Infertility in the herd Flashcards

Principles of monitoring fertility in populations

1
Q

What data do we need to monitor fertility, at a basic level?

A

“Aggregated” data, e.g:
▪Total numbers of ewes bred, lambs born live
▪Total number of piglets produced per year

  • Fairly crude measures
  • hard to judge data quality/accuracy
  • may be all you have
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2
Q

What data do we need to monitor fertility? (more detailed than basic)

A

▪ Animal ID data
▪ Event records, e.g:
– Inseminations
– PDs
– Parturition events

  • Generally more accurate
  • better insights from data
  • analysis can be more automated
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3
Q

Paper records (for data storage)

A
  • More useful for “aggregated” measures using totals
  • Very labour intensive for anything more detailed
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4
Q

On-farm software (for data storage)

A
  • Usually good detail/accuracy
  • Useful for day to day management on farm
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5
Q

Central database (for data storage)

A
  • Easy to access
  • usually less detail and sometimes accuracy
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6
Q

How can we analyse data?

A

DIY methods
* Flexible and customisable
* Time consuming
* Only option for simple “totals” data

Using the platform where the data lives
* Easy to access
* Multiple systems to be familiar with
* Some not very good at analysis

Specialist analysis software
* Relatively simple to use
* Only one system to get used to
* Can bring together lots of sources of data
* Ideal

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7
Q

How to monitor fertility in sheep - last season’s performance

A

▪ Lambing %
– (lambs born alive / ewes put to ram) x 100
– Target 120-200% (lowland>upland>hill)
▪Weaning %
– (lambs weaned / ewes put to ram) x 100
▪ Length of lambing period
– 95% should be within 2 cycles (ie 35 day period)
▪Barren ewes
– (1-(ewes lambing / ewes put to ram)) x 100
– Target <2-3%

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8
Q

How to monitor fertility in sheep - this season’s performance

A
  • Use of raddle
    – identifies ewes returning to serve
    – identifies ewes not served
  • Use of scanning
    – Identifies empty ewes at end of breeding season
    – estimates lambing %
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9
Q

How to monitor fertility in beef cattle

A

Almost all herds seasonal calving

Major objectives:
▪ One calf per cow per year
▪ 90% herd should calve within 9wk period with 65% in first 3wks
▪ <5% barren/empty cows

Easy to analyse last breeding season

Calving distribution
▪ Can get data from CTS online

Can be difficult to work out what’s going on this season
- Vast majority of herds run bull(s) with cows
- No need for stockpeople to detect oestrus
- Usually no recording of serves/heats
– Often have PD session after end of breeding season (+/- at/during)
- Can use chin markers: rest their head on them before serving (like raddle marker)

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10
Q

Beef cattle breeding goals

A
  • % of cows served being empty should be less than 5%
  • aiming for 65% of cows served in the 1st 3wk block of the calving season
  • aiming for 90% of cows in the first 9wks of the calving season (i.e.
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11
Q

How long is the voluntary wait period?

A

~45d

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12
Q

Parts of the dairy production cycle

A
  • voluntary wait period (farm policy/choice)
  • calving-1st serve interval
  • calving-conception interval (wanting it to be as close the a year as possible)
  • gestation period
  • calving interval/index
  • lactation
  • dry period
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13
Q

How long is the gestational period in cows?

A
  • ~280d
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14
Q

How long is the dry period in dairy cows?

A

~50d

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15
Q

Calving index and culling

A
  • Farm culling policy can affect or “manipulate” calving index
    – This is often seen in seasonal calving herds
    -> Cows not pregnant at the end of a set “breeding season” each year are culled
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16
Q

Why not just monitor calving index and culling in dairy cattle?

A
  • very slow to respond to changes
  • doesn’t show where the problem is
17
Q

What makes good fertility?

A
  • return to cyclicity
  • heat detection
  • serving cows
  • conception rate
  • when served are they getting pregnant?
18
Q

Measuring heat detection

A

First service submission rate
- Are cows getting their first serve “on time”?
- % of cows getting first serve within 24 days of VWP ending
- Target 80%

19
Q

Inter-service intervals

A

0-17d from previous
- short return
- inaccurate heat detection
- or follicular cyst

18-24d from previous
- normal return
- correct oestrus detection
- 19-26d suggested to be a better normal range

25-35d from previous
- abnormal return
- inaccurate heat detection or LED

36-48d from previous
- return after heat missed

49+d from previous
- multiple missed heats
- foetal death

20
Q

Heat detection - what goes wrong?

A

Expression
- lameness
- environment
- nutrition
- use of bull
- genetics

Detection
- time observing
- timing of observation
- training
- use of bull
- technology
- heat detection aids

21
Q

Measuring conception rate

A

Proportion of serves leading to a pregnancy
- Outcome ideally via PD
– Can also use non-return to serve or next calving
- Sometimes known as “pregnancy rate”
- Target >35-50%
– Associated with milk yield
– Higher targets for lower yielding herds

22
Q

Conception rate - what goes wrong?

A

Nutrition
- energy balance
- micronutrients
- SARA
- excess protein?

AI related
- technique
- semen quality
- semen storage
- thawing and handling
- timing of AI

Disease
- lameness
- herd level infectious disease (IBR/BVD/lepto)
- uterine bacterial dz
venereal (e.g. campylobacter)

Bull
- true infertility
- lameness
- lack of libido

NEB likely to be most common cause

Harder to fix than submission rate

23
Q

Monitoring fertility - 21d pregnancy rate

A

every 3wks measure
- number eligible to serve
- number served
- number in calf
- % of eligible cows served
- % of eligible cows getting in calf

21d-serve rate (aka 21d insemination rate):
- proportion of eligible cows served every 21d
- Measures submission
- blue line on graph

21d-preg rate (aka fertility efficiency):
- proportion of eligible cows becoming pregnant every 21d
- Measures overall repro performance
- green line on graph

24
Q

Limitations in managing and monitoring fertility

A
  • lack of data
  • poor data quality
  • lack of skill/time
  • no access to software