DocumentCode :
3585970
Title :
Prediction model for amylose content of Malaysian rice grains via visible-shortwave NIR spectroscopy
Author :
Ibrahim, Syahira ; Rahim, Herlina Abdul
Author_Institution :
Process Tomography & Instrum. Res. Group (PROTOM-I), Univ. Teknol. Malaysia, Skudai, Malaysia
fYear :
2014
Firstpage :
41
Lastpage :
46
Abstract :
The amylose content is an essential element in determining the texture and taste of rice grains. This paper evaluates the use of VIS-SWNIRS in estimating the amylose content for seven varieties of rice grains available in the Malaysian market. Each type consists of 30 samples and all the samples are scanned using the spectroscopy to obtain a range of values between 680-1000nm. The Savitzky-Golay (SG) smoothing filter is applied to each sample´s data before the Principal Component Regression (PCR) technique is used to examine the data and produce a single value for each sample. This value is then compared with reference values obtained from the standard iodine colorimetric test in terms of its coefficient of determination, R2. Results show that this technique produced low R2 values of less than 0.50. In order to improve the result, the range should include a wavelength range of 1100-2500nm and the number of samples processed should also be increased.
Keywords :
agricultural products; chemical variables measurement; chemioception; colorimetry; infrared spectroscopy; organic compounds; principal component analysis; regression analysis; spectrophotometry; visible spectroscopy; Malaysian market; PCR technique; Savitzky-Golay smoothing filter; VIS-SWNIRS; amylose content prediction model; coefficient of determination; principal component regression; rice grain taste determination; rice grain texture determination; standard iodine colorimetric test; visible-shortwave NIR spectroscopy; wavelength 1100 nm to 2500 nm; Calibration; Conferences; Control systems; Correlation; Process control; Reflectivity; Spectroscopy; Amylose; VIS-SWNIRS; diffuse reflectance; principal component regression; rice grain;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Process and Control (ICSPC), 2014 IEEE Conference on
Print_ISBN :
978-1-4799-6105-4
Type :
conf
DOI :
10.1109/SPC.2014.7086227
Filename :
7086227
Link To Document :
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