USING DHI RECORDS TO MANAGE THE DAIRY HERD

DAIRY HERD IMPROVEMENT
1985

APPLEMAN, R., & NOBLE, J.
VOLUME: NCDHIP HANDBOOK

Dairy producers manage cattle, land, labor and capital. Management
is conducting, controlling and directing the dairy farm operation,
and records are necessary to determine where you are, where you
want to go and how you get there.

Good decisions are based on good supporting information. The value
of information ultimately is measured by the value of a change
resulting from using the information, minus the cost of obtaining
the information. Modern management information systems have five
decision support components (Conlin, 1985):

1. Performance goals. Information defining goals by the producer
and providing a basis for identifying expectations and measuring
progress. The Extension Service has been very helpful in
summarizing data and providing standards for dairy producers to
use.

2. Descriptive information. Information describing "what is". The
majority of the information in Dairy Herd Improvement (DHI) records
is descriptive.

3. Diagnostic information. Information describing "what is
wrong", which helps managers identify strengths and weaknesses in
their operations. DHI records provide some diagnostic information,
such as conception rates, length of dry period and subclinical
mastitis.

4. Predictive information. Information describing "what if". This
is a process of looking into the future and exploring the impact of
proposed alternatives. Although DHI records lack predictive
capabilities, using DHI data and onfarm microcomputers provides the
opportunity to test alternatives.

5. Prescriptive information. Information describing "what should
be" that identifies a plan for the future. One example of a
prescriptive application is the computer controlled feeding system
that allocates feed to individual cows automatically, based on
level of milk production, age of cow, stage of gestation and other
factors. Undoubtedly, DHI information will be used more frequently
in the future.

Use of DHI Records

The DHI program has become a management oriented program. When the
information is properly used, there is a tremendous economic return
from the investment required to obtain the records. For example, in
Minnesota, income over feed costs in herds achieving 17,000 pounds
of milk per cow annually is $800 per year more than that for the
average cow in a nontested herd.

New York researchers found that profits for DHI-tested herds
increased over time; the more years the herd was enrolled, the
greater the benefits (McCaffree, 1974a, 1974b).

While DHI information is of value to those dairy producers selling
breeding stock, that is not a primary purpose. In a 1976
Pennsylvania study, only 29 percent of the participating dairy
farmers indicated that to be the primary reason for membership
(Croyle, 1976). Since then, most DHI programs have added new
features and provide more services.

In an Ohio study over two-thirds of the survey respondents listed
receiving monthly progress reports as a very important reason for
participating in DHI (see Table 1) (Smith, 1985). The ability to
feed according to production and to use action or management lists
(for example, cows to breed, calve and cull) was more important to
DHI users than the use of production records for advertising and
sale of breeding stock.

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PLEASE NOTE: THE FOLLOWING TABLE IS WIDER THAN THE SCREEN. USE THE
RIGHT ARROW KEY TO VIEW THE RIGHT SIDE OF THE TABLE. TO
PRINT THE ENTIRE TABLE YOU MUST FIRST EXPORT THE TABLE
AND USE A WORD PROCESSOR OUTSIDE THE RETRIEVAL SYSTEM.
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TABLE 1. Response to questions about reasons for participating in a DHI program.

Response (percentage of total responding)
Very Somewhat Not
Reason for being on test(a) important Important important important None

To have monthly progress 67.4 26.5 4.2 1.1 0.8
reports on how my herd
is doing.

To be able to feed according 50.6 30.9 10.3 6.7 1.5
to production.

To have lists of cows to 40 25.9 20.8 12.1 1.2
breed, calve, cull, etc.

"Good" dairy farmers use 33.6 29.1 15.9 17.7 3.7
DHI records.

Production records for 41.5 14 11.5 28.8 4.2
purebred sales and
advertising.

My lender requires it. 2.1 6.1 10.4 72.6 8.8

(a) Listed in order of ranked response, based on total derived from the
Very Important and Important columns. Source: Smith, 1985

Every dairy manager uses DHI records differently and for different
reasons. The key is to make the most productive use of the
information-where and when needed. To use DHIA information
effectively, the producer must break the information into three
segments: volatile test-day information, intermediate information
and long-term information.

Volatile test-day information allows the farmer to make decisions
on grouping, feeding, breeding, drying off and selling dairy cows.
Here simple calculations are performed---for example, 30 days x
milk weight x a factor. These data, along with previous milk
yields, will provide the information needed to calculate energy
required, totals to date, days in milk and other data. This
information is useless if not available within 2 days.

Intermediate information includes lactation to date for all
components, mature equivalent (ME) production, persistency,
mastitis screening and income to date information. This information
allows the producer to evaluate monthly performance of management,
feeding program, breeding performance, monthly production
performance, and the effect of short-term management adjustments.

Long-term information allows analysis to be made within herd and
across herds. This information is generated by analyzing large
amounts of data and allows the manager to compare and evaluate
different management techniques such as dry period evaluation,
culling program, services/ conception, lactation curves, long-term
feeding effect, genetic progress evaluation and sire summaries. The
researchers, Extension personnel, breed associations and AI
organizations help DHI users use this information effectively.

A Minnesota study identified six management traits that contribute
significantly to increased milk production per cow (Appleman,
1985). They were, in order of importance: a) mastitis control, b)
nutrition, c) recordkeeping and records utilization, d)
reproductive management, e) genetics (sire selection) and f) cow
culling. These six factors accounted for nearly 40 percent of all
variation in rolling herd averages among 2,674 Minnesota Holstein
herds.

