Key Factors Affecting Automated Milking System Performance

Abstract Text: Automatic or robotic milking systems (AMS) are being adopted by dairy producers in the upper Midwest at a relatively fast rate. AMS allow farmers to milk more cows with less labor and have an improved lifestyle. We collected data from 52 AMS dairy farms in Minnesota and Wisconsin to describe characteristics of AMS systems and investigate factors that may influence AMS efficiency. Farms were visited once to collect information and daily data from the AMS was remotely collected for approximately 18 months. Farms had 2.6 ± 1.6 AMS/farm, with a range or 1 to 8 AMS/farm. These data showed that on average, cows were milked 2.6 ± 0.3 times per day, produced 32.3 ± 6.8 kg of milk per day, and consumed 5.03 ± 0.95 kg of concentrate in the AMS per day. Free flow systems fed more concentrate through the AMS than guided flow systems. A survey of nutritionists working with these farms showed that in free flow herds the partial mixed ration (PMR) was balanced for milk production levels of 4.5 to 13.6 kg less than the herd’s average production. For guided flow herds the PMR was balanced for 4.1 to 9.1 kg less than the average of the herd. Feeding management is suggested to be one of the major factors for success in AMS. Nutritionists ranked palatability of the pellet and consistency of the PMR as two keys for feeding success. The number of cows per robot box was 70.3 ± 14.1 and it was greater for guided flow compared to free flow farms. Milking speed was 2.24 ± 0.40 L/min and total milk yield per robot unit was 1843.5 ± 490.9 L/day. Total daily milk yield per robot has been suggested to be an important characteristic to assess the efficiency of AMS. An analysis showed that the factors most strongly associated with yield per robot (P < 0.001) were milk per cow per day (r = 0.81) and average milking speed (r = 0.76). Other factors moderately associated (P < 0.001) with yield per robot were average concentrate consumed per day (r = 0.31) and exit length from the AMS (r = 0.32). Further multilevel regression analysis will provide a clearer picture of factors influencing efficiency of AMS in the US.

Keywords:  dairy cattle, automatic milking system, robot