Research updates on robotic milking
Research and data are still scarce on the topic of robotic milking economics and management, especially in North America. Here is a summary of three new studies that were published in the Journal of Dairy Science this year.
Two studies, conducted by a team of veterinarians at UW-Madison (Tremblay et al., 2016a and 2016b) in collaboration with Lely, analyzed four years of data (2011-2014) collected from Lely Astronaut automatic milking systems (AMS) on 529 farms in Canada and the Midwestern and Eastern U.S. About a third of the herds were in the U.S. One study looked at what variables explained the observed differences in milk production per cow (or per robot) per day, and the other divided those 529 farms into 6 groups and derived group-specific benchmarks and recommendations.
The first study found that 1) the free-traffic design was associated with 1.1 kg per cow per day higher milk output compared to the guided-traffic design, 2) those who retrofitted their facilities with AMS had a slightly lower milk output in the first three years compared to those who constructed new facilities, 3) U.S. producers had a slightly higher milk output than Canadian producers who were under a production quota system, 4) higher milk production per cow was associated with fewer milking refusals, milking failures, and connection attempts; a lower rate of non-dispensed feed concentrate over projected allowances; higher milking speeds; more milkings per day; and more box time in the AMS. Additionally, one may note that successful producers achieved higher production per cow with more cows per robot than the average, indicating a greater ability to manage overcrowding with the AMS. Milking more cows per robot helps spread the cost of large capital investment associated with AMS and hence contributes to higher income.
The second study recommended 1) for those with breeds other than Holsteins, adjust AMS settings according to the breeds’ characteristics, 2) for those with the guided-traffic design, consider switching to the free-traffic design or coming up with better gate solutions, 3) those in the most northern regions with limited feed availability should consider additional automatic feeding stations outside robots, 4) for those with a single robot per pen, minimize the robot’s downtime by preventing dominant cows from crowding the robot and blocking timid cows’ access, 5) those with relatively high production per animal should fine-tune the settings to decrease milking failures which will reduce the risks of milk leakage and mastitis, and 6) for those operating in Canada under the quota system, focus on optimizing efficiency in milk production and resource use. That was the gist of the researchers’ interpretation of the results and recommendations, while those groups were more loosely defined based on the similarities in producer characteristics and robots’ performance measures. The authors’ point is to derive group-specific statistics and customized benchmarks for AMS variables that are adjusted for varying circumstances of individual producers.
The third study (Shortall et al., 2016) presented AMS budget simulations from Ireland. Focusing on pasture-based, low-cost dairy production prevalent in their country, the Ireland researchers simulated farm budgets under the scenarios of AMS, medium-technology parlors, and high-technology parlors at 70-cow and 140-cow herd sizes. The profitability over a 10-year time horizon was similar between AMS and high-tech parlors, which had lower profitability compared to medium-tech parlors. Medium-tech parlors were more profitable than AMS by 74% and 24% at the 70-cow and 140-cow herd sizes, respectively. That 24% difference at the 140-cow herd size would shrink with additional assumptions like wage inflation, tax deductions on interests and depreciations, and improved quality of life through reduced manual labor and added flexibility in work schedule. More interestingly, observe how business environments differ in Ireland: 11,000 pounds per cow milk production, €12.5 per hour ($14 per hour) labor wage (at €1 = $1.12), €195,000 ($218,000) investment for two AMS units with €60,000 ($67,000) infrastructure cost, and €135,000 ($150,000) investment for 20-unit herringbone high-tech parlors with €110,000 ($123,000) infrastructure cost. Yes, two robots for $218,000! Apparently, low-cost AMS and milking parlors exist in Ireland. The authors used the average prices of milking systems obtained from manufactures and suppliers. When I contacted the corresponding author, he noted the highly competitive AMS market in Ireland where Lely, De Laval, and Fullwood Packo compete to establish their market shares.
As one might guess, all budget simulations are subject to assumptions. We encourage those considering a new milking system to try out the University of Minnesota Dairy Extension’s online tool. Given the current economic environment in the U.S., robots are increasingly becoming competitive with conventional parlors. The bottom line for the choice between robots and parlors is to know which one you are better at managing, machines or humans.
Shortall, J., L. Shalloo, C. Foley, R.D. Sleator, and B. O’Brien. 2016. Investment appraisal of automatic milking and conventional milking technologies in a pasture-based dairy system. Journal of Dairy Science. 99:7700–7713.
Tremblay, M., J.P. Hess, B.M. Christenson, K.K. McIntyre, B. Smink, A.J. van der Kamp, L.G. de Jong, and D. Döpfer. 2016a. Factors associated with increased milk production for automatic milking systems. Journal of Dairy Science. 99:3824–3837.
Tremblay, M., J.P. Hess, B.M. Christenson, K.K. McIntyre, B. Smink, A.J. van der Kamp, L.G. de Jong, and D. Döpfer. 2016b. Customized recommendations for production management clusters of North American automatic milking systems. Journal of Dairy Science. 99:5671–5680.