Determination Of Anthocyanins And Glucosinolates In Purple Cabbage By Infrared Spectrometry Method And Its Rapid Determination Model

Purple cabbage was a kind of hybrid vegetable with the same shape as the common Chinese cabbage,purple leaves,high content of dry matter and other characteristics.In recent years,the color and nutritional quality of vegetable leaves had become an important index to measure the commercial quality of vegetables,and the purple cabbage with dark purple leafy head had also attracted people’s attention.In order to improve the nutritional quality of purple cabbage,it was necessary to accurately determine the content of anthocyanin and glucosinolates in purple cabbage.Therefore,it had become an important task to study the content of anthocyanin and glucosinolates in purple cabbage quality breeding.In this study,86 samples of purple cabbage were used as experimental materials.The content of anthocyanin and glucosinolates in purple cabbage were determined by high performance liquid chromatography.Meanwhile,the data were determined and processed by Near Infrared Spectroscopy analyzer and software,and the fast detection model for anthocyanin and glucosinolates in purple cabbage was established.The results are as follows:1.Among the 86 anthocyanins in purple cabbage,the content of Cyanindin varied the most,ranging from 93.5 mg/kg to 12802.4 mg/kg,with the highest average content of 5741.20 mg/kg,while the contents of other anthocyanins were low and the range of variation was very small.2.Among the 86 components of glucosinolates in purple cabbage,the content of GBN varied the most,with the range of1.52μmol/g～11.75μmol/g,and the average content was the highest,with the content of 19.74μmol/g.The contents of other glucosinolates were low and the range of variation was small.3.Cyanindin and total anthocyanins NIR prediction model were the best effect,in the full spectrum of 400～1098nm,1100～2498nm,all use None through the first derivative(1,4,4,1)processing,RSQ were 0.9651,0.9657,1-VR ratio were 0.9421,0.9444,validation set RSQ were 0.947 and 0.951,respectively,which were all above 0.90,which could be applied to rapid screening of purple cabbage breeding materials.4.The NIR prediction models of 4OH and GBN in glucosinolate were the best,which were pretreated with detrend only(1,4,4,1)and weighted MSC(1,4,4,1)under the full spectrum of 400～1098nm and 1100～2498nm,respectively.RSQ were 0.7335 and 0.7833,1-VR were 0.6796 and 0.7047,respectively.And the validation set RSQ were 0.816 and 0.765,respectively,which all above 0.70.It could be applied to the rapid screening of breeding materials of purple cabbage.