A novel method to determine total sugar of Goji berry using FT-NIR spectroscopy with effective wavelength selection. (18th December 2017) - Li, Qi; Yu, Xiuzhu; Gao, Jin-Ming
ABSTRACT: This study investigated the feasibility of determining the content of Goji berry total sugar (GBTS) through Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometrics. A total of 114 Goji berry samples from different regions in China were scanned with a FT-NIR reflectance spectroscopic system. X-loading weights and correlation coefficients were utilised to identify the most influential wavelength after the selection of spectra processing methods. Partial least squares regression was applied to build models, and paired t test was used for external validation. The model with raw spectra after pre-treatment with Norris gap derivatives and effective wavelength of 8700–4000 cm −1, which were determined by the correlation coefficients, exhibited the best predicative ability. In addition, the determination coefficients (R 2 ) of calibration validation set were both greater than 0.9 when principal component number was 6. The model presents good performance, with root mean square errors (RMSE) of 0.406 and 0.695 for the prediction of calibration validation set, relatively. The use of FT-NIR spectroscopy to implement quick determination of GBTS is thus feasible.