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- W2349847470 abstract "Using ground milled rice as test example, various methods for spectra pretreatment and different regression method were compared to form a good regression equation for rice apparent amylose content (AAC) by near infrared reflectance spectroscopy (NIRS).The results were as follows: Scatter correction for spectra had insignificant effects on calibration, and Standard normal variate (SNV) could be used in option; The first derivative is better for mathematical treatment of the spectra value than second or third derivative, and the suitable Segment Gap combination was “1, 5, 5,1” for data collection; Regression method had obvious effect on calibration, and the best one was Modified Partial Least Square (MPLS) method. In summary, the optimal calibration procedures could be “SNV/1, 5, 5, 1/MPLS” for NIRS analysis of rice AAC when using ground milled rice as test sample. When using such calibration parameters, an ideal regression equation was obtained with a SEP (Standard Error for Performance) as low as 0.84 and a R 2 (Determination coefficient for validation) as high as 94%." @default.
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- W2349847470 title "Calibration optimization for rice apparent amylose content by near infrared reflectance spectroscopy (NIRS)" @default.
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