Near-infrared spectroscopy and data analysis for predicting milk powder quality attributes

Asma Khan, Muhammad Tajammal Munir, Wei Yu, Brent R. Young

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

Near-infrared (NIR) spectroscopy is a rapid analytical method for food products. In this study, NIR spectroscopy, data pretreatment techniques and multivariate data analysis were used to predict fine particle size fraction, dispersibility and bulk density of various milk powder samples, which are believed to have a significant impact on milk powder quality. Predictive models using partial least-squares (PLS) regression were developed using NIR spectra and milk powder physical and functional properties, and it was concluded that the PLS models predicted milk powder quality with an accuracy of 88-90 per cent.

Original languageEnglish
Pages (from-to)235-245
Number of pages11
JournalInternational Journal of Dairy Technology
Volume74
Issue number1
DOIs
Publication statusPublished - Feb 2021
Externally publishedYes

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