ACE Expo '99

THE USE OF COMPUTERS IN DAIRY NUTRITION
The Consultants Point of View

Charles E. Gardner, DVM, MBA
Director of Animal Health and Herd Economics
Keystone Agway
6213 Vista Terrace, Orefield, PA 18069
610-395-7210

Introduction

Computers are used for two distinct functions in dairy nutrition. The first is to formulate rations and prepare feeding charts. The second is to store, manipulate, retrieve, and transmit information. This information is then used by the owner and his consultants to make decisions about future feeding programs. Computers can process large volumes of data very quickly. However, for the results to be meaningful, accurate data must be entered on a consistent basis. Inaccurate information is worse than no information. This paper will summarize the facts that I need to know in order to evaluate the nutrition program on a dairy farm.

While computers provide objective, numerical data, I also need subjective information that requires me to visit the farm. Body condition, hair coats, cud chewing, forage preservation, stall maintenance, bunk conditions, and employee attitudes are all factors which impact herd performance. Numbers alone cannot give me a complete picture, and computer printouts cannot totally replace the need to walk the farm.

Milk Production And Components

Milk production is the most frequently used measurement of the nutrition program. It is most helpful to know production of fresh cows and heifers (< 30 days in milk), as well as production of cows and heifers near peak output (31 - 90 d.i.m.). If animals are starting out poorly, their entire lactation is harmed. Heifers often suffer more than cows from over crowding or other stresses, so having information on them, as a separate category is very helpful. Poor performance of fresh animals dictates examination of dry and pre-fresh diets, as well as the post calving ration. If milk output of peak animals is sub-par, then the components and handling of that ration must be re-evaluated.

Beyond early lactation, persistency reports tell me if cows are maintaining their production potentials. Group changes can sometimes cause inappropriate drops in production. Forage changes, improper mixing, empty bunks, overcrowding, and disease problems can all impact milk production. The absolute and relative levels of butterfat, protein, and urea nitrogen give a good indication of rumen digestion, reflecting ration levels of fiber, non-structural carbohydrates, and protein forms.

Reproductive Data

The standard DHI reproductive parameters are still meaningful, and I like to know them. Days To First Breeding and Days Between Breedings provide information about estrus detection. Timed insemination programs, such as Ovsync, can be used to lower these values if excessive. Services Per Conception reflects fertility. Care must be taken to know if it applies to all cows, or only pregnant cows. If the number is high, it suggests excessive weight loss in early lactation cows. Trace mineral or vitamins could also play a role. The possibility that cows are being inseminated when not in heat can be investigated using milk progesterone testing.

I like to know accurate numbers of eligible cows detected in estrus during a specific time period, and a true conception rate, based on number of breedings and number of resulting pregnancies. These values can be generated with on farm computers immediately after pregnancy exams are done, but only for those animals that had been bred long enough to be examined. The heat detection rate multiplied by the conception rate will give us the pregnancy rate. A goal is 35% per 21-day time frame. On most farms, a timed insemination program is needed to artificially raise the heat detection rate to a level that can subsequently yield a 35% pregnancy rate.

Culling

Culling rate and the reasons behind culling has a huge impact on herd profit. DHI data often does not reflect culling policies. For example, a producer who culls opens cows very aggressively may maintain a low calving interval, despite significant breeding problems. Cows being culled for chronic lameness serve as a red flag for rumen acidosis, while excessive culling of early lactation animals directs our attention to dry cow and springer programs.

Feed Intake

All feeding programs are based on some level of dry matter intake. If the actual intake does not match the program, then nutrient intake is not what is expected. This is one of the most common reasons for poor results. I ask for dry matter intake on all groups of animals being fed, but seldom get better than rough estimates. Computers certainly lend themselves to tracking amounts fed and refusals collected. If the dry matter of the ration is known, then the rest is simply math, which of course computers do best.

Once feed intake in known, then we can also calculate dry matter intake per hundredweight of milk. This is an efficiency number seldom considered on dairy farms, yet it has a huge impact on profit. For example, corn silage that has fermented for only two weeks usually requires high dry matter intake per cwt. of milk, compared to fully fermented material. The magnitude of this effect has led to the practice of making enough corn silage so that new crop is not needed until late in the year.

When feed intake in known, we can easily calculate feed costs per cwt. of milk, and income over feed costs. These values should always be considered when adding expensive ingredients to a ration.

Summary

The set of information listed above allows me to have an accurate picture of all phases of herd performance affected by nutrition. In order to be valuable to the producer, I must interpret all of this data, and then make sound recommendations. The producer makes the final decisions, and implements changes as needed. If no decisions are made, or if no change occurs when needed, then all the effort of gathering and analyzing data is wasted.