The use of 3-dimensional imaging of Holstein cows to estimate body weight and monitor the composition of body weight change throughout lactation

Abstract

Three-dimensional (3D) imaging offers new possibilities in animal phenotyping. Here, we investigated how this technology can be used to study the morphological changes that occur in dairy cows over the course of a single lactation. First, we estimated the individual body weight (BW) of dairy cows using traits measured with 3D images. To improve the quality of prediction, we monitored body growth (via 3D imaging), gut fill (via individual dry matter intake), and body reserves (via body condition score) throughout lactation. A group of 16 Holstein cows-8 in their first lactation, 4 in their second lactation, and 4 in their third or higher lactation-was scanned in 3D once a month for an entire lactation. Values of morphological traits (e.g., chest depth or hip width) increased continuously with parity, but cows in their first lactation experienced the largest increase during the monitoring period. Values of partial volume, estimated from point of shoulder to pin bone, predicted BW with an error of 25.4 kg (R 2 = 0.92), which was reduced to 14.3 kg when the individual effect of cows was added to the estimation model. The model was further improved by the addition of partial surface area (from point of shoulder to pin bone), hip width, chest depth, diagonal length, and heart girth, which increased the R 2 of BW prediction to 0.94 and decreased root mean square error to 22.1 kg. The different slopes for individual cows were partly explained by body condition score and morphological traits, indicating that they may have reflected differences in body density among animals. Changes in BW over the course of lactation were mostly due to changes in growth, which accounted for around two-thirds of BW gain regardless of parity. Body reserves and gut fill had smaller but still notable effects on body composition, with a higher gain in body reserves and gut fill for cows in their first lactation compared with multiparous cows. This work demonstrated the potential for rapid and low-cost 3D imaging to facilitate the monitoring of several traits of high interest in dairy livestock farming.

The high fertility cycle

“…Future studies to assess management strategies for feeding cows during lactation ( Boerman et al, 2015 ) or the dry period (or both) ( Beever, 2006 ; Daros et al, 2021 ) to manage BCS and for differentially grouping cows based on BCS targets are needed to determine how to better manage BCS throughout lactation. Although BCS scoring is easily performed by properly trained personnel on dairy farms, emerging technologies involving 3-dimensional imaging systems ( Xavier et al, 2022 ) and digital camera imaging systems ( Mullins et al, 2019 ) may soon automate this task and provide a more frequent and uniform measure of BCS in dairy cows. Future randomized, controlled experiments are needed to causally link these relationships between BCS change and fertility and health events in lactating dairy cows.…”

Identifying the Most Important Linear Body Depth Traits Associated with Milk Yield in Dairy Cattle

“…In addition, CHD is also positively linked with BCS and heart girth (LE COZLER et al 2019b). The higher the parity number, the deeper this region, mainly in the first lactation period (XAVIER et al 2022). Then, a deeper cavity in this area leverages the broader level in the pleural cavity; consequently, lung expansion is easier (GELAYE et al 2022).…”

One-shot technology for three-dimensional imaging of large animals: perspectives for ruminant management

“…From these indicators, it then becomes possible to estimate body weight (BW) in both adults and young animals ( Le Cozler et al, 2019a , 2022b ; Wang et al, 2023 ). We have also shown that information from 3D-imaging technology can be used to study the nature of weight gain during lactation ( Xavier et al, 2022a ), but also to estimate the chemical composition of animals ( Xavier et al, 2022b ). For these earlier studies, we used an imaging device called “Morpho3D,” which is very accurate but requires specific conditions of use that are not always easy to obtain, including the absence of direct light and a complete lack of movement by the animals while recording images (5-s acquisition time).…”