TY  - JOUR
T1  - The Use of VIS/NIR Hyper-Spectral Analysis on Moisture and Fat Content Predictions for Breaded-Fried Chicken Nuggets
AU - , Samira Kazemi AU - , Michael Ngadi AU - , Ning Wang AU - , Shiv O. Prasher 
JO  - Asian Journal of Information Technology
VL  - 5
IS  - 12
SP  - 1343
EP  - 1350
PY  - 2006
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2006.1343.1350
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2006.1343.1350
KW  - Deep-fat frying
KW  -partial least squares method
KW  -multivariate statistical analysis
AB  - Moisture and fat contents are two important parameters in quality evaluation of fried chicken nuggets. This study was undertaken to evaluate moisture and fat contents of fried breaded chicken nuggets using VIS/NIR hyper-spectroscopic technique. Breaded nugget samples were fried for different times in hydrogenated canola oil in order to obtain various levels of moisture and fat contents. Reflectance spectra of samples were collected within the range of 400-1750 nm using a spectroradiometer. Partial Least Squares (PLS) calibration models were developed for quantitative evaluation of the two parameters. The <I>R<SUP>2</I> </SUP>and Root Mean Square Error (RMSE) for each prediction were calculated to assess the prediction capability of the model. <I>R<SUP>2</I> </SUP>values of 0.92 were obtained from cross-validation of calibration for total moisture and fat contents. Validation of the calibration resulted in RMSE of 0.105 for moisture content and 0.017 for fat content predictions. VIS/NIR spectral analysis was proved to be a straightforward and fast method for prediction of the two important quality parameters of fried breaded chicken nuggets (moisture and fat) and once the calibration model was developed, the VIS/NIR instrument was capable of doing the analysis in few minutes.
ER  -