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Fried bread sticks (FBS) are one of the most widely consumed deep fried food products in China. Understanding the fat and moisture content in FBS will help consumers make healthy food choices as well as assist food processors to provide FBS with desirable quality. Rapid Fourier transform near-infrared methods (FT-NIR) were developed for determining fat and moisture content in FBS collected from 123 different vendors in Shanghai, China. FBS samples with minimum sample preparation (either finely or coarsely ground) were used for NIR analyses. Spectra of FBS were treated with different mathematic pretreatments before being used to build models between the spectral information and fat (7.71%–30.89%) or moisture (17.39%–32.65%) content in FBS. Finely ground samples may lead to slightly more robust PLS models, but the particle sizes of ground FBS samples did not seriously affect the predictability of the models with appropriate mathematical treatments. The fat and moisture content in FBS predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (fat, R2=0.965; moisture, R2=0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of fat and moisture content in FBS

Fat and Moisture Content in Chinese Fried Bread Sticks: Assessment and Rapid Near-Infrared Spectroscopic Method Development