Your browser doesn't support javascript.
loading
Effectiveness of mid-infrared spectroscopy for the prediction of cow milk metabolites.
Franzoi, M; Niero, G; Meoni, G; Tenori, L; Luchinat, C; Penasa, M; Cassandro, M; De Marchi, M.
Afiliación
  • Franzoi M; Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy.
  • Niero G; Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy. Electronic address: g.niero@unipd.it.
  • Meoni G; Magnetic Resonance Center (CERM) and Department of Chemistry "Ugo Schiff," University of Florence, 50019 Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), 50019 Sesto Fiorentino, Italy.
  • Tenori L; Magnetic Resonance Center (CERM) and Department of Chemistry "Ugo Schiff," University of Florence, 50019 Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), 50019 Sesto Fiorentino, Italy.
  • Luchinat C; Magnetic Resonance Center (CERM) and Department of Chemistry "Ugo Schiff," University of Florence, 50019 Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), 50019 Sesto Fiorentino, Italy.
  • Penasa M; Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy.
  • Cassandro M; Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy; Italian Holstein, Brown Swiss and Jersey Association (ANAFIBJ), Via Bergamo 292, 26100 Cremona, Italy.
  • De Marchi M; Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy.
J Dairy Sci ; 106(8): 5288-5297, 2023 Aug.
Article en En | MEDLINE | ID: mdl-37296050
Proton nuclear magnetic resonance (1H NMR) spectroscopy is acknowledged as one of the most powerful analytical methods with cross-cutting applications in dairy foods. To date, the use of 1H NMR spectroscopy for the collection of milk metabolic profile is hindered by costly and time-consuming sample preparation and analysis. The present study aimed at evaluating the accuracy of mid-infrared spectroscopy (MIRS) as a rapid method for the prediction of cow milk metabolites determined through 1H NMR spectroscopy. Bulk milk (n = 72) and individual milk samples (n = 482) were analyzed through one-dimensional 1H NMR spectroscopy and MIRS. Nuclear magnetic resonance spectroscopy identified 35 milk metabolites, which were quantified in terms of relative abundance, and MIRS prediction models were developed on the same 35 milk metabolites, using partial least squares regression analysis. The best MIRS prediction models were developed for galactose-1-phosphate, glycerophosphocholine, orotate, choline, galactose, lecithin, glutamate, and lactose, with coefficient of determination in external validation from 0.58 to 0.85, and ratio of performance to deviation in external validation from 1.50 to 2.64. The remaining 27 metabolites were poorly predicted. This study represents a first attempt to predict milk metabolome. Further research is needed to specifically address whether developed prediction models may find practical application in the dairy sector, with particular regard to the screening of dairy cows' metabolic status, the quality control of dairy foods, and the identification of processed milk or incorrectly stored milk.
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Leche / Metaboloma Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals Idioma: En Revista: J Dairy Sci Año: 2023 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Leche / Metaboloma Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals Idioma: En Revista: J Dairy Sci Año: 2023 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Estados Unidos