AN INTEGRATED REPRODUCTIVE MANAGEMENT PUBLICATION
Minnesota DHI Reproduction Information
An Integrated Reproductive Management Publication
J.K. Reneau and G.R. Steuernagel
The ideal calving interval for maximum productivity is 12
months. When intervals extend beyond 13 months, significant
economic loss will occur. By keeping intervals below 13.0 months,
severe economic loss will probably be avoided. Estimates on
economic losses for calving intervals extending beyond the ideal 12
months have ranged from $3.00 to $5.50 loss per cow per day. Though
definitive research is needed to determine more accurate loss
figures, these estimates portray the economic seriousness of the
problem.
The average calving interval for Holstein herds in Minnesota
during 1984 was 13.0 months. Over 40 percent of those herds had
calving intervals exceeding 13 months with only a very small
percentage of herds at the ideal 12-month level. Obviously there is
still considerable room for improved reproductive performance among
Minnesota dairy farms.
HERD SUMMARY
Factors most influencing calving interval are heat detection,
conception rate, days to first breeding, and culling for
reproductive failure. These measures of reproductive performance
are displayed on the DHI Herd Summary (figure 7). When the
reporting of reproduction information by the farmer and DHI
supervisor has been timely and accurate, these values are helpful
assessments of reproductive performance.
CULLING RATE
Culling rate can have a profound influence on calving
intervals. If culling rates are unusually high, one should
determine the underlying reason. Reasonably good calving intervals
can be maintained in the face of considerable infertility if cows
with reproductive problems are culled. Consider cull rate before
making assessments of the true reproductive performance in a herd.
HEAT DETECTION INDEX
The heat detection index is an estimate of the percentage of
heat cycles observed during the breeding interval. The detection
index is calculated as follows:
21 X 100
________________
Average interval
between breedings
or recorded heats
CONCEPTION RATE
The DHI conception rate represents the maximum possible
conception for cows in the herd. It includes those cows that are
confirmed pregnant plus those recently bred. The calculation is as
follows:
Number of cows pregnant + possibly pregnant X 100
___________________________________________
Total number of services
The DHI rate is not an index of recent herd reproductive
performance, but a historical account of the average conception
rate among all cows bred in the herd. The timeliness of the DHI
conception rate figure is dependent on when pregnancy is
recognized. Pregnancy recognition will be more timely on a farm
where fertility work is routinely being done by veterinarians. The
conception rate represents an estimate of the very best possible
conception rate, and is likely to be inflated on farms with many
problem cows.
CALVED TO FIRST BREEDING
The average number of days from calving to first breeding has
great influence on calving interval. Minnesota DHI records indicate
that the average days from calving to first breeding is 84 days.
Yet if a 12-month calving interval is to be achieved, the cows must
be pregnant 85 days after calving. One of the simplest ways to
improve caving intervals is to make a management decision to begin
breeding as soon as feasible.
Understanding the interaction between heat detection,
conception rate, and days to first breeding is crucial to taking
steps to improve reproductive management. For example, if a dairy
farmer expects a 12-month calving interval but has only 40 percent
heat detection and a 40-percent conception rate, he can quickly see
how unrealistic the goal is. In order to achieve such a goal with
that level of performance, breeding would have to begin 51 days
before the cow caved. For this dairy farmer, improved heat
detection is essential. Table 1 shows the relationship between heat
detection, conception rate, and days to first breeding and
demonstrates the impact of reproductive management factors on
reproductive performance.
Table 1. Relationship between heat detection, conception rate,
and days to first breeding.*
The day breeding must begin to achieve a 12-month
calving interval at varying heat and conception rate
performance levels.
100-
90-
Heat
Detection 80- 30 45 54 61
70- 25 39 49 58
60- 15 32 43 53
50- 1 21 35 47
40- -51 5 22 37
________________________________
40 50 60 70
Conception Rate%
*Based on percent heat detection and conception rates, the figures
in tablet represent the number of days to allow between caving and
breeding in order to achieve a 12.0 month calving interval. To
make the table applicable to calving interval goals of 12.5 and
13.0 months, add 15 or 30 days respectively to each number in the
table.
The most serious criticism of the Reproductive Herd Summary
values is that they are historical in nature and may not always
reflect recent reproductive performance in the herd. Therefore,
they have not been useful monitors of reproductive performance in
providing early warning of reproductive failure.
