摘要
This study was conducted to find a method for rapid determination of fat content in complete quinoa （ Chenopodium quinoa Willd） seeds. The near infrared spectra of 100 quinoa samples were collected, and a mathematic model was built using the near infrared spectra, so as to perform prediction. The results showed that within the wavelength range of 1 0 000-4 000 cm ^-1 , the quantification model of fat content built by first derivative ＋vector normalization spectral pre-processing had better calibration and prediction effects, and showed a determination coefficient of cross validation （ r cv^ 2 ） of 0.939 3 and a determination coefficient of validation （ rval^2 ） of 0.923 5. The near infrared spectral model of fat could be used for rapid detection of fat contents in quinoa.
This study was conducted to find a method for rapid determination of fat content in complete quinoa （ Chenopodium quinoa Willd） seeds. The near infrared spectra of 100 quinoa samples were collected, and a mathematic model was built using the near infrared spectra, so as to perform prediction. The results showed that within the wavelength range of 1 0 000-4 000 cm ^-1 , the quantification model of fat content built by first derivative ＋vector normalization spectral pre-processing had better calibration and prediction effects, and showed a determination coefficient of cross validation （ r cv^ 2 ） of 0.939 3 and a determination coefficient of validation （ rval^2 ） of 0.923 5. The near infrared spectral model of fat could be used for rapid detection of fat contents in quinoa.
基金
Supported by Special Fund for the Protection and Utilization of Crop Germplasm Resources of the Ministry of Agriculture(2017NWB036-20)
Key Project of Shanxi Academy of Agricultural Sciences(YGG17064)
Key Research Plan Project of Shanxi Province(201603D21102)
