Reference : Mid-infrared predictions of cheese yield from bovine milk
Scientific congresses and symposiums : Unpublished conference
Life sciences : Animal production & animal husbandry
Life sciences : Food science
Life sciences : Genetics & genetic processes
http://hdl.handle.net/2268/98234
Mid-infrared predictions of cheese yield from bovine milk
English
Vanlierde, Amélie [University de Liège - ULg > Sciences Agronomiques > Zootechnie > 2e an. master bioingé. : sc. agrono., fin. spéc. >]
Soyeurt, Hélène mailto [Université de Liège - ULg > Sciences agronomiques > Zootechnie >]
Anceau, Christine [Université de Liège - ULg > Chimie et bio-industries > Technologie des industries agro-alimentaires >]
Vanden Bossche, sandrine [Université de Liège - ULg > Chimie et bio-industries > Technologie des industries agro-alimentaires >]
Dehareng, Frédéric [Centre wallon des Recherches agronomiques > Département Valorisation des Produits Agricoles > > >]
Dardenne, Pierre [Centre wallon des Recherches agronomiques > Département Valorisation des Produits Agricoles > > >]
Gengler, Nicolas mailto [Université de Liège - ULg > Sciences agronomiques > Zootechnie >]
Sindic, Marianne mailto [Université de Liège - ULg > Chimie et bio-industries > Technologie des industries agro-alimentaires >]
Colinet, Frédéric mailto [Université de Liège - ULg > Sciences agronomiques > Zootechnie >]
31-Aug-2011
No
No
International
62nd Annual Meeting of the European Association for Animal Production
du 29 août 2011 au 1 septembre 2011
European Association for Animal Production
Stavanger
Norway
[en] Cheese yield ; MIR ; Prediction
[en] Economically, cheese yield (CY) is very important. Todate, empirical or theoretical formulae allow estimating the theoretical CY from milk fat and casein or protein content of milk. It would be interesting to predict CY during milk recording directly without the need to estimate milk components. Through the BlueSel project, 157 milk samples were collected in Wallonia from individual cows and analyzed using a mid-infrared (MIR) MilkoScanFT6000 spectrometer. Individual laboratory cheese yields (ILCY) were determined for each sample and expressed as g of dry coagulum/100 g of milk dry matter. An equation to predict ILCY from MIR was developed using partial least squared regression (Winisi III). A first derivative pre-treatment of spectra was used to correct the baseline drift. To improve the repeatability of the spectral data, a file which contained the spectra of samples analyzed on 5 spectrometers was used during the calibration. During calibration, 23 outliers were detected a nd removed from the calibration set. The ILCY mean of the final calibration set was 63.9% with a SD of 11.2%. The calibration (C) coefficient of determination (R²) was equal to 0.76 with a standard error (SE) of calibration of 5.5%. A full cross-validation (CV) was preformed to assess the robustness. R²cv was 0.72 with a SECV of 6.0%. The similarity between R²c and R²cv as well as between SEC and SECV permits to consider robustness of the developed equation as good. Even if it is planned to improve the equation with additional samples, this first equation will permit to study ILCY in the Walloon dairy cattle.
EPAN - GAA
Fonds Européen de Développement Régional - FEDER ; Région wallonne : Direction générale opérationnelle de l'Agriculture, des Ressources Naturelles et de l'Environnement - DGARNE
Researchers ; Professionals
http://hdl.handle.net/2268/98234

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