REPRODUCTION REPORT
Retrospective study of reproductive performance in Minnesota
DHI herds reveals that the greatest obstacles to achievement of a
12-month calving interval are poor heat detection and too great a
delay in days to first breeding. The changing of current trends and
improved reproductive performance will require an increased
educational focus on these two factors. First, educators and dairy
farmers must appreciate the relationship between heat detection,
conception rate, and days to first breeding. Secondly, there needs
to be a record system that gives both historical and current
accounting of herd reproductive performance.
The herd summary will continue to carry the historical
measures of reproductive performance. The DHI Reproduction Report
is designed to provide more current information, facilitating early
identification of problems in reproductive performance and enabling
timely correction in either management deficiencies or reproductive
disease. Individual problem cows as well as recent herd trends
will be emphasized.
The format of the reproductive report is very similar to that
of the SCC Report. Herd summaries predominate on the upper portion
of the report while detailed individual cow data are listed in the
lower portion (figure 6). The report will be discussed by section
and examples will be given to illustrate its usefulness.
SECTION A. MONTHLY REPRODUCTIVE CYCLES
Early recognition of reproductive failure or infertility is
necessary in order to avoid serious losses. The use of routine
veterinary herd fertility programs will facilitate early
recognition of clinical reproductive disease (cystic ovaries,
metritis, etc.) so that timely treatment will lessen the number of
days affected cows stand open. Herd specific vaccination programs
will lessen infertility and abortions due to subclinical diseases.
Early pregnancy diagnosis (prior to 42 days) will reduce days lost
due to presumed pregnancy. However, even the most skilled farm
managers or veterinary teams will be unable to significantly
improve reproductive performance without the use of good records.
Records not only serve to monitor the success or failure of
veterinary procedures, but also define reproductive management
deficiencies which must be remedied if total success is to occur.
Poor heat detection is the greatest single obstacle to
successful A.I. programs. Minnesota studies involving large numbers
of cows show that detection of heat is more of a management problem
than a cow problem. Ninety percent of all cows thought to be
anestrus (not showing heat) were cycling normally. Only 10 percent
of supposedly anestrus cows were actually not cycling as a result
of some pathological problem.
Well fed and healthy cows will normally begin to cycle by
approximately 20 days postpartum (after calving). Not all of these
early ovulations are accompanied by strong heat signs. However, by
60 days postpartum, nearly 100 percent of normal cows are cycling
and expressing normal heat signs. Whether or not these cows are
observed in heat depends on the intensity of the heat detection
effort. This fact is clearly verified in a summary of three studies
found in table 2.
Table 2. Percentage of normal cows detected in heat at first,
second, and third ovulation when maintained under
different systems of observation.
Ovulation
Observation First Second Third
system (20 days) (44 days) (64 days)
(1) Continuous 24 hr. observation
(A) King, et al. 50% 84% 100%
(B) Williamson, et al 100%
(2) Casual (herdsman)
(A) King, et al. 20% 44% 64%
(B) Williamson, et al. 56%
(C)Morrow, et al. 23% 46% 64%
In the summary of Monthly Reproductive Cycles (figure 1), the
number of heats is calculated from estimates given for each month.
This figure represents the number of heats theoretically possible
beginning with the first reported heat date or on day 60 postpartum
if no heat date is reported prior to 60 days. Reported heats are
those heats where the cow is observed and recorded in heat or is in
heat and also bred. Reported heats divided by the estimated number
of theoretical heats times 100 will give the percentage of cows
detected in heat. The DHI Reproduction Report will allow monthly
monitoring of heat detection efforts. For example, the John
Dairyman herd (figure 1) had 100 percent heat detection in November
and 50 percent in December.
This herd's average heat detection index was 62 percent. The
present average heat detection performance among DHI herds is a
dismal 44 percent. In general, the heat detection performance is
better on the high producing herds (table 3) although improvement
could be made on these farms as well.
Good heat detection is a function of a complete awareness of
the physical and behavioral signs of heat and the time spent
looking for cows in heat. A recommended reference is Detection of
Heat in Dairy Cows, extension publication AG-FO-2018. Since a cow
standing firmly while another cow mounts (standing heat) is the
most reliable sign of heat, success in heat detection is dependent
on cows being able to interact. Table 4 nicely demonstrates the
relationship between the number of daily observations and the
percentage of cows detected in heat. If you are observing cows only
once per day for 20 to 30 minutes, you are missing half of the cows
in heat. An excellent heat detection goal under Minnesota dairying
conditions would be 80 percent. Monthly reminders of heat detection
performance will help dairy farmers improve productive performance.
