, for greater account of industry supply and demand flow-on effects, and for combining gene marker tests with other criteria in indexes of economic merit. The critical role of selection indexes in targeting multiple-trait economic merit is likely to increase further with the availability of new gene marker test information

Genetic trends are presented for the estimated feed intake of young Angus animals at pasture and in the feedlot, and of Angus cows at pasture for a self-replacing, 100d-finished production system. Increases in feed intake over time, both at pasture and in the feedlot, are estimated to have accompanied genetic gains in productivity traits in Angus cattle. The estimated increases are both in feed requirement and residual feed intake, with the latter being smaller in magnitude. The need for industry to record feed intake to facilitate selection for feed efficiency and, in the absence of this, for stocking rate to be managed in commercial herds to offset increases in feed intake, are factors briefly discussed in connection with industry realising benefits from genetic improvement.

This paper briefly describes a new facility, developed within 'BreedObject on the web', where Australian seedstock (eg. bulls, semen) are able to be ranked on overseas and Australian indexes as well as overseas seedstock ranked on Australian indexes. The development was at the request of Australian and overseas breeds, who agreed to share the availability of their indexes. Through the ability of ‘BreedObject on the web’ to calculate indexes on-line, and through its on-line access to breed databases, results for the indexes of different countries are able to be reproduced, on demand, for any selection of animals from the databases. The facility has the potential to assist the export of superior Australian seedstock, and to expand the gene pool for Australian breeders by increasing the effectiveness with which animals with desirable genetic merit are identified in overseas populations.

Research and development to provide systems for effective derivation and use of selection indexes has been conducted for the Australian beef industry since the late 1980s. This paper reports on development successes and presents evidence of increasing rates of industry genetic gain in beef production profitability. Key factors in success are identified and include the ability of the index development process to capture the full context of selection. The level of performance recording in many cases is the primary limitation to effective index use. Issues that will be more important in future applications of indexes are discussed. They include the need for more specific selection for environments, for extending the breeding objective to encompass additional industry sectors and aims, for greater account of industry supply and demand flow-on effects, and for combining gene marker tests with other criteria in indexes of economic merit. The critical role of selection indexes in targeting multiple-trait economic merit is likely to increase further with the availability of new gene marker test information.

This paper outlines a method for assessing trait economic impacts, at the level of the individual animals considered in selection, for traits where the economic value changes across the range of the trait. Results are compared with those from linear methods for price patterns that are common for traits, such as beef carcase fat depth, weight and marbling score, which affect market acceptability and preference. Some important deviations from linearity were seen in the change in index that occurs with change in estimated breeding value (EBV) for these traits. The deviations were most evident at the extremes of the EBV range, which could affect the animals selected. Simple extensions of the method are also suited for use in mate selection and other important areas where non-linearity is encountered.

Genetic trends are presented for estimated greenhouse gas (GHG) emissions of young Angus animals at pasture and in the feedlot, and of Angus cows at pasture for a self-replacing, 100d-finished production system. GHG emissions are predicted to have increased over time, accompanying genetic gains in productivity traits and feed intake. The trends support the need for multiple trait selection that appropriately considers feed intake and the whole production chain. The results show the cost of feed used in the breeding objective impacts on the GHG emissions reductions that can be achieved with selection. Small reductions in GHG emissions can be achieved when feed is expensive, e.g. $130/t, and carbon is priced at $0/t. When feed is inexpensive GHG emissions increase and an $80/t carbon price is needed to make GHG emission changes negligible.

