J. Dairy Sci. 106:9006–9015 https://doi.org/10.3168/jds.2023-23405 © 2023, The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association ® . This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Genetic parameters for feed intake and body weight in dairy cattle using high-throughput 3-dimensional cameras in Danish commercial farms Coralia I. V. Manzanilla-Pech, 1 * Rasmus B. Stephansen, 1 and Jan Lassen 1,2 1 Center for Quantitative Genetics and Genomics, Aarhus University, DK-8000 Aarhus, Denmark 2 Viking Genetics, Assentoft, 8960 Randers, Denmark ABSTRACT Recording complex phenotypes on a large scale is be- coming possible with the incorporation of recently de- veloped new technologies. One of these new technologies is the use of 3-dimensional (3D) cameras on commercial farms to measure feed intake and body weight (BW) daily. Residual feed intake (RFI) has been proposed as a proxy for feed efficiency in several species, including cattle, pigs, and poultry. Dry matter intake (DMI) and BW records are required to calculate RFI, and the use of this new technology will help increase the number of individual records more efficiently. The aim of this study was to estimate genetic parameters (including genetic correlations) for DMI and BW obtained by 3D cameras from 6,000 cows in commercial farms from the breeds Danish Holstein, Jersey, and Nordic Red. Ad- ditionally, heritabilities per parity and genetic correla- tions among parities were estimated for DMI and BW in the 3 breeds. Data included 158,000 weekly records of DMI and BW obtained between 2019 and 2022 on 17 commercial farms. Estimated heritability for DMI ranged from 0.17 to 0.25, whereas for BW they ranged from 0.44 to 0.58. The genetic correlations between DMI and BW were moderately positive (0.58–0.65). Genetic correlations among parities in both traits were highly correlated in the 3 breeds, except for DMI between first parity and late parities in Holstein where they were down to 0.62. Based on these results, we conclude that DMI and BW phenotypes measured by 3D cameras are heritable for the 3 dairy breeds and their heritabilities are comparable to those obtained by traditional meth- ods (scales and feed bins). The high heritabilities and correlations of 3D measurements with the true trait in previous studies demonstrate the potential of this new technology for measuring feed intake and BW in real time. In conclusion, 3D camera technology has the potential to become a valuable tool for automatic and Received February 21, 2023. Accepted June 8, 2023. *Corresponding author: cmanzanillap@gmail.com continuous recording of feed intake and BW on com- mercial farms. Key words: feed efficiency, 3-dimensional cameras phenotypes, dry matter intake, body weight INTRODUCTION Feed costs account for more than half of the total production cost of dairy cattle (Braae et al., 2021). Therefore, improving feed efficiency is a goal of the dairy industry. In the last decade, several countries, such as Australia, the Netherlands, the United States, and Canada, have included feed efficiency in their breeding goals (Pryce et al., 2015; CRV, 2022; Gaddis et al., 2021; Lactanet, 2021). Since 2020, the Nordic Cattle Genetic Evaluation ( NAV ) has included feed efficiency through the Saved Feed Index in the Nordic Total Merit Index (Lidauer et al., 2019; Stephansen et al., 2019). Residual feed intake ( RFI ) provides new information about feed efficiency beyond the existing traits. Feed efficiency is an important trait in all livestock species, including cattle, pigs, and poultry (Luiting, 1990; Berry and Crowley, 2013; Patience et al., 2015). Residual feed intake has many definitions; one widely accepted defini- tion (originally for growing animals) is the difference between actual and predicted feed intake after consider- ing variability in maintenance requirement and growth (Koch et al., 1963). For dairy cattle, Tempelman et al. (2015) defined RFI as an estimated residual derived from a multiple regression equation on energy sinks. Energy sinks usually include ECM, metabolic body weight, and body weight change. However, DMI and BW records used to calculate RFI are scarce, as they are labor intensive, expensive, and time consuming to measure. Currently, most DMI records are only avail- able for research and nutrition experiments, mainly for the first and second lactation, and in many cases, only for a part of lactation (e.g., from 50 to 150 DIM). Some studies have shown the importance of recording DMI during the entire lactation (Manzanilla-Pech et al., 2014a,b; Li et al., 2016) and in multiple lactations (Khanal et al., 2022) to properly account for the ge- 9006
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