Predicting furan content in a fried dough system using image analysis

Abstract

The aim of this paper is to test different models for predicting furan content in a dough system, based 22 on partial least squares regression using colour images. Starch dough systems were fried at five 23 temperatures between 150 and 190°C and for 5, 7, 9, 11 and 13 minutes. The furan content was 24 quantified using gas chromatography/mass spectrometry, while the corresponding images were 25 simultaneously obtained and processed in order to extract 2914 features. The best predictions were 26 obtained using textural features (Rp = 0.92), when the number of features was reduced to just 10 by 27 algorithms applications. The results suggest that furan content in fried dough systems can be predicted 28 using features of colour images. 29 Keywords: Furan; non-enzymatic browning; image analysis; prediction of furan