| Summary: | 碩士 === 國立臺灣大學 === 生物產業機電工程學研究所 === 97 === Near-infrared (NIR) has been widely used in many fields; however, there are still some constraints in application due to the constructional differences among spectrometers. Even if the measurements conducted on the same sample, the spectral responses of instruments are different. Therefore, the databases and calibration models built on Master instrument can’t be used for the spectra measured by Slave instrument. In order to solve this problem, the method of Spectral Standardization has been developed.
In this research, Spectral Standardization Models were practically applied to the Sugar Content Inspection for Fruits. In this study, Standard Normal Variate (SNV)、Multiplicative Scatter Correction (MSC) and 1st Derivatives Spectral Pretreatment method were combined with the Spectral Mapping methods, such as Piecewise Direct Standardization, (PDS) and Support Vector Standardization (SVS) , in order to find the best Standardization strategy among different instruments. The Standardization ability will be evaluated by the Spectral prediction ability after standardization.
The best result for same type spectrometer but different associated apparatus was using PDS with 1st Derivatives. After Standardization, the SEP of slave instrument could be reduced from 3.01 °Brix to 1.27 °Brix, the RSEP also reduced from 21.11 % to 9.07 %. The best result for same type detectors but different optical design was using 1st Derivatives and PDS together, the SEP and RSEP of slave instrument were 15.95 °Brix and 112.94 % before Spectral Standardization; the SEP and RSEP were 0.95 °Brix and 6.73 % after Spectral Standardization, while the SEP and RSEP of master instrument were 0.67 °Brix and 4.91%. The Slave spectra after Standardization almost have the same prediction ability of sugar content as Master spectra, and can be directly applied to the databases built by master instrument.
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