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International audience; Despite its potential utility for predicting cows' milk yield responses to once-daily milking (ODM), the genetic basis of cow milk trait responses to ODM has been scarcely if ever described in the literature, especially for short ODM periods. This study set out to (1) estimate the genetic determinism of milk yield and composition during a 3-wk ODM period, (2) estimate the genetic determinism of milk yield responses (i.e., milk yield loss upon switching cows to ODM and milk yield recovery upon switching them back to twice-daily milking; TDM), and (3) seek predictors of milk yield responses to ODM, in particular using the first day of ODM. Our trial used 430 crossbred Holstein × Normande cows and comprised 3 successive periods: 1 wk of TDM (control), 3 wk of ODM, and 2 wk of TDM. Implementing ODM for 3 wk reduced milk yield by 27.5% on average, and after resuming TDM cows recovered on average 57% of the milk lost. Heritability estimates in the TDM control period and 3-wk ODM period were, respectively, 0.41 and 0.35 for milk yield, 0.66 and 0.61 for milk fat content, 0.60 and 0.80 for milk protein content, 0.66 and 0.36 for milk lactose content, and 0.20 and 0.15 for milk somatic cell score content. Milk yield and composition during 3-wk ODM and TDM periods were genetically close (within-trait genetic correlations between experimental periods all exceeding 0.80) but were genetically closer within the same milking frequency. Heritabilities of milk yield loss observed upon switching cows to ODM (0.39 and 0.34 for milk yield loss in kg/d and %, respectively) were moderate and similar to milk yield heritabilities. Milk yield recovery (kg/d) upon resuming TDM was a trait of high heritability (0.63). Because they are easy to measure, TDM milk yield and composition and milk yield responses on the first day of ODM were investigated as predictors of milk yield responses to a 3-wk ODM to easily detect animals that are well adapted to ODM. Twice-daily milking milk yield and composition were found to be partly genetically correlated with milk yield responses but not closely enough for practical application. With genetic correlations of 0.98 and 0.96 with 3-wk ODM milk yield losses (in kg/d and %, respectively), milk yield losses on the first day of ODM proved to be more accurate in predicting milk yield responses on longer term ODM than TDM milk yield.

The aim of this study was to investigate the effects of a severe nutrient restriction on mammary tissue morphology and remodeling, mammary epithelial cell (MEC) turnover and activity, and hormonal status in lactating dairy cows. We used 16 Holstein × Normande crossbred dairy cows, divided into 2 groups submitted to different feeding levels (basal and restricted) from 2 wk before calving to wk 11 postpartum. Restricted-diet cows had lower 11-wk average daily milk yield from calving to slaughter than did basal-diet cows (20.5 vs. 33.5 kg/d). Feed restriction decreased milk fat, protein, and lactose yields. Restriction also led to lower plasma insulin-like growth factor 1 and higher growth hormone concentrations. Restricted-diet cows had lighter mammary glands than did basal-diet cows. The total amount of DNA in the mammary gland and the size of the mammary acini were smaller in the restricted-diet group. Feed restriction had no significant effect on MEC proliferation at the time of slaughter but led to a higher level of apoptosis in the mammary gland. Gelatin zymography highlighted remodeling of the mammary extracellular matrix in restricted-diet cows. Udders from restricted-diet cows showed lower transcript expression of α-lactalbumin and kappa-casein. In conclusion, nutrient restriction resulted in lower milk yield in lactating dairy cows, partly due to modulation of MEC activity and a lower number of mammary cells. An association was found between feed restriction-induced changes in the growth hormone-insulin-like growth factor-1 axis and mammary epithelial cell dynamics.

International audience; The new challenges of the dairy industry require an accurate estimation of fine milk composition. The mid-infrared (MIR) spectrometry method appears to be a good, fast and cheap method for assessing milk fatty acid profile. Although partial least squares (PLS) regression is a very useful and powerful method to determine fine milk composition from the spectra, the estimations are not always very accurate and stable over time. Therefore a genetic algorithm (GA) combined with a PLS regression was used to produce models with a reduced number of wavelengths and a better accuracy. The results are a little sensitive to the choice of parameters in the algorithm. The number of wavelengths to consider is reduced substantially by 4 and accuracy is increased on average by 15%.