Methods are presented for including feed intake and efficiency in genetic selection for multiple-trait merit when commercial production is from any combination of pasture or concentrates. Consequences for the production system and for individual animals are illustrated with a beef cattle example. Residual feed intake at pasture (RFI-p), residual feed intake in the feedlot (RFI-f), and cow condition score are additional traits of the breeding objective. Feed requirement change is costed in the economic values of other objective traits. Selection responses are examined when feed costs are ignored, partially or fully included in the breeding objective, and when net feed intake (NFI) EBVs are added to the index. When all feed cost was included and NFI EBVs were in the index, selection (with selection intensity, i = 1) increased production system $ net return by 6.0%, $ per unit of product by 5.2%, $ per unit of feed by 6.6%, total product by 0.7% and product per unit of feed by 1.3%. There was little change in production system total feed. When feed cost was ignored, selection decreased production system $ net return, $ per unit of product, and $ per unit of feed. At the individual trait level, when feed was fully included there were increases in weaning weight-direct (0.8 kg), feedlot entry weight (1.4 kg), dressing % (0.04%), carcass meat % (0.36%), carcase fat depth (0.12 mm), carcass marbling score (0.02 score), cow condition score (0.01 score), calving ease-direct (0.97%), calving ease-maternal (0.22%) and cow weaning rate (1.3%), and decreases in weaning weight-maternal (-0.9 kg), RFI-p (-0.09 kg DM/d), RFI-f (-0.11 kg DM/d), sale weight (-1.6 kg) and cow weight (-8.7 kg). Gains were evident over a range of feed price. Selection for $ net return also increased $ net return per unit of feed, suggesting that $ net return per unit area would increase in grazing industries. Feed cost for trait change was the source of a major genotype x environment interaction affecting animal rankings. Where industry production environments vary, and feed cost for trait change varies with the environment, we recommend that industry indexes be derived for more than one level of feed cost. Cow condition score did not decline while biological and economic efficiency of the production system and individual animal were improving, suggesting that efficiency can be improved under multiple-trait selection without compromising breeding cow welfare.

Background: Societal pressures exist to reduce greenhouse gas (GHG) emissions from farm animals, especially in beef cattle. Both total GHG and GHG emissions per unit of product decrease as productivity increases. Limitations of previous studies on GHG emissions are that they generally describe feed intake inadequately, assess the consequences of selection on particular traits only, or examine consequences for only part of the production chain. Here, we examine GHG emissions for the whole production chain, with the estimated cost of carbon included as an extra cost on traits in the breeding objective of the production system. Methods: We examined an example beef production system where economic merit was measured from weaning to slaughter. The estimated cost of the carbon dioxide equivalent (CO₂-e) associated with feed intake change is included in the economic values calculated for the breeding objective traits and comes in addition to the cost of the feed associated with trait change. GHG emission effects on the production system are accumulated over the breeding objective traits, and the reduction in GHG emissions is evaluated, for different carbon prices, both for the individual animal and the production system. Results: Multiple-trait selection in beef cattle can reduce total GHG and GHG emissions per unit of product while increasing economic performance if the cost of feed in the breeding objective is high. When carbon price was $10, $20, $30 and $40/ton CO₂-e, selection decreased total GHG emissions by 1.1, 1.6, 2.1 and 2.6% per generation, respectively. When the cost of feed for the breeding objective was low, selection reduced total GHG emissions only if carbon price was high (~ $80/ton CO₂-e). Ignoring the costs of GHG emissions when feed cost was low substantially increased emissions (e.g. 4.4% per generation or ~ 8.8% in 10 years). Conclusions: The ability to reduce GHG emissions in beef cattle depends on the cost of feed in the breeding objective of the production system. Multiple-trait selection will reduce emissions, while improving economic performance, if the cost of feed in the breeding objective is high. If it is low, greater growth will be favoured, leading to an increase in GHG emissions that may be undesirable.

Procedures are described for estimating selection index accuracies for individual animals and expected genetic change from selection for the general case where indexes of EBVs predict an aggregate breeding objective of traits that may or may not have been measured. Index accuracies for the breeding objective are shown to take an important general form, being able to be expressed as the product of the accuracy of the index function of true breeding values and the accuracy with which that function predicts the breeding objective. When the accuracies of the individual EBVs of the index are known, prediction error variances (PEVs) and covariances (PECs) for the EBVs within animal are able to be well approximated, and index accuracies and expected genetic change from selection estimated with high accuracy. The procedures are suited to routine use in estimating index accuracies in genetic evaluation, and for providing important information, without additional modelling, on the directions in which a population will move under selection.