Towards online Near-Infrared spectroscopy to optimise food product mixing

Angela Barone , Jarka Glassey, Gary Montague

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This paper advances the use of in-situ Near-Infrared (NIR) spectroscopy as the basis for an in-line control system to optimise mixing time of food powder blends. A non-contact NIR fibre-optic probe installed in a conical screw mixer was used to scan three powder mixtures characterised by different particle size distribution and component distribution. The current state of the art is extended by comparing Conformity Index and Standard deviation of the Moving Block Standard Deviation (MBSD), establishing the optimal pre-treatment combination and investigating the effects of the mixture properties on the results. Products with a broad particle size distribution were more accurately represented using derivatives rather than SNV and Detrending, while products with a broad component distribution showed good results with all pre-treatments.

This study evaluated the effect of data pre-treatments on mixing time for different physical properties of powder blends and provided a general guidance on the most appropriate pre-treatment.
Original languageEnglish
Pages (from-to)227-236
Number of pages10
JournalJournal of Food Engineering
Early online date5 Jul 2019
Publication statusPublished - 31 Dec 2019


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