A novel production profile classification system for incoming calves that predicts feedlot growth performance

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dc.contributor.author Hentzen, A.H.R.
dc.contributor.author Holm, Dietmar Erik
dc.date.accessioned 2024-08-06T09:17:30Z
dc.date.available 2024-08-06T09:17:30Z
dc.date.issued 2024-02 *
dc.description DATA AVAILABILITY : The data obtained in this study are stored in the University of Pretoria’s research data management platform (https://researchdata.up.ac.za/account/items/23929170/edit). en_US
dc.description.abstract CONTEXT : Mitigating financial risk in the feedlot environment is an ongoing occurrence, and good production is a key risk mitigator. However, production protocols are based on historic averages because of the inability to predict growth potential of incoming calves. Production profiling of individual incoming feeder calves could address these limitations. AIMS : The aim of this study was to establish criteria for optimal sorting of incoming feeder calves into various cattle groups in a feedlot that maximises feedlot profit. METHODS : South African feeder calves (n = 436) were classified into four production-profile (PP) categories according to a predetermined set of phenotypic traits: PP 3 (n = 72) representing feeder calves with the poorest feedlot growth potential, PP 2− (n = 191) with below-average potential, PP 2+ (n = 139) with above-average potential and PP 1 (n = 34) with above-average feedlot growth potential. After combining the data of PP 2− and PP 2+ into PP 2, mixed modelling of economically important feedlot growth traits (average daily gain (ADG), carcass ADG, and carcass exit weight) was performed to evaluate the effect of PP classification (PP 1 and PP 3), while adjusting for potential confounding effects such as starting weight (entry weight) and gender. KEY RESULTS : Carcass weights for calves with a PP classification of 3 and 1 were 15.54 kg less (P < 0.000), and 11.34 kg more (P = 0.007) respectively, than those with a PP classification of 2 (261.27 kg, 95% CI 257.94–264.57), after adjusting for entry weight, calf gender and the random effect of the feeding pen. Similar to carcass weight, calves with a PP 3 classification were outperformed by other classifications in all the measured traits (P < 0.05). CONCLUSIONS : This is the first report demonstrating the ability of subjective production-profile classification to predict growth performance of individual feeder calves. IMPLICATIONS : The opportunity of the PP classification system lies in value-based procurement of incoming feeder calves based on their growth potential at the start of the feeding period, and then to use technology to improve and finalise the current subjective PP classification system. en_US
dc.description.department Production Animal Studies en_US
dc.description.librarian hj2024 en_US
dc.description.sdg SDG-02:Zero Hunger en_US
dc.description.sponsorship The Technology Innovation Agency of South Africa (Department of Trade and Industry). en_US
dc.description.uri https://www.publish.csiro.au/an en_US
dc.identifier.citation Hentzen, A.H.R. & Holm, D.E. 2024, 'A novel production profile classification system for incoming calves that predicts feedlot growth performance', Animal Production Science, vol. 64, no. 3, art. AN23395, pp. 1-10, doi : 10.1071/AN23395. en_US
dc.identifier.issn 1836-0939 (print)
dc.identifier.issn 1836-5787 (online)
dc.identifier.other 10.1071/AN23395
dc.identifier.uri http://hdl.handle.net/2263/97447
dc.language.iso en en_US
dc.publisher CSIRO Publishing en_US
dc.rights © 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing. en_US
dc.subject Animal production en_US
dc.subject Cattle feedlot en_US
dc.subject Phenotype en_US
dc.subject Precision farming en_US
dc.subject Production profiling en_US
dc.subject SDG-02: Zero hunger en_US
dc.title A novel production profile classification system for incoming calves that predicts feedlot growth performance en_US
dc.type Postprint Article en_US


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