“There is one employee on many farms who is often overlooked but may be the most important person on any dairy farm…it’s the feeder” (Dyk 2011).
Paul Dyk, a University of WI extension agent, helped design a multiday training program to teach feeders the basics of dry matter, sampling forages, feed mixing, safety, quality control, and inventory management. Dyk is well aware of the importance of feed management in an operation’s profitability. The lack of training protocols and programs available to feeders prompted him to help create this program.
Over 70 feeders in northeast Wisconsin participated in the program during 2009 and 2010. Dyk identified two groups of feeders during the course that had very different needs:
1. 70% – Experienced and seasoned English-speaking employees.
2. 30% – Spanish-speaking employees with limited feeding experience.
Dyk identified seven areas that deserve attention to make feeders the best feeders:
- “The basics are important.” Feeders must understand the fundamentals of dry matter and proper forage sampling.
- “Managing bags is difficult.” More “how to” information should be made available to help feeders unload bags properly.
- “Taking feed out of a bunker is not the same as putting it in.” There needs to be new protocols for safely removing plastic and tires.
- “Mixing feed is not like the Betty Crocker cookbook.” Feeders are interested in topics such as mixer run time, tractor RPM, ingredient order, etc., and more resources should be developed to assist them in these areas.
- “Weekend feeders are to blame for everything that goes wrong.” This statement is not 100% true but may appear to be because weekend feeders often do not receive as much training as regular feeders.
- “Computers don’t solve all problems.” Software is valuable as far as adjusting dry matter and monitoring shrink, but it does not train feeders on everything they need to know, i.e. removing tires from bunkers, maintaining a mixer, etc.
- “Dry matter intake is still a mystery.” Calculating DMI accurately is essential to predicting and preventing problems in feed management and could reveal changes in forage DM, forage quality, mixing errors, etc.