The authors concluded that no single factor was an overriding
influence (Appleman, 1985). Those farmers that were above average
in all or most of the six primary traits marketed more milk than
producers who excelled in fewer traits (see Table 2). Herds in the
study were grouped by the number of these six primary traits, if
any, that were above average. Producers included in the top line of
information (0) performed at a below average level for all six
traits; while those producers included in the second line of
information (1) exceeded average in only one trait. Producers who
excelled in all six management practices are reported on the bottom
line in Table 2.

To be above average in a management trait, the producer must have
achieved the following levels of performance.

a. Mastitis Control. Less than 18.5 percent of cows in the herd
with a linear somatic cell count score (SCC) of 5 or more. A higher
percentage score indicated that mastitis was a severe problem. See
Fact Sheet I-3 for more information about the use of SCC's and
mastitis control.

b. Nutrition. More than 5,752 pounds of grain mix dry matter per
cow per year. This resulted in 2.75 pounds of milk per pound of
grain mix, because milk production per cow among herds in the study
averaged 15,823 pounds. See Fact Sheet I-4 for more information
about use of records in feeding the dairy herd.

TABLE 2. Relationship between number of above average management practices
and pounds of milk per cow per year, including average values for the six
management traits.

Number of
management Cows dry Sire's
practices Average Average Positive Grain Sire more than average Cows
above milk per co Number of Number of SCC fed ID 70 days PD$ left herd
average (lb) herds cows (percentage) (lb) (percentage) (percentage (1984) (percentage)
0 13784 53 50.5 28.5 4722 68.5 38.6 -26.5 25.5
1 14217 253 49.1 24.6 4914 68.9 30.5 -24.1 28.3
2 14950 493 53.3 22.6 5331 77.4 27.3 -17.2 30.8
3 15605 726 53.7 19.2 5899 81.5 22.4 -10.12 33.8
4 16354 656 55.7 15.7 5988 88.7 18.8 -4.43 38.1
5 17220 373 58.8 13.5 6429 93.3 14.4 3.47 39.3
6 17767 120 56.6 11.8 6627 95.6 10.9 10.42 44

Source: Appleman, 1985

c. Recordkeeping. More than 83.3 percent of the cows identified
with known ancestry, meaning the sires were identified and
recorded. See Fact Sheets I-2, I-5 and I-8 for additional
information.

d. Reproductive Management. Less than 21.9 percent of cows in
the herd with more than 70 days dry. A long dry period by many cows
reflects a herd reproduction problem. See Fact Sheet I-6 for more
information about using records in managing the reproductive
program.

e. Sire Selection. A predicted difference dollar (PD$) value that
is more positive than -$8.90. PD$'s, in this study, reflect the
genetic potential of cows in the herds in 1982 and 1983, using the
PD 82 base. A comparable 1985 figure would be $21.00, increasing
about $15 annually. See Fact Sheet I-7 for more information.

f. Cow Culling. More than 34.3 percent of the cows removed from
the herd each year. This figure is usually larger in the higher
producing herds presumably because: a) more first lactation cows
are culled, and b) some cows may be sold for "dairy purposes".
Furthermore, data in Table 2 may reflect "heavier-than-normal"
culling in preparation for participation in the 1984 to 1985 "milk
diversion program".

The Future

Widespread use of microcomputers on the dairy farm and the dairy
manager's acquaintance and appreciation for record management will
pave the way for an increasing number of remote access systems
tying the onfarm computer to the Dairy Records Processing Center
(DRPC) data base.

A remote access system will provide the manager with a versatile
data base for storing herd health and production information. The
dairy manager can assess trends and identify problem cows over
time. At some point, given the accumulation of these data,
researchers will develop more useful culling criteria. The biggest
gain, however, will be derived from producers using records, not
simply to describe the situation, but rather to diagnose the
situation and evaluate the different alternatives available to
them.

The DHIA program provides milk producers an opportunity to obtain
a tremendous amount of data regarding their dairy cows. DHIA
assembles that data into useful management information each month.
It is the responsibility of the producer or the manager to
interpret that information to help manage the herd more effectively
and improve the efficiency and profitability of the dairy
operation.

Literature Cited

Appleman, R.D., G.R. Steuernagel, L.B. Hansen and M.M. Schutz.
1985. Assessing Management

Traits That Influence Herd Average Milk Production. P327,
Supplement 1, J. Dairy Sci. 68:243 (abst.)

Conlin, B.J., et al. 1985. Minnesota State DHIA Long Range Planning
Report. Minnesota State DHIA unpublished report. Buffalo,
Minnesota.

Croyle, G.E., Jr. 1976. Pennsylvania Dairy Production Testing
Participant Perceptions of and Attitudes Towards the Dairy Herd
Improvement Program: A Statewide Survey. Pennsylvania State
University Extension Studies 62.

McCaffree, J.D., R.W. Everett, H.R. Ainslee and B.T. McDaniel.
1974. Economic Value of Dairy Herd Improvement Program. J. Dairy
Sci. 57:1420.

McCaffree, J.D., R.W. Everett, H.R. Ainslee and B.T. McDaniel.
1974. Economic Value of Dairy Herd Improvement Programs. Search
Vol. 4, No.1, College of Agriculture, Cornell University, Ithaca,
New York.

Smith, T.R. and G.H. Schmidt. 1985. Use of Dairy Herd Improvement
Testing Programs by Dairy Farmers. J. Dairy Sci. (accepted for
publication).
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תתתתתתתתתתתתתתתתתתתתThe National Dairy Database (1992)תתתתתתתתתתתתתתתתתתתת
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%f TITLE;USING DHI RECORDS TO MANAGE THE DAIRY HERD
%f COLLECTION;DAIRY HERD IMPROVEMENT
%f ORIGIN;Minnesota
%f DATE_INCLUDED;June 1992