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Validation of the prediction of body weight from dairy cow characteristics and milk MIR spectra
Soyeurt, Hélène; Froidmont, E.; Dufrasne, Isabelle et al.
2019In Book of Abstracts of the 70th Annual Meeting of the European Association for Animal Production
Peer reviewed
 

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Keywords :
body weight; prediction equation; milk traits
Abstract :
[en] Body weight (BW) recording is of interest to optimize herd management and environmental fingerprint. Due to its cost, a weighing system is not installed in many farms. Linear type traits are mostly available only once in the lifetime of the cow. So, an interest exists to develop a method to predict routinely BW with traits easily recorded and cheap. First investigation was conducted one year ago to build a prediction equation of BW from parity, test month, milk yield, days in milk and milk MIR spectrum. This study based on 717 records obtained a herd validation root mean square error (RMSEv) ranged from 37 to 64 kg. Cross-validation (cv) R2 was equal to 0.51 with RMSE of 50 kg. This equation was applied on 1,161 milk MIR spectra collected in the GplusE project from Holstein cows. Validation R2 was 0.51 with RMSEv of 65 kg. A total of 109 spectra had a global H distance higher than 3 suggesting spectral outliers. After their removal, R2v increased slightly (0.54). Difference of RMSEv can be explained by a lack of spectral variability in the calibration set. So, the 2 datasets were merged to build a PLS regression including the same predictive traits as the first study. After a spectral cleaning based on GH and residual analysis, the best equation used 1,837 records and gave a 10 fold R2cv of 0.64±0.02 with a RMSEv of 46±2 kg. The ability to predict BW was improved by adding this new data. Lowest errors were observed for BW ranged from 500 to 750 kg which represents 94% of the set. So, low and high BW lack in the calibration set. This study confirms the preliminary results and the potentiality to predict an indicator of body weight. This alternative BW prediction could explain a part of the BW variability not already covered by other BW predictors as those based on linear scores. Moreover, this method allows to consider the past information if the spectral data is available. This approach should help research on BW changes and selection for this trait in the future.
Disciplines :
Animal production & animal husbandry
Author, co-author :
Soyeurt, Hélène  ;  Université de Liège - ULiège > Agronomie, Bio-ingénierie et Chimie (AgroBioChem) > Modélisation et développement
Froidmont, E.
Dufrasne, Isabelle  ;  Université de Liège - ULiège > Dpt. de gestion vétérinaire des Ressources Animales (DRA) > Nutrition des animaux domestiques
Wang, Z.
Gengler, Nicolas  ;  Université de Liège - ULiège > Agronomie, Bio-ingénierie et Chimie (AgroBioChem) > Ingénierie des productions animales et nutrition
Dehareng, Frédéric  ;  Walloon Agricultural Research Center
Grelet, Clément ;  Université de Liège - ULiège > Doct. sc. agro. & ingé. biol. (Paysage)
Language :
English
Title :
Validation of the prediction of body weight from dairy cow characteristics and milk MIR spectra
Publication date :
August 2019
Event name :
70th Annual Meeting of the European Federation of Animal Science
Event organizer :
EAAP - European Federation of Animal Science
Event place :
Ghent, Belgium
Event date :
26-30 August 2019
Audience :
International
Main work title :
Book of Abstracts of the 70th Annual Meeting of the European Association for Animal Production
Publisher :
Wageningen Academic Publishers, Wageningen, Netherlands
Edition :
Ghent 2019
ISBN/EAN :
978-90-8686-339-6
Collection name :
Nº. 25
Pages :
606
Peer reviewed :
Peer reviewed
European Projects :
FP7 - 613689 - GPLUSE - Genotype and Environment contributing to the sustainability of dairy cow production systems through the optimal integration of genomic selection and novel management protocols based on the development
Funders :
CE - Commission Européenne [BE]
Available on ORBi :
since 15 October 2019

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