Investigating the genetic background of novel behavioral indicators of robotic milking efficiency in North American Holstein cattle

The adoption of automated milking systems (AMS) across worldwide dairy farms has grown considerably over the last few decades. Automated milking systems contribute to reducing labor costs, increasing milk performance, improving cow welfare, and generating large-scale data on a routine basis that can be used for deriving novel traits for breeding purposes. Therefore, the primary objectives of this study were to (1) derive behavioral traits from AMS data and assess their phenotypic variability during lactation in US Holstein cattle, and (2) estimate variance components and genetic parameters for these traits. Daily AMS records from 5,645 US Holstein cows, collected at 36 robotic milking stations between 2018 and 2021, were analyzed. Evaluated traits included average milking time (AMT, min), total milking time (TMT, min), time interval between milkings (INT, h), number of attempted visits to the AMS (NoV), number of successful entries within the AMS (NSE), percentage of successful milkings (PSM, %), and cow preference consistency score (PCS, score unit). Variance components and genetic parameters were estimated using repeatability models with the restricted maximum likelihood method. The heritability estimates were similar between the 2 models for most traits: 0.46 versus 0.46, 0.27 versus 0.28, 0.08 versus 0.10, 0.10 versus 0.10, 0.10 versus 0.11, and 0.05 versus 0.06, for AMT, TMT, INT, NoV, NSE, and PSM, respectively. However, a notable difference was observed for PCS, with heritability estimates of 0.09 and 0.24 depending on the model fitted. The SE for the heritability ranged from 0.001 to 0.03. Repeatability estimates were 0.74 to 0.71 (AMT), 0.52 to 0.49 (TMT), 0.34 to 0.27 (INT), 0.29 to 0.25 (NoV), 0.29 to 0.30 (NSE), 0.20 to 0.18 (PSM), and 0.55 to 0.53 (PCS). Positive genetic correlations were observed for trait pairs AMT-PSM (0.38–0.35), INT-PSM (0.71–0.64), INT-PCS (0.50–0.40), and PSMPCS (0.37), whereas other correlations were unfavorable or near zero. All cow behavioral traits related to AMS efficiency evaluated in this study were found to be heritable, suggesting that their inclusion in selection schemes could contribute to improving dairy cow milking efficiency and welfare in dairy farms using AMS. Future studies will model these traits using random regression models and estimate their genetic correlation with other relevant traits in dairy breeding programs.