Characterization of Wheat Varieties Using Terahertz Time-Domain Spectroscopy

Terahertz (THz) spectroscopy and multivariate data analysis were explored to discriminate eight wheat varieties. The absorption spectra were measured using THz time-domain spectroscopy from 0.2 to 2.0 THz. Using partial least squares (PLS), a regression model for discriminating wheat varieties was d...

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Detalles Bibliográficos
Autores principales: Ge, Hongyi, Jiang, Yuying, Lian, Feiyu, Zhang, Yuan, Xia, Shanhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4507591/
https://www.ncbi.nlm.nih.gov/pubmed/26024421
http://dx.doi.org/10.3390/s150612560
Descripción
Sumario:Terahertz (THz) spectroscopy and multivariate data analysis were explored to discriminate eight wheat varieties. The absorption spectra were measured using THz time-domain spectroscopy from 0.2 to 2.0 THz. Using partial least squares (PLS), a regression model for discriminating wheat varieties was developed. The coefficient of correlation in cross validation (R) and root-mean-square error of cross validation (RMSECV) were 0.985 and 1.162, respectively. In addition, interval PLS was applied to optimize the models by selecting the most appropriate regions in the spectra, improving the prediction accuracy (R = 0.992 and RMSECV = 0.967). Results demonstrate that THz spectroscopy combined with multivariate analysis can provide rapid, nondestructive discrimination of wheat varieties.

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