Abstract :
[en] Recent research showed the usefulness of using estimated breeding values (EBV) for midinfrared
(MIR) based biomarkers in genetic improvement. Similarly, research has also shown
that genetic variation is contained in the absorbance traits along the MIR band of wavelengths.
Targeted extraction of the useful genetic variance can be achieved by the combination of
EBV. Direct estimation of EBV for absorbance traits was demonstrated. Our first objective
was to show that the reduction of the rank of the (co)variance structure among spectral traits is
possible by imposing linear functions, even if these functions represent lower accuracy MIR
biomarkers. MIR based biomarkers traits were derived from ongoing research in the FP7
GplusE project. In this study, the pathway from MIR spectra to the use in genetic
improvement will be described. First, blood reference phenotypic data was collected on
Holstein cows, at early lactation for IGF-1, glucose, urea, cholesterol, fructosamine, β-
hydroxybutyric (BHB) acid and non-esterified fatty acids (NEFA). These traits were calibrated
against corresponding MIR spectral data. Calibration 2
cv R ranged from 0.21 to 0.51, very low
from a chemometrical point of view, but potentially sufficient to extract useful spectral
variation. This was validated, using EBV that were based on these MIR predictions for
144,623 records (closest to days in milk 25), from 73,378 cows, in the Walloon region of
Belgium. Single-trait, but multi-lactation (1, 2, 3+) models yielded h2 estimates ranging from
0.07 to 0.27. At least 20 daughters with novel traits and official EBV for udder health, fertility
and longevity with minimum reliabilities of 70% were required; a total of 124 bulls met this
criteria. Standard selection index theory would usually rely on prediction error variance
minimisation and estimated population (co)variances. Alternatively in this study, Partial Least
Squares were applied to EBV for the milk MIR based biomarkers to develop novel genetic
predictors, for udder health, fertility and longevity, by extracting genetic variation along the
wave band after rank reduction. Using all bulls, correlations between best predictors and EBV
for udder health, fertility and longevity were at least 0.63, 0.67 and 0.62. Using selection
index theory and based on significant increases of prediction abilities of longevity (0.76
compared to 0.68 from udder health or fertility alone) using also milk MIR based blood
biomarkers, their potential contribution to genetic improvement of udder health, fertility and
longevity will be demonstrated.