%G D10301d.pcx, D10301p.pcx; FIG. 1, 2 & 3: SAMPLE LISTINGS
Table 3. 1984 Heat Detection Performance on Holstein DHI
Herds in Minnesota at Various Levels of Performance
Rolling Herd Averages by Thousand
lbs Milk
11-12 14-15 17-18 20+
Number of herds 394 1,095 565 73
Cows per herd 46 50 53 52
Heat detection index 38 44 50 53
Table 4. Relative Efficiency of Heat Detection Schemes.*
% Correctly Found
Heat Detection Scheme in Heat
Continuous 24 hr observation 98-100%
Observed three times daily 90%
Observed two times daily 83%
Observed once daily 50%
*These figures assume that cattle being observed for heat are
allowed to freely interact.
Also listed in the Monthly Reproductive Cycles chart
(figure 1;) is a monthly compilation of
the number of cycling cows detected in heat and bred as well as the number
of cows that became pregnant as a result of those breedings. This enables
easy calculation of conception rates on a monthly basis. The information
is useful, but must be interpreted with caution. The average expected
conception rate under normal conditions would be 60 to 65 percent,
reflecting good reproductive performance. Conception rates calculated on a
monthly basis in a small herd are likely to vary considerably. For
example, the conception rate for one month might be as high as 80 to 100
percent. If such a high rate does occur, one must realize that this level
of performance should not be routinely expected. This is a statistical
phenomenon quite similar to the situation in which a farmer got 80 percent
heifer calves in one particular calving season. Over the long run, we know
that the average would be closer to 50 percent heifers. Likewise, the
average expected conception rate under good conditions would be 60 to 65
percent. However, we should expect a somewhat higher conception rate in
heifers than older cows. We also know that some bulls are more fertile
than others.
When the conception rate drops below 50 percent in any
month as was the case in the John Dairyman herd in November,
January, and March, we ought to try to determine why. If the cows
bred during that month were older cows or were cows that had
experienced postpartum uterine disorders such as retained placentas
or metritis, these lower conception rates would not be surprising.
Or perhaps high ambient temperature and humidity had a detrimental
influence on conception rate or early embryonic death in May and
June. In Arizona dairies, for example, conception rate is reduced
to as low as 10 to 20 percent during the hot summer months. But if
monthly conception rates are low and cannot be easily explained,
then other things must be considered. The timing of A.l., A.l.
technique, poor quality semen or faulty semen handling should be
considered as possible explanations. Nutritional factors may also
need attention.
If no management or physiological factors can be found,
one can be content that the low conception rate is a statistical
phenomenon similar to the case of the farmer who got 80 percent
heifer calves. Though such concerns may arise on occasion with this
type of reporting system, there should be sufficient warning to
allow for early action.
SECTION B. MONTHLY Calving PATTERN
Figure 2 provides a historical account of the numbers of cows
and heifers that have calved over the past 13 months as well as the
anticipated number of cows and heifers expected to calve during the
next six months.
Calving patterns may be helpful in managing labor or in
anticipating or adjusting milk flow. The planning of calving
management as well as heifer breeding and labor will be aided by
the recording of monthly calving patterns.
SECTION C. LIST OF PROBLEM COWS
The problem cow list is an effective means of focusing
attention on those individuals in the herd that are most hindering
reproductive performance. Note cows Vanesa and Elsie (figure 3) in
the John Dairyman example herd. This list consists of heifers or
cows in the herd ghat have been open more than 120 days and are not
confirmed pregnant or that began a lactation by abortion or
premature calving. These cows are listed in calving order so that
those of greatest concern are listed first. Those listed with an
asterisk next to the number are problem cows that are bred but not
confirmed pregnant. The problem list helps indicate the extent of
the reproductive problem. In comparing two herds, each with 13.5
month calving intervals, one would be more concerned about
reproductive management when the list of problem cows is numerous
compared to the herd with one or two cows with excessively long
calving intervals.
It is important to be able to get an assessment of a cow's
performance at a glance. Graphic presentations of herd summary data
often are the most effective means of calling attention to both
strengths and weaknesses in reproductive management.
