Building global models for fat and total protein content in raw milk based on historical spectroscopic data in the visible and short-wave near infrared range

Anastasiia Melenteva, Vladislav Galyanin, Elena Savenkova, Andrey Bogomolov

Research output

17 Citations (Scopus)

Abstract

A large set of fresh cow milk samples collected from many suppliers over a large geographical area in Russia during a year has been analyzed by optical spectroscopy in the range 400-1100 nm in accordance with previously developed scatter-based technique. The global (i.e. resistant to seasonal, genetic, regional and other variations of the milk composition) models for fat and total protein content, which were built using partial least-squares (PLS) regression, exhibit satisfactory prediction performances enabling their practical application in the dairy. The root mean-square errors of prediction (RMSEP) were 0.09 and 0.10 for fat and total protein content, respectively. The issues of raw milk analysis and multivariate modelling based on the historical spectroscopic data have been considered and approaches to the creation of global models and their transfer between the instruments have been proposed. Availability of global models should significantly facilitate the dissemination of optical spectroscopic methods for the laboratory and in-line quantitative milk analysis.

Original languageEnglish
Pages (from-to)190-198
Number of pages9
JournalFood Chemistry
Volume203
DOIs
Publication statusPublished - 15 Jul 2016

Scopus subject areas

  • Analytical Chemistry
  • Food Science
  • Medicine(all)

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