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Application of NIR spectroscopy in gluten detection as a cross-contaminant in food (CROSBI ID 666815)

Prilog sa skupa u zborniku | sažetak izlaganja sa skupa | međunarodna recenzija

Radman, Marija ; Jurina, Tamara ; Benković Maja ; Jurinjak Tušek, Ana ; Valinger, Davor ; Gajdoš Kljusurić, Jasenka Application of NIR spectroscopy in gluten detection as a cross-contaminant in food // Book of Abstracts 9th International Congress of Food Technologists, Biotechnologists and Nutritionists / Kovačević Ganić, Karin (ur.). Zagreb: Hrvatsko društvo prehrambenih tehnologa, biotehnologa i nutricionista, 2018. str. 152-152

Podaci o odgovornosti

Radman, Marija ; Jurina, Tamara ; Benković Maja ; Jurinjak Tušek, Ana ; Valinger, Davor ; Gajdoš Kljusurić, Jasenka

engleski

Application of NIR spectroscopy in gluten detection as a cross-contaminant in food

The determination of gluten is of critical importance when food screening is intended for special groups such as 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 (NIR) spectroscopy for detection of traces of gluten in rice, rice flour, corn flour and corn crown. In the cross-contamination simulation, two types of flour were used, added to the food in a percentage from 5 to 30%. Apart from the spectra of pure and contaminated samples, conductivity and total dissolved substance were monitored to determine changes in the samples. NIR spectroscopy was combined with chemometric techniques to determine at which wavelengths a gluten-free fingerprint can be detected. Although experiments were carried out with a NIR device that monitors molecular vibrations in the range of 904-1699 nm, the gluten fingerprint was successfully determined, regardless of the type of flour that was added to the rice and corn samples. All concentrations of the added flour were successfully determined and a model was developed to detect the concentration of the added flour. Even the conductivity showed good prediction potential. Regardless if the food that was contaminated, the R2 was over 0.9. Developed models can be used to predict possible contamination of any rice/flour and corn/flour in raw samples or samples prepared for cooking (in water).

NIR ; cross contamination, ; gluten ; modelling ; prediction

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Podaci o prilogu

152-152.

2018.

objavljeno

Podaci o matičnoj publikaciji

Book of Abstracts 9th International Congress of Food Technologists, Biotechnologists and Nutritionists

Kovačević Ganić, Karin

Zagreb: Hrvatsko društvo prehrambenih tehnologa, biotehnologa i nutricionista

978-953-99725-7-6

Podaci o skupu

9th International Congress of Food Technologists, Biotechnologists and Nutritionist

poster

03.10.2018-06.10.2018

Zagreb, Hrvatska

Povezanost rada

Prehrambena tehnologija