Robots and feed
By Laura Zagorski
As the trend of automation continues to rise in the dairy industry, so does the popularity and interest in robotic milking systems. Robotic milking systems can provide new opportunities in herd management.
By Laura Zagorski
As the trend of automation continues to rise in the dairy industry, so does the popularity and interest in robotic milking systems. Robotic milking systems can provide new opportunities in herd management.
One area in particular that receives a great deal of attention in the success of robotic milking systems is nutrition. In a free-flow traffic situation, well-balanced rations, quality pellets and appropriate feed tables are all driving factors in promoting visits to the milking robots.
Partial mixed ration
At the foundation, your nutritionist should formulate a partial mixed ration (PMR). The PMR should be formulated below the production level of the herd. A good rule of thumb is to target 15 pounds below the herd’s average production. This is a starting point and will change as herd dynamics or level of management changes.
This is where forage will be fed along with ingredients that may not be palatable or feasible in a pellet, such as fat, minerals or animal proteins. Additional key factors in formulating the PMR include dialing into and accurately monitoring dry matter intakes (DMI) at the feedbunk. Furthermore, it is important to recognize that both bulk fill and energy density that is too high can detrimentally affect milkings per cow.
Robot pellet
Once the PMR is dialed in, it must be complemented with a high-quality pellet. A good robot pellet should be palatable, durable and free of fines. Pellets should be made with palatable ingredients that will bind well with minimal fracture points. When a pellet durability index (PDI) is available, the goal should be a measurement of 90 PDI or greater. PDI is a test that feed manufacturers can use to provide feedback on the strength of the pellet. It is a measurement that runs on a scale of 0 to 100. Pellets are put into a tumbler, which simulates stress, and the fines are sifted out. The percent of the pellets that remain on the top of the screen is the resulting PDI. Wheat middlings make a great base for achieving a high PDI.
Finally, starch fermentability should be well-balanced in the pellet. Sources may vary depending on available forage and concentrate sources available on the farm.
Feeding tables
Farm nutritionists should have access and input into developing the programmed pellet feeding tables. These feed tables are what calculate the rate pellets are consumed when a cow enters the box. Feed tables can be split by days in milk (DIM), production levels or groups within the herd to provide the optimal amount of pellets to each individual cow. Some common considerations include evaluating the need for a separate feed table for first-lactation cows, ensuring that pellet availability supports fresh and peak performance, and reducing pellets allotted to late-lactation cows.
Other management considerations
Further management strategies that are vital for robotic success include a consistent, regular feed pushing schedule. This can be done well with a robotic feed pusher. Also, forage analyses and dry matter adjustments should be looked at on a consistent, regular basis. Because the nutrition program largely influences cow traffic to the robot, the feeder should be on top of any possible change to the PMR. A feeder should have the ability to precisely monitor feed refusals and make appropriate adjustments.
With robotic technology, farms have the unique ability to feed cows based on their individual needs. Robot software can provide bountiful information to evaluate the success of the farm’s nutrition program. By keeping some of these things in mind, you can successfully make the most of your investment in automation.
This article was originally written for the Progressive Dairyman Extra enewsletter on March 30, 2017.
About the author: Laura Zagorski is a Vita Plus Gagetown dairy specialist. She earned a bachelor’s degree in animal science from Michigan State University. She works closely with farms in Michigan’s Thumb, offering customized nutrition solutions and technical expertise to those dairy producers.
Category: |
Dairy Performance Equipment Technology and data management |