To establish a fast detection method during the purifying process of the extracts from Grardeniae using macroporous resin based on near infrared spectroscopy. First, the ethanol eluent was collected from the purification process of small size sample; and near infrared (NIR) spectrum was collected. Then the content of the geniposide was determined by HPLC method, and partial least squares (PLS) method was used to establish the quantitative model to predict the content of geniposide by NIR spectrum. This model was used to supervise the changes of geniposide concentrations in ethanol eluent during medium scale process. Experimental results showed that the NIR small scale model can accurately predict the concentrations of geniposide in the production process of medium scale. However, with the proceeding of batch processes, the prediction performance of the model was decreased, so model updating method was employed to maintain the model. After twice updates, the NIR quantitative model can accurately predict the concentrations of the geniposide during medium scale process. Therefore, through model updates, the established NIR quantitative model can be applied in different scales of macroporous resin purification processes, to improve the data utilization efficiency of small scale process and save the cost of rebuilding the quantitative model of medium scale.
Keywords: geniposide; macroporous resin; model transfer; near infrared spectroscopy; partial least squares.
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