Improving the prediction ability of FT-MIR spectroscopy to assess titratable acidity in cow’s milk

Paolo Bani, Luigi Calamari, Laura Gobbi

Risultato della ricerca: Contributo in rivistaArticolo in rivistapeer review

13 Citazioni (Scopus)

Abstract

This study investigated the potential application of Fourier transform mid-infrared spectroscopy (FT-MIR) for the determination of titratable acidity (TA) in cow’s milk. The prediction model was developed on 201 samples collected from cows in early and late lactation, and was successively used to predict TA on samples collected from cows in early lactation and in samples with high somatic cell count. The root mean square error of cross-validation of the model by using external validation dataset was 0.09 Soxhlet-Henkel/50 mL. Applying the model on milk samples from cows in early lactation or with high somatic cell count, the root mean square error of prediction was 0.163 Soxhlet-Henkel/50 mL, with a RER and RPD of 23.9 and 5.1, respectively. Our results seem to indicate that FT-MIR can be used in individual milk samples to accurately predict TA, and has the potential to be adopted to measure routinely the TA of milk.
Lingua originaleEnglish
pagine (da-a)477-484
Numero di pagine8
RivistaFood Chemistry
Volume192
DOI
Stato di pubblicazionePubblicato - 2015

Keywords

  • Milk

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