文献类型：期刊文献

英文题名：Prediction of saponin content in soapnut (Sapindus mukorossi Gaertn.) fruits by near infrared spectroscopy

作者：Li, Yanjie[1,2] Shao, Wenhao[1] Dong, Ruxiang[1] Jiang, Jingmin[1] Diao, Songfeng[1,3]

第一作者：李彦杰;Li, Yanjie

通信作者：Shao, Wenhao

机构：[1] Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Fuyang County, Zhejiang Province, China; [2] School of Forestry, University of Canterbury, Christchurch, New Zealand; [3] China Paulownia Research Centre, Non-timber Forest Research and Development Centre, Chinese Academy of Forestry, Zhengzhou city, Henan Province, China

年份：2018

卷号：26

期号：2

起止页码：95-100

外文期刊名：Journal of Near Infrared Spectroscopy

收录：EI(收录号：20194707720813);Scopus(收录号：2-s2.0-85043342651)

语种：英文

外文关键词：Near infrared spectroscopy - Infrared devices - Calibration - Spectrum analysis - Least squares approximations - Mean square error

摘要：In this study, near infrared spectroscopy has been demonstrated to quickly determine the saponin content in soapnut fruits. Partial least squares analysis combined with pre-processing methods and significance multivariate correlation variable selection was introduced to develop a statistical model calibrated for saponin content in soapnut fruits. The results showed that the first derivative yielded the best partial least squares calibration models with spectra of both the surface of dried fruits and the powder of dry seeded fruits with root mean square error of calibration values of 0.85% and 0.59%, respectively. The surface model presented less accuracy than the powder model. However, when the significance multivariate correlation variable selection method was applied to select the best variables from the spectra, the partial least squares models using spectra of surface and powder samples became similar, with higher R2 values (0.84 and 0.90), lower root mean square error of calibration values of 0.23% and 0.39%. It was suggested that near infrared spectroscopy could be a promising and rapid method for predicting the saponin content in the soapnut fruits without grinding them into powder. ? The Author(s) 2018.