[en] Lameness in dairy cows is a concern for both producers and consumers. Milk midinfrared
(MIR) analysis could be an extra tool in the detection of lameness problems
for farmers. Th e aim of this study was to test the feasibility of detecting lameness
problems using MIR spectra from milk through the development of predictive
models. Th e data for this research was provided by RINDERZUCHT AUSTRIA
(2017), from their “Effi cient Cow” project and were recorded between July 2014 and
December 2014. Th e data sets used were the complete data set of 9811 records and
subsets according to lactation stage, parity, breed and hoof disease. Two types of preprocessing
were tried: fi rst derivative followed by a Standard Normal Variate (SNV)
transformation or second derivative followed by a SNV transformation. Th e fi rst and
second derivatives do not give the same results which highlights the importance of
pre-processing during model development. Th e best results were obtained for the
Heel horn erosion subset. However, the specifi c nature of the used data requires the
addition of more data coming from varied animals and farms and validation steps
before using this technology on a larger scale.
Research Center/Unit :
Département Agronomie, Bio-ingénierie et Chimie - Ingénierie des Productions Animales - Génétique, Génomique et Modélisation numériques
Disciplines :
Zoology
Author, co-author :
Mineur, Axelle ; Université de Liège - ULiège > Master bioingé.: sc. agro., à fin.
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