Construction of a Q Sum Graph (figure 4) is a simple method of
keeping abreast of recent herd reproductive performance trends.
This graph can be used to supplement DHI reproductive records. The
success or failure of successive breedings are charted on graph
paper by beginning at an arbitrary reference point. With each
diagnosed pregnancy, a circle is drawn in a square to the right and
up. A pregnancy failure is indicated by an X marked to the right
and one square down. Such a graph is demonstrated in figure 4.
SECTION D. REPRODUCTIVE ACTIVITY CHART
Failure trends are quickly noticed when Q sum graphs are used,
allowing correction of problems before d disaster occurs. This
particular graph (figure 4) was constructed in retrospect in an
attempt to solve reproductive problems on one dairy farm. The
dairyman had begun doing his own A.l. sometime in March and had
serious A.l. technique problems which did not get resolved until
June. Conception rates between 3/10 and 5/12 were 20 percent and
from 5/12 to 6/19 were 10 percent. Conception rates after June 19th
were improving at 37 percent. It appears that conception rate
trends during July indicate normal expected performance. Had
performance been monitored with the Q sum graph, the problem may
have been discovered and corrected sooner.
Q sum graphs can be adapted readily to microcomputer
technology but are awkward when the printout is confined to a small
space. The Reproductive Activity chart (figures) found on the upper
right hand corner of the DHI Reproduction Report is meant to be
used in a manner similar to Q sum graphs. The Reproductive Activity
chart consists of ten columns with ten squares per column.
Each column represents ten percent of the theoretically
estimated heats in the herd during the past six months. The
beginning date is printed to the left of the arrow found in the top
of the chart. In the column on the left side (figures) the H
indicates that seven out of ten heats were observed and recorded
six months ago. Heat detection was improved slightly during the
past six months; the columns on the right side of the chart
indicate that currently the dairyman is detecting eight out of ten
heats. The letter B indicates the number of cows not only observed
but bred out of ten theoretical heats. The letter C indicates the
number of cows that conceived. Cs only appear in the left hand side
of the graph because we are not sure which breedings were
successful for cows bred more recently.
%G D10302d.pcx, D10302p.pcx; FIG. 4 & 5. Q SUM GRAPH
Reproductive activity charts enable you to spot poor
reproduction performance early enough to get corrective measures in
place before the entire herd is in trouble. In the above example,
heat detection has gone from about 70 percent to 80 percent during
the past six months indicating heat detection is not a problem in
this herd. Recently (the right side of chart) about five out of
eight cows observed in heat were being bred. Note that in the first
two columns conception rate was acceptable (50 to 55 percent) but
that conception rate declined more recently. The management factors
affecting conception rate should be reviewed by the herd owner.
As was pointed out in the example of the herd plotted on the
Q Sum Graph, dairy farmers beginning their own A.I. should
carefully monitor their results. Rapid decline in conception rate
should be a warning that A.l. technique or semen handling may not
be correct. It is hoped that this chart will be helpful to both
farmers and those with whom they consult on reproductive matters in
assessing the herd's reproductive performance at a glance.
SECTION E. INDIVIDUAL COW DATA
Individual cow data (figure 6) on the DHI Reproductive
Report has considerably more reproduction information than offered
before. Though most of that information is self-explanatory, it may
be of value to highlight how some of this information may be used,
particularly to improve reproductive performance.
Assuming all heats observed are being recorded by the farmer
and also are being accurately transferred to the DHI barn sheet by
the DHI supervisor, a study of the days to first heat can be
revealing. Even more revealing would be a calculation of the
average days to first heat on a herd basis. One hundred percent of
normal cows will show standing heat by 60 days postpartum (table
5).
Table 5. Standing Estrus at First Heat PostPartum
Postpartum Type of Estrus
days Non-standing % Standing
1-20 64% 36%
21-40 15% 85%
41-60 11% 89%
61 0% 100%
Lauderdale, 1974
The percentage of cows seen in heat by 60 days postpartum is
an excellent reflection of either the herd's reproductive health or
the heat detection efficiency (Reproduction Summary, figure 7). For
example, in a high producing herd, you may find that the percentage
of cows showing heat is acceptable, but the farmer is complaining
that the cows are not showing heat well at the time he would like
to begin breeding (60 to 70 days postpartum). It could be that heat
detection in this herd is adequate but there is a need for
adjustment in early lactation feeding to maximize DM intake, thus
minimizing a negative energy balance with its subsequent depression
of heat signs.
