monitoring the pregnancy status of dairy cows using mid-infrared ... · example of a mir spectrum...
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Monitoring the pregnancy status of dairy cows using mid-infrared spectra of milk collected from milk recording
www.optimir.eu
WITH THE SUPPORT OF
A. Lainé*, L.M. Dale, H. Bel Mabrouk, C. Bastin, and N. Gengler University of Liège, Gembloux Agro-Bio Tech, 2 Passage des Déportés, 5030 Gembloux, Belgium
IDF/ISO Analytical Week and Symposium OptiMIR Namur, 13-17 April 2015
A pregnancy diagnosis ?
www.partners-in-reproduction.com
Vet’s check Rectal palpation Transrectal ultrasond Echograpy …
AI/mating
Monitoring of the pregnancy along the lactation
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Calving Calving ?
IDF/ISO Analytical Week and Symposium OptiMIR Namur, 13-17 April 2015
Using the monthly milk recording data ...
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Wavelengths (cm-1)
Example of a MIR spectrum of milk
Mid-infrared spectrum of milk is a fingerprint of the milk composition
Spectra collected and stored routinely
Rapid, inexpensive and non-destructive method which is widely used
Allow for a large scale sampling
IDF/ISO Analytical Week and Symposium OptiMIR Namur, 13-17 April 2015
... not so easy !
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Wavelengths (cm-1)
Example of a MIR spectrum of milk
Chemical components of
the milk
Animal status
Pregnant cow or not ?
1. High correlations between some wavenumbers of the spectra
2. Milk composition is influenced by several different effects and the pregnancy status is probably not the main one
3. The pregnancy status is highly linked with the lactation stage
IDF/ISO Analytical Week and Symposium OptiMIR Namur, 13-17 April 2015
Dealing with drawbacks by modelling them
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1. High correlations between some wavenumbers of the spectra
2. Milk composition is influenced by several different effects and the pregnancy status is probably not the main one
3. The pregnancy status is highly linked with the lactation stage
Transformation of wavenumbers by PCA
Estimation of various fixed and random effect
for each PCs
Introduction of days in milk in the model using polynomial Legendre
IDF/ISO Analytical Week and Symposium OptiMIR Namur, 13-17 April 2015
Dealing with drawbacks by modelling them
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𝑦 = 𝑚𝑖𝑙𝑘𝑖𝑛𝑔 𝑚𝑜𝑚𝑒𝑛𝑡 + 𝑚𝑜𝑛𝑡ℎ 𝑜𝑓 𝑇𝐷 + 𝑝𝑟𝑒𝑔𝑛𝑎𝑛𝑐𝑦 𝑠𝑡𝑎𝑡𝑢𝑠 + 2𝑛𝑑 𝐿𝑒𝑔𝑒𝑛𝑑𝑟𝑒+ 3𝑡ℎ 𝐿𝑒𝑔𝑒𝑛𝑑𝑟𝑒 + 𝑎𝑛𝑖𝑚𝑎𝑙 + 2𝑛𝑑 𝐿𝑒𝑔𝑒𝑛𝑑𝑟𝑒 ∗ 𝑎𝑛𝑖𝑚𝑎𝑙 + 3𝑡ℎ 𝐿𝑒𝑔𝑒𝑛𝑑𝑟𝑒 ∗ 𝑎𝑛𝑖𝑚𝑎𝑙
1st lactations of Holstein cows over the last 3 years of records in the Walloon Region of Belgium 40,990 spectra
𝑝𝑟𝑒𝑔𝑛𝑎𝑛𝑐𝑦 𝑠𝑡𝑎𝑡𝑢𝑠
What is the impact of the pregnancy on the
spectra ?
IDF/ISO Analytical Week and Symposium OptiMIR Namur, 13-17 April 2015
Significant impact of the pregnancy status on MIR spectra
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|pregnant|/s.e.
Principal Components explaining 99.9% of the spectral variability
95% of the spectral variability
t value > 2 64% PCs retained
t value > 5 22% PCs retained
IDF/ISO Analytical Week and Symposium OptiMIR Namur, 13-17 April 2015
Significant impact of the pregnancy status on MIR spectra
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Principal Components explaining 99.9% of the spectral variability
Whole dataset
Pregnant data from 1 to 120days post AI
Same trends are observed when only pregnant data from 1 to 120 days post-insemination are considered to model the pregnant effect
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Wavelengths (cm-1)
Example of a MIR spectrum of milk
IDF/ISO Analytical Week and Symposium OptiMIR Namur, 13-17 April 2015
From theoretical concerns to a practical tool for farmers
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Pregnant ?
IDF/ISO Analytical Week and Symposium OptiMIR Namur, 13-17 April 2015
Residual spectra as an image of the pregnancy status
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Observed spectrum = Milk sample on which we want to test the pregnancy
Expected open spectrum = The expected spectrum for the same day in milk if the animal was open
IDF/ISO Analytical Week and Symposium OptiMIR Namur, 13-17 April 2015
Residual spectra as an image of the pregnancy status
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Residual spectrum = Observed spectrum – Expected open spectrum
Residual spectra are used to perform discrimination between two groups of classification (Pregnant cow and non-pregnant cow)
IDF/ISO Analytical Week and Symposium OptiMIR Namur, 13-17 April 2015
Applying a logistic regression on residual spectra
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2,515 Non-pregnant 5,377 Pregnant Testing dataset
46% 54% 89% 11%
Sensitivity Specificity
Average error rate of classification = 25%
46% of data belonging to
non-pregnant cows were correctly classified
89% of data belonging to
pregnant cows were correctly classified
IDF/ISO Analytical Week and Symposium OptiMIR Namur, 13-17 April 2015
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Good perspectives on performances of the tool
Needs for improvement on the detection of non-pregnant cows
Tests on pilot farms are ongoing
Not yet implemented but the strategy is well define
Needs to provide an “useful” information to the farmers
IDF/ISO Analytical Week and Symposium OptiMIR Namur, 13-17 April 2015
Thanks to a fruitful partnership !
Service Public of Wallonia SPW – DGO3
European Commission (ERDF) through project INTERREG IVb OptiMIR
Author’s contact e-mail: