O5 Predicting the efficiency of utilisation of energy for maintenance (km) or gain (kg) for sheep and cattle from feed quality components

E H Clayton; J W Oltjen; M Evered; V H Oddy

doi:10.1016/j.anscip.2022.07.015

Abstract

In the current Australian feeding standards for ruminants (CSIRO, 2007) the metabolisablecff energy intake (MEI) required for maintenance (MEm), where retained energy (RE) is zero, is estimated from fasting heat production (FHP) and the efficiency of utilisation of energy for maintenance (km). The efficiency of utilisation of energy for gain (kg) is estimated from the regression of RE:MEI at all levels of feeding (LoF). As FHP is affected by prior LoF, the accuracy of prediction of km and kg relies on feeding at maintenance prior to measurement. The UK feeding system (ARC, 1980) uses fixed values of km and kg for different feedstuffs. The Australian system predicts efficiencies from the energy density (M/D, MJ/kg DM) of the diet (km = 0.02 × M/D + 0.5, kg = 0.043 × M/D), however, it is unclear where the data used to derive these relationships was obtained. Therefore, the aim of the current study was to determine the relationship between km or kg and M/D or other proximate analysis components using data obtained from in vivo calorimetry studies

Original language	English
Pages	248-249
DOIs	https://doi.org/10.1016/j.anscip.2022.07.015
Publication status	Published - 31 Aug 2022
Event	ISEP 2022: 7th EAAP International Symposium on Energy and Protein Nutrition (ISEP) - Granada, Spain Duration: 12 Sept 2022 → 15 Sept 2022

Other

Other	ISEP 2022: 7th EAAP International Symposium on Energy and Protein Nutrition (ISEP)
City	Granada, Spain
Period	12/09/22 → 15/09/22

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10.1016/j.anscip.2022.07.015

https://hdl.handle.net/1959.11/58983

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Clayton, E. H., Oltjen, J. W., Evered, M., & Oddy, V. H. (2022). O5 Predicting the efficiency of utilisation of energy for maintenance (km) or gain (kg) for sheep and cattle from feed quality components. 248-249. Abstract from ISEP 2022: 7th EAAP International Symposium on Energy and Protein Nutrition (ISEP), Granada, Spain. https://doi.org/10.1016/j.anscip.2022.07.015

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title = "O5 Predicting the efficiency of utilisation of energy for maintenance (km) or gain (kg) for sheep and cattle from feed quality components",

abstract = "In the current Australian feeding standards for ruminants (CSIRO, 2007) the metabolisablecff energy intake (MEI) required for maintenance (MEm), where retained energy (RE) is zero, is estimated from fasting heat production (FHP) and the efficiency of utilisation of energy for maintenance (km). The efficiency of utilisation of energy for gain (kg) is estimated from the regression of RE:MEI at all levels of feeding (LoF). As FHP is affected by prior LoF, the accuracy of prediction of km and kg relies on feeding at maintenance prior to measurement. The UK feeding system (ARC, 1980) uses fixed values of km and kg for different feedstuffs. The Australian system predicts efficiencies from the energy density (M/D, MJ/kg DM) of the diet (km = 0.02 × M/D + 0.5, kg = 0.043 × M/D), however, it is unclear where the data used to derive these relationships was obtained. Therefore, the aim of the current study was to determine the relationship between km or kg and M/D or other proximate analysis components using data obtained from in vivo calorimetry studies",

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doi = "10.1016/j.anscip.2022.07.015",

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Clayton, EH, Oltjen, JW, Evered, M & Oddy, VH 2022, 'O5 Predicting the efficiency of utilisation of energy for maintenance (km) or gain (kg) for sheep and cattle from feed quality components', ISEP 2022: 7th EAAP International Symposium on Energy and Protein Nutrition (ISEP), Granada, Spain, 12/09/22 - 15/09/22 pp. 248-249. https://doi.org/10.1016/j.anscip.2022.07.015

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T1 - O5 Predicting the efficiency of utilisation of energy for maintenance (km) or gain (kg) for sheep and cattle from feed quality components

AU - Clayton, E H

AU - Oltjen, J W

AU - Evered, M

AU - Oddy, V H

PY - 2022/8/31

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N2 - In the current Australian feeding standards for ruminants (CSIRO, 2007) the metabolisablecff energy intake (MEI) required for maintenance (MEm), where retained energy (RE) is zero, is estimated from fasting heat production (FHP) and the efficiency of utilisation of energy for maintenance (km). The efficiency of utilisation of energy for gain (kg) is estimated from the regression of RE:MEI at all levels of feeding (LoF). As FHP is affected by prior LoF, the accuracy of prediction of km and kg relies on feeding at maintenance prior to measurement. The UK feeding system (ARC, 1980) uses fixed values of km and kg for different feedstuffs. The Australian system predicts efficiencies from the energy density (M/D, MJ/kg DM) of the diet (km = 0.02 × M/D + 0.5, kg = 0.043 × M/D), however, it is unclear where the data used to derive these relationships was obtained. Therefore, the aim of the current study was to determine the relationship between km or kg and M/D or other proximate analysis components using data obtained from in vivo calorimetry studies

AB - In the current Australian feeding standards for ruminants (CSIRO, 2007) the metabolisablecff energy intake (MEI) required for maintenance (MEm), where retained energy (RE) is zero, is estimated from fasting heat production (FHP) and the efficiency of utilisation of energy for maintenance (km). The efficiency of utilisation of energy for gain (kg) is estimated from the regression of RE:MEI at all levels of feeding (LoF). As FHP is affected by prior LoF, the accuracy of prediction of km and kg relies on feeding at maintenance prior to measurement. The UK feeding system (ARC, 1980) uses fixed values of km and kg for different feedstuffs. The Australian system predicts efficiencies from the energy density (M/D, MJ/kg DM) of the diet (km = 0.02 × M/D + 0.5, kg = 0.043 × M/D), however, it is unclear where the data used to derive these relationships was obtained. Therefore, the aim of the current study was to determine the relationship between km or kg and M/D or other proximate analysis components using data obtained from in vivo calorimetry studies

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Y2 - 12 September 2022 through 15 September 2022