Abstract
AbstractIn order to improve near infrared spectrum analysis precision, it is need to extract information from spectrum data. Derivative can not only eliminate spectrum background disturb , baseline drift and other factors influence, but also improve spectrum resolution ratio. However, at the same time derivative strengthen signal noise, reduce spectrum SNR (signal-to-noise ratio). Smoothing can effectively smooth high frequency noise, heighten spectrum SNR. In use of smoothing window’s size has a great effect on spectrum information extraction. This paper take near infrared spectrum of eucalyptus to research NIR spectrum information extraction methods, pay more attention on smoothing window’s size influence on spectrum information extraction. Then combine with multiple scatter correction and standardized variables to build eucalyptus lignin PLS model. The results showed that, using 1st derivative to combine with one of 19 point smoothing, multiple scatter correction, standardized variables to treat spectrum can all get good modeling result. In one word, spectrum information extraction can dislodge unfavorable factors influence and enhance spectrum analysis precision.KeywordsRoot Mean Square ErrorHigh Frequency NoiseEucalyptus WoodSpectrum InformationSpectrum Analysis PrecisionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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