Eating quality of cooked rice determination using Fourier transform near infrared spectroscopy

The goal of this research was to study the relationship between the eating quality of cooked rice and near infrared spectra measured by a Fourier Transform near infrared(FT-NIR)Spee-trometer.Samples of milled:parboiled rioe,white rioe,new Jasmine rice(harvested in 2012)and aged Jasmine rice(harvested in 2006 or during the period 2007-2011)were used in this study.The eating quality of the cooked rioe,ie,adhesiveness,hardness,dryness,whiteness and aroma,were evaluated by trained sensory panelists.FT-NIR spectroscopy models for predicting the eating quality of cooked rioe were established using the partial least squares regression.Among the eating quality,the stickiness model indicated its highest prediction ability(ie,R2a=0.71;.RMSEP=0.65;Bias=0.00;RPD=1.87)and SEP/SD of 2.In addition,it was clear that the water content did not affect the eating quality of cooked rice,rather the main chemical com-ponent implicated was starch.

Identification of syrup type using fourier transform-near infrared spectroscopy with multivariate classification methods

This research aimed to establish near infrared(NIR)spectroscopy models for identification ofsyrup types in which the maple syrup was discriminated from other syrup types.Thirty syruptypes were used in this research;the NIR spectra of each type were recorded with 10 replicates.The repeatability and reproducibility of NIR scamning were perfomed,and the absorbance atG940cn-1 was used for calculation,.Principal component analysis was used to group the syruptype.Identification models were developed by soft independent modeling by,class analogy(SIMCA)and partial least-squares diseriminant analysis(PLS.DA),The SiMCA models of alsyrup types exhibited accuracy percentage of 93.3-100%for identifying syrup types,whereasmaple syrup discrimination models showed percentage of accuracy between 83.2%and 100%.The PLS-DA technique gave the accuracy of syrup types classification bet ween 96.6%and 100%and presented ability on discrimination of maple syrup form other types of syrup with accuracyof 100%.The finding presented the potential of NIR spectroscopy for the syrup typeidentification.