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Development and Validation of a Near-Infrared Spectroscopy Method for the Prediction of Acrylamide Content in French-Fried Potato

Adedipe Oluwatosin E., Johanningsmeier Suzanne D., Truong Van-Den, Yencho G. Craig
Journal of agricultural and food chemistry 2016 v.64 no.8 pp. 1850-1860
food availability, French fries, acrylamides, breeding, deep fat frying, discriminant analysis, fast food restaurants, freeze drying, gas chromatography-mass spectrometry, least squares, models, near-infrared spectroscopy, potato flour, potatoes, prediction, reflectance, screening, spectrometers
This study investigated the ability of near-infrared spectroscopy (NIRS) to predict acrylamide content in French-fried potato. Potato flour spiked with acrylamide (50–8000 μg/kg) was used to determine if acrylamide could be accurately predicted in a potato matrix. French fries produced with various pretreatments and cook times (n = 84) and obtained from quick-service restaurants (n = 64) were used for model development and validation. Acrylamide was quantified using gas chromatography–mass spectrometry, and reflectance spectra (400–2500 nm) of each freeze-dried sample were captured on a Foss XDS Rapid Content Analyzer-NIR spectrometer. Partial least-squares (PLS) discriminant analysis and PLS regression modeling demonstrated that NIRS could accurately detect acrylamide content as low as 50 μg/kg in the model potato matrix. Prediction errors of 135 μg/kg (R² = 0.98) and 255 μg/kg (R² = 0.93) were achieved with the best PLS models for acrylamide prediction in Russet Norkotah French-fried potato and multiple samples of unknown varieties, respectively. The findings indicate that NIRS can be used as a screening tool in potato breeding and potato processing research to reduce acrylamide in the food supply.