Fast compositional analysis of ramie using near-infrared spectroscopy

Rapid and accurate determination of chemical compositions of ramie is crucial to its application. In this paper, calibration models were established using near-infrared (NIR) spectroscopy to predict the main chemical compositions of ramie. A wet chemical analysis method which was improved on the basis of Chinese national standard for getting calibration data was used in this paper. NIR data of 59 ramie samples were collected using Fourier transform near-infrared spectrometer. The calibration models of chemical compositions of ramie were derived by partial least square (PLS) regression. Prediction of chemical composition of independent ramie samples showed that these models were rapid and accurate in the chemical composition analysis, giving residual predictive deviation (RPD) value higher than 2.5. Such NIR calibration models can be utilized by ramie fiber manufacturers and breeding workers, in order to better manage the degumming process and evaluate the quality of ramie varieties.