Determination of Degree of Retrogradation of Cooked Rice by near Infrared Reflectance Spectroscopy

1998 ◽  
Vol 6 (A) ◽  
pp. A355-A359 ◽  
Author(s):  
Seung-Yong Cho ◽  
Sung-Gil Choi ◽  
Chul Rhee

Near infrared (NIR) reflectance spectroscopy was used to determine the degree of retrogradation of cooked rice. Cooked rice samples were stored at 4°C for 120 hours, and the degree of retrogradation was measured every six hours during the storage time. Enzymatic method, using glucoamylase, was used as reference method for the determination of the degree of retrogradation. Spectral differences, due to retrogradation of cooked rice, were observed at 1434, 1700, 1928, 2100, 2284 and 2320 nm. 32 samples were used for calibration set and 16 samples were used for validation set. High correlations were achieved between degree of retrogradation determined by enzymatic method and by NIR with multiple correlation coefficient of 0.9753 and a standard error of calibration of 3.64%. Comparable results were obtained with 3.91% of standard error of prediction, when the calibration equation was applied to an independent group of samples. The moisture content of samples tested significantly affected the determination of degree of retrogradation by NIR. The critical moisture content for the determination of degree of retrogradation by NIR was found to be ca. 5% (W.B.). The results suggested that NIR spectroscopy might be used as a potential method for determining both the degree of retrogradation and gelatinization of cooked rice.

1998 ◽  
Vol 6 (A) ◽  
pp. A181-A184 ◽  
Author(s):  
Henryk W. Czarnik-Matusewicz ◽  
Adolf Korniewicz

The evaluation of near infrared (NIR) reflectance spectroscopy as a method for the determination of capsaicin (8-methyl-N-vanillyl-6-nonenamide)—an active ingredient in the antirheumatical plasters was examined. The analytical procedure for determining the capsaicin was carried out by conventional, time-consuming colorimetric method. Spectra of the 76 plaster samples were recorded in reflectance mode at 2 nm intervals in the range 1100–2500 nm using InfraAlyzer 500 (Bran+Luebbe GmbH). A comparison is made between two regression methods, stepwise multiple linear regression (MLR) and partial least squares regression (PLS). MLR and PLS regression were used for calibrations, with the aid of the software SESAME ver. 2.10 (Bran+Luebbe GmbH). The PLS method showed consistently lower standard error of calibration and higher R values with first and second difference equations. The first difference PLS regression equation resulted in standard error of calibration of 0.018 %, with an R of 0.95. Generalizability of both methods for prediction of capsaicin contents on independent data sets is discussed. Prediction accuracy for independent data sets was increased using PLS regression, but was poor for sample sets with laboratory-measured concentration ranges beyond those of the calibration set. The results in this study indicate that NIR technique has a high applicability to quantitative analysis of capsaicin content in antirheumatical plasters.


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