evaluating progesterone profiles to improve automated oestrus detection
TRANSCRIPT
![Page 1: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/1.jpg)
Evaluating progesterone profiles to improve automated oestrus detection
Claudia Kamphuis, Wageningen UniversityKirsten Huijps, CRVHenk Hogeveen, Wageningen and Utrecht University
![Page 2: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/2.jpg)
- First insemination between 40-70 DIM is optimal*- oestrus detection is a key driver
- Challenges of detection- Time consuming- Error prone- Increased herd sizes
The importance of oestrus detection
*Inchaisri et al., 2012
![Page 3: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/3.jpg)
- 20% of Dutch dairy farms have automated systems*
- Appears to be a success story
- 20% of Dutch dairy farms have automated systems*
- Appears to be a success story when it all works- Sensitivities 80-90% with specificities > 90%**
- No technical / human errors
Adoption automated oestrus detection
*Huijps, 2014, CRV, personal communication*Huijps, 2014, CRV, personal communication**Rutten et al., 2013
![Page 4: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/4.jpg)
- Normal cycle takes 21 days
- Does progesterone affect oestrus behaviour- Affect automated oestrus detection?
Progesterone and oestrus
Days
Prog
este
rone
(ng
/ml)
Behavioural changes
![Page 5: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/5.jpg)
Aims of this study: gain insight in
- Performance of oestrus detection in the field
- Timing of oestrus alerts
- Use of alerts by farmers
- Effect of combining oestrus alerts on performance
- Effect of progesterone profiles on oestrus detection
![Page 6: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/6.jpg)
Materials and Methods
- 31 cows, 40-70 DIM, not inseminated
Farm A (450) Farm B (AMS; 250)
Milk samples for 24 days Morning milkingsResidual milk12 cows
First milkingsWhole milk19 cows
Oestrus alerts System A: 12 cowsSystem B: 12 cows System B: 8 cows
System C: 19 cowsOestrus observations Farm Staff Farm Staff
Average DIM at start 44 53
Average Parity 5.5 2.4
![Page 7: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/7.jpg)
Hormonost-Microlab Farmertest, Biolab, Unterschleissheim, Germany
Progesterone profiles from milk samples- Commercial on-farm kit
- Analyses 3x a week- Including forgone 1 / 2 days
- Profiles created
- Visual assessment of heat- According to manual- Gold standard
![Page 8: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/8.jpg)
Results: heats, observations and alerts
- Based on Progesterone (P): 30 heats from 30 cows
Farm Staff System
A B C
Heat observed/alerts generated 15 14 12 31
Heat alerts on day with P-heat 3 9
Heat alerts on day with P-heat +/- 1 day 9 17
False positive observations / alerts 6 4 5 18
![Page 9: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/9.jpg)
Results: timing alerts and observations
-23 -18 -13 -8 -3 2 7 12 17 220
1
2
3
4
5
6
System Adays around day of P-heat (day = 0)
Num
ber
of a
lert
s/ob
ser-
vatio
ns
![Page 10: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/10.jpg)
Results: timing alerts and observations
-23 -18 -13 -8 -3 2 7 12 17 220
1
2
3
4
5
6
System A System Bdays around day of P4heat (day = 0)
Num
ber
of a
lert
s/ob
ser-
vatio
ns
![Page 11: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/11.jpg)
Results: timing alerts and observations
-23 -18 -13 -8 -3 2 7 12 17 220
1
2
3
4
5
6
System A System B System Cdays around day of P4heat (day = 0)
Num
ber
of a
lert
s/ob
ser-
vatio
ns
![Page 12: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/12.jpg)
-23 -18 -13 -8 -3 2 7 12 17 220
1
2
3
4
5
6
Farm staff System A System B System Cdays around day of P4heat (day = 0)
Num
ber
of a
lert
s/ob
-se
rvat
ions
Results: timing alerts and observations84% of all alerts
87% of all observationsare 3 days around P-heat
False or True?
![Page 13: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/13.jpg)
Results: combining detection systems
Using a 1 day time window around a P-heat
Farm ASystem A: 5 out of 12 P-heats (42%)System B: 3 out of 12 P-heats (25%)One P-heat additionally detected
Farm BSystem B: 2 out of 18 P-heats (11%)System C: 9 out of 18 P-heats (50%)No additionally P-heat detected
![Page 14: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/14.jpg)
Results: effect of progesterone profiles
-23 -20 -17 -14 -11 -8 -5 -2 1 4 7 10 13 16 19 220
5
10
15
20
25
30
Average P levelsDays around P-heat (day = 0)
Prog
este
rone
leve
l (ng
/mL)
![Page 15: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/15.jpg)
Results: effect of progesterone profiles
-23 -20 -17 -14 -11 -8 -5 -2 1 4 7 10 13 16 19 220
5
10
15
20
25
30
Average P levels Detected P-heatsDays around P-heat (day = 0)
Prog
este
rone
leve
l (ng
/mL)
![Page 16: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/16.jpg)
Results: effect of progesterone profiles
-23 -20 -17 -14 -11 -8 -5 -2 1 4 7 10 13 16 19 220
5
10
15
20
25
30
Average P levels Not detected P-heatsDetected P-heats
Days around P-heat (day = 0)
Prog
este
rone
leve
l (ng
/mL)
![Page 17: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/17.jpg)
Conclusions
* Rutten et al., 2012; Kamphuis et al., 2012
- All 3 systems performed less than expected- Expected: 80%*; Found: 25-50%
-Farm staff missed 48% of true positive alerts- Not checked alerts / behavioural changes
already passed
-Most alerts and observations around 3 days of P-heat
-Progesterone profiles did not differ between (non)detected cows
![Page 18: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/18.jpg)
Take Home Message
- Farmers miss correctly identified oestrus's
- Progesterone does not affect oestrus behaviour
- Confirm with larger numbers- Successful inseminations as gold standard
![Page 19: Evaluating progesterone profiles to improve automated oestrus detection](https://reader036.vdocuments.site/reader036/viewer/2022062502/58ab6ef01a28abb54e8b52bf/html5/thumbnails/19.jpg)
Acknowledgements
- Hands-on- Farmers- Farm staff- Marije Popta and Gea Miedema
(Van Hall-Larenstein, Leeuwarden)
- Funding