mid-infrared; milk; minerals; Food Science; Microbiology; Health (social science); Health Professions (miscellaneous); Plant Science
Abstract :
[en] Measuring the mineral composition of milk is of major interest in the dairy sector. This study aims to develop and validate robust multi-breed and multi-country models predicting the major minerals through milk mid-infrared spectrometry using partial least square regressions. A total of 1281 samples coming from five countries were analyzed to obtain spectra and in ICP-AES to measure the mineral reference contents. Models were built from records coming from four countries (n = 1181) and validated using records from the fifth country, Austria (n = 100). The importance of including local samples was tested by integrating 30 Austrian samples in the model while validating with the remaining 70 samples. The best performances were achieved using this second set of models, confirming the need to cover the spectral variability of a country before making a prediction. Validation root mean square errors were 54.56, 63.60, 7.30, 59.87, and 152.89 mg/kg for Na, Ca, Mg, P, and K, respectively. The built models were applied on the Walloon milk recording large-scale spectral database, including 3,510,077. The large-scale predictions on this dairy herd improvement database provide new insight regarding the minerals' variability in the population, as well as the effect of parity, stage of lactation, breeds, and seasons.
Disciplines :
Food science Animal production & animal husbandry
Author, co-author :
Christophe, Octave S ; Walloon Agricultural Research Center (CRA-W), 24 Chaussée de Namur, 5030 Gembloux, Belgium
Grelet, Clément ; Walloon Agricultural Research Center (CRA-W), 24 Chaussée de Namur, 5030 Gembloux, Belgium
Bertozzi, Carlo; Elevéo Asbl, AWE Group, 4, Rue des Champs Elysées, 5590 Ciney, Belgium
Veselko, Didier; Comité du Lait de Battice Route de Herve 104, 4651 Battice, Belgium
Lecomte, Christophe; France Conseil Elevage, Maison du Lait, 42 Rue de Chateaudun, 75009 Paris, France
The authors would like to thank the Walloon Region and European Union?s INTERREG NWE program for their financial support of through OptiMIR and Happymoo project, as well as the FFG, Federal Ministry Republic of Austria, Digital and Economic Affairs, and the Federal Ministry Republic of Austria, Climate Action, Environment, Energy, Mobility, Innovation and Technology of Austria for their financial support through the D4Dairy project. This research received a partial financial support from the European Commission, Directorate-General for Agriculture and Rural De-velopment, under Grant Agreement 211708 and from the Commission of the European Communities through the ROBUSTMILK project (Grant Agreement 211708, FP7, KBBE-2007-1). The content of this paper is the sole responsibility of the authors, and it does not necessarily represent the views of the Commission or its services.Funding: The authors would like to thank the Walloon Region and European Union’s INTERREG NWE program for their financial support of through OptiMIR and Happymoo project, as well as the FFG, Federal Ministry Republic of Austria, Digital and Economic Affairs, and the Federal Ministry Republic of Austria, Climate Action, Environment, Energy, Mobility, Innovation and Technology of Austria for their financial support through the D4Dairy project. This research received a partial financial support from the European Commission, Directorate-General for Agriculture and Rural Development, under Grant Agreement 211708 and from the Commission of the European Communities through the ROBUSTMILK project (Grant Agreement 211708, FP7, KBBE-2007-1). The content of this paper is the sole responsibility of the authors, and it does not necessarily represent the views of the Commission or its services.
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