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Context Feedlotting lambs has the potential to considerably increase the efficiency of lamb production in Australia. Many producers have turned to grain-finishing lambs to capitalise on high lamb prices and, due to the perceived profitability of this practice, further research to improve production has not been prioritised. Lambs are, however, difficult to adapt to a predominantly grain-based diet, often resulting in highly variable feed intake and growth rates. Aims The aim of this survey was to investigate the apparent growth rates and feed conversion ratios of lambs in current feedlotting enterprises. A secondary aim was to identify research priorities that could improve feedlot production efficiency. Methods A cross-sectional survey was conducted between February and May 2020 among Australian lamb producers, with the target population being lamb producers using feedlots to finish lambs. Producer responses from 59 current lamb feedlotters were collated and analysed. Key results The most frequently reported growth rates were between 300 and 350 g/day, and most respondents reported a feed conversion ratio of 5:1. The incidence of shy feeders was a median of 3.5% and mortality was a median of 1%, with acidosis reported as the major contributor to mortality. Conclusions The results of the current survey indicate that for the majority of responding producers, lamb growth rates and feed conversion ratios are consistent with those predicted by the nutrient requirements of domesticated ruminants (CSIRO 2007), and improvements in production are unlikely without significantly increasing nutrient intake. Shy feeders, acidosis and the intake of lowly digestible feeds are the clear limitations to production efficiency. Implications Research to improve productivity of lambs in feedlots needs to prioritise the implementation of feeding strategies that minimise social and nutritional issues, and promote maximum intake of nutrients.

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Metabolizable energy intake is the key determining factor for the expression of an animal’s genetic potential for growth, and current predictive growth models are not capable of accounting for all the nutritional variation that is commonly observed. The current study was designed to investigate energy transactions as lambs grow using CT scanning to assess body compositional changes at two levels of intake and two stages of maturity, and compare results to predictive equations. A pelleted diet was provided to cross-bred lambs (n=108) at approximately 2.5 and 3.5% of liveweight (LW) in dry matter when the lambs were approximately four (31.8 ± 0.3 kg LW) and eight (40.5 ± 0.3 kg LW) months of age. A digestibility trial was run sequentially using 10 lambs of the same genetic and nutritional history fed at the same feeding levels to determine the digestibility of the diet. In the first feeding period, metabolizable energy intake was 15.3 ± 0.03 and 9.5 ± 0.03 MJ ME/d for high and low feeding levels respectively, resulting in higher rates of empty body gain for high feeding level lambs (197.7 ± 7.8 v. 72.8 ± 8.2 g/d; P<0.001). In the second feeding period, metabolizable energy intake was 15.2 ± 0.01 and 12.0 ± 0.01 MJ ME/d for high and low feeding levels respectively, resulting in higher rates of empty body gain for high feeding level lambs (176.3 ± 5.4 v. 73.9 ± 5.3; P<0.001). Lambs at later stages of maturity retained proportionately more energy as fat for every unit of retained energy compared to younger lambs (95.4 ± 0.40 v. 90.0 ± 0.42%; P<0.001). Lambs fed the lower feeding level in period two also retained proportionately more energy as fat for every unit of retained energy than lambs at the higher feeding level (97.1 ± 0.36 v. 94.0 ± 0.37%; P<0.001) which is hypothesised to be because of the rapid response of visceral lean tissue to changes in nutrition. There were no significant interactions between treatments in the first and second feeding periods, indicating an absence of a compensatory gain response to a nutritional restriction in the first feeding period. This experiment highlights the significance of a changing feed supply and the subsequent effects on body composition and the partitioning of energy to lean and fat tissue deposition. For improvements in the accuracy of predictive ruminant growth models it is necessary to gain a greater understanding of the different tissue responses over time to changes in nutrition.

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