Original scientific paper
https://doi.org/10.31895/hcptbn.13.3-4.4
Application of NIR spectroscopy in gluten detection as a cross-contaminant in food
Marija Radman
; Faculty of Food Technology and Biotechnology, University of Zagreb, Croatia
Tamara Jurina
; Faculty of Food Technology and Biotechnology, University of Zagreb, Croatia
Maja Benković
; Faculty of Food Technology and Biotechnology, University of Zagreb, Croatia
Ana Jurinjak TUšek
; Faculty of Food Technology and Biotechnology, University of Zagreb, Croatia
Davor Valinger
; Faculty of Food Technology and Biotechnology, University of Zagreb, Croatia
Jasenka Gajdoš Kljusurić
; Faculty of Food Technology and Biotechnology, University of Zagreb, Croatia
Abstract
The determination of gluten is of critical importance when food screening is intended for special groups such as food ingredient intolerant and allergic persons. Cross-contamination of food that does not contain gluten is also possible in the sales chain. The aim of this study was to determine the applicability of Near-Infrared Spectroscopy (NIRs) for the detection of gluten traces in rice, rice flour, corn flour and corn grits. In the cross-contamination simulation, two types of wheat flour were used. They were added to rice, rice flour, corn flour and corn grits in a range from 5 % to 30 %. Apart from the spectra of pure and contaminated samples, conductivity and total dissolved solids were monitored to determine changes in the samples. NIR spectroscopy was combined with chemometric techniques to determine at which wavelengths a glutenfree fingerprint can be detected. Although experiments were carried out with a NIR instrument that monitors molecular vibrations in the range of λ= 904-1699 nm, the gluten fingerprint was successfully determined, regardless of the type of flour that was added to the rice, rice flour, corn flour and corn grits. All concentrations of the added flours were successfully determined and models were developed to detect the concentrations of the added flours. Even the conductivity showed good prediction potential in gluten determination. Regardless if the investigated samples were contaminated or not, the determination coefficient R2 was over 0.9. Developed models could be used to predict possible wheat flour contamination of any rice or corn product samples or samples prepared for cooking in water.
Keywords
NIR spectroscopy; cross-contamination; gluten; modelling; prediction
Hrčak ID:
217739
URI
Publication date:
19.12.2018.
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