As previously cited, 90 percent of all cows not seen in heat
are cycling normally but are not being observed. The missed heats
column (figure 6) emphasizes this fact. In a few cases where there
is reproductive pathology (cystic ovaries, etc.) or stress-related
reproductive inactivity, cows will be listed as having been missed
in heat when this may not be true. For example, it is not uncommon
to find first calf heifers with completely inactive ovaries due to
the stresses resulting from adjustment to stall barn living or to
the lactation ration, recuperation from a difficult calving, or
needing nutrients to continue growth. In such cases, rectal
examination of the cow or heifer by a veterinarian will determine
if the cow is truly anestrus or being missed because of poor heat
detection.
Repeat breeders are defined as those cows that are cycling
normally and are showing normal signs of heat, but have not become
pregnant after being bred three times. Repeat breeder cows are
common among Minnesota dairy herds. Normal incidence is 10 to 15
percent. The column labeled "Times" under the "Last Breeding or
Heat" column can be used to identify repeat breeder problems which
tend to occur in older, high-producing cows. It is common for a cow
to habitually have repeat breeder problems year after year. These
studies also showed that there is an increase in repeat breeder
cows as herd size increases.
The most common cause of repeat breeders is faulty heat
detection. Hormone tests of milk samples collected at the time of
insemination show that nearly 20 percent of cows bred were not even
in heat. The timing of insemination should be based on standing
heat, that is, a cow standing firm with all four legs braced while
mounted by another cow. For best A.l. results, cows should not be
inseminated based on non-standing signs of heat such as mounting
other cows, hyperactivity, mucus discharge, or a swollen vulva.
This leads to poor timing of A.I. and many repeat breeders.
Consider these factors when the incidence of repeat breeders is
greater than 10 percent.
The future of any herd is determined by the quality of the
bull used. For many years, the DHI Herd Summary has been printing
the average PD$ service sires being used in the herd. This
information has been an excellent monitor of the general breeding
policy in the herd. The new DHI Reproduction Report will report PD$
of service sires on the last breeding of every cow. This will add
greater depth to the DHI genetic information.
Pregnancy diagnosis is an important part of the herd
fertility program. Equally important is the determination that a
cow previously bred and thought pregnant is open. The discovery of
an open cow 42 days after breeding or sooner is important to
minimizing days open. ln a herd on a monthly veterinary
reproductive health program, the range of days from breeding to the
pregnancy exam should be a maximum of 35 to 70 days. The exam of
most value is that one prior to 42 days post breeding so that
timely treatment or more intensive observation for heat can prevent
undue loss of time. Examinations of cows for pregnancy beyond two
months post breeding will not be as effective in helping maintain
low caving intervals.
The last four columns, "Days in Milk," "Production Index,"
"Peak Milk" and "Sample Day Milk (Actual) (Expected)," are useful
as culling aids.
The DHI Reproduction Form contributes to a better
understanding of dairy farm reproduction. As time goes on, we are
certain that DHI reproduction information will become vital to the
management success of every Minnesota dairy farm.
The authors are extension dairy specialists.
Issued in furtherance of cooperative extension work in agriculture
and home economics, acts of May 8 and June 30,1914, in cooperation
with the U.S. Department of Agriculture, Patrick. Borich, Dean and
Director of Minnesota Extension Service, University of Minnesota,
St. Paul, Minnesota 55108. The University of Minnesota, including
the Minnesota Extension Service, is committed to the policy that
all persons shall have equal access to its programs, facilities,
and employment without regard to race, religion, color, sex,
national origin, handicap, age, veteran status, or sexual
orientation.
%G D10303d.pcx, D10303p.pcx; FIG. 6. SAMPLE REPRODUCTION SHEET
%G D10304d.pcx, D10304p.pcx; FIG. 7. SAMPLE HERD SUMMARY SHEET
%f TITLE;AN INTEGRATED REPRODUCTIVE MANAGEMENT PUBLICATION
%f COLLECTION;DAIRY HERD IMPROVEMENT
%f ORIGIN;UNIVERSITY OF MINNESOTA
%f DATE_INCLUDED;OCTOBER, 1993
%t AN INTEGRATED REPRODUCTIVE MANAGEMENT PUBLICATION