Claire Agabriel

Prediction of bulk milk fatty acid composition based on farming practices collected through on-farm surveys.

The aim of this study was to predict the fatty acid (FA) composition of bulk milk using data describing farming practices collected via on-farm surveys. The FA composition of 1,248 bulk cow milk samples and the related farming practices were collected from 20 experiments led in 10 different European countries at 44°N to 60°N latitude and sea level to 2,000 m altitude. Farming practice-based FA predictions [coefficient of determination (R(2)) >0.50] were good for C16:0, C17:0, saturated FA, polyunsaturated FA, and odd-chain FA, and very good (R(2) ≥0.60) for trans-11 C18:1, trans-10 + trans-11 C18:1, cis-9,trans-11 conjugated linoleic acid, total trans FA, C18:3n-3, n-6:n-3 ratio, and branched-chain FA. Fatty acids were predicted by cow diet composition and by the altitude at which milk was produced, whereas animal-related factors (i.e., lactation stage, breed, milk yield, and proportion of primiparous cows in the herd) were not significant in any of the models. Proportion of fresh herbage in the cow diet was the main predictor, with the highest effect in almost all FA models. However, models built solely on conserved forage-derived samples gave good predictions for odd-chain FA, branched-chain FA, trans-10 C18:1 and C18:3n-3 (R(2) ≥0.46, 0.54, 0.52, and 0.70, respectively). These prediction models could offer farmers a valuable tool to help improve the nutritional quality of the milk they produce.

Authentication of cow feeding and geographic origin on milk using visible and near-infrared spectroscopy

The ability of near-infrared spectroscopy to trace cow feeding systems and farming altitude was tested on 486 bulk milk samples from France and northwestern Italy. Milks were grouped into feeding systems according to the main forage in the diet. Partial least square discriminant analysis correctly classified 95.5, 91.5, and 93.3% of pasture versus maize silage, hay, and fermented herbage feeding systems, respectively. Discrimination was slightly less successful when diets with large proportions of the nondominant forage were included in each group. Near-infrared spectroscopy correctly discriminated no-pasture from pasture milk, even with only 30% of pasture in the diet (5.4% cross-validation error), and the error stabilized when pasture exceeded 70% (2.5% error). Near-infrared spectroscopy did not reliably trace milk geographic origin when the feeding system effect was isolated from the altitude effect. These findings may be usefully exploited for the authentication of dairy products.

Potential of milk fatty acid composition to predict diet composition and authenticate feeding systems and altitude origin of European bulk milk

The aims of this work were to elucidate the potential of using milk fatty acid (FA) concentration to predict cow diet composition and altitude of bulk milk collected in 10 different European countries and to authenticate cow-feeding systems and altitude of the production area using a data set of 1,248 bulk cow milk samples and associated farm records. The predictions based on FA for cow diet composition were excellent for the proportions of fresh herbage [coefficient of determination (R2)=0.81], good for hay, total herbage-derived forages, and total preserved forages (R2>0.73), intermediate for corn silage and grass silage (R2>0.62), and poor for concentrates (R2<0.51) in the cow diet. Milk samples were assigned to groups according to feeding system, level of concentrate supplementation, and altitude origin. Milk FA composition successfully authenticated cow-feeding systems dominated by a main forage (>93% of samples correctly classified), but the presence of mixed diets reduced the discrimination. Altitude prediction reliability was intermediate (R2<0.62). Milk FA composition was not able to authenticate concentrate supplementation level in the diet (<58% of samples correctly classified). Similarly, the altitude origin was not successfully authenticated by milk FA composition (<76% of samples correctly classified). The potential of milk FA composition to authenticate cow feeding was confirmed using a data set representative of the diversity of European production conditions.

Using visible or near infrared spectroscopy (NIRS) on cheese to authenticate cow feeding regimes

An experiment was conducted to evaluate the ability of two spectroscopy methods to distinguish between pasture and preserved-forage cheeses. The reflectance spectra of 308 fresh and freeze-dried samples of cows milk cheeses were recorded at wavelengths in the range of the visible, using a portable MINOLTA CM-2002 spectrophotometer. The reflectance spectra of the same samples were also measured in near infrared range using a non-portable laboratory monochromator NIRSystem 6500. The proportion of cheeses correctly classified by NIRS and visible spectra was respectively 0.96 and 0.91 for pasture samples, and 0.96 and 0.79 for preserved-forage samples. No significant differences were found when fresh and freeze-dried cheeses were compared. We conclude that NIRS is able to classify cheese samples from different regimes (here, pasture vs. preserved-forage).