Method for tracing to production places of market saffron via ATR-FTIR in combination with RBF neural network

Abstract

The invention relates to the technical field of identification of traditional Chinese medicines, and discloses a method for tracing to production places of market saffron via ATR-FTIR in combination with a RBF neural network. The method comprises the steps of 1, pretreating a sample; 2, collecting infrared spectrum data; 3, pretreating spectrum data; and 4, putting data into a model: putting dataacquired in the step 3 into a RBF neural network tracing model, and judging the production place of the sample according to a result. According to the method, the 129 collected saffron samples produced by 7 different countries are used as research objects, and a saffron production place judgment model having less limitation on the analysis samples is built by using an ATR-FTIR united quantitativeanalysis technique; the method provided by the invention is high in accuracy, high in analysis speed, less in sample consumption and low in detection cost, and does not need standard substances.

Description

technical field [0001] The invention relates to the technical field of identification of traditional Chinese medicinal materials, in particular to a method for tracing the origin of commercially available saffron by combining ATR-FTIR with RBF neural network. Background technique [0002] Saffron is the dry red stigma of Crocus sativus L., a plant of the Iridaceae family. It has the effects of promoting blood circulation and removing blood stasis, cooling blood and detoxifying, relieving depression and calming the nerves. It is one of the new "Zhejiang Bawei" varieties in Zhejiang Province. Saffron is native to the Mediterranean region, and the main production area in the world is in the Khorasan region in southern Iran. In 1986, my country began to introduce and cultivate it in Chongming Island, Shanghai, and Jiande, Zhejiang. Although Shanghai and Zhejiang are newly introduced places, due to different cultivation models, the quality of saffron is much higher than that in m...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the fact that the place of origin of saffron sold in the market is not clear, and consumers cannot correctly identify the origin of saffron on the market, the present invention provides an ATR-FTIR combined with RBF neural network to analyze the origin of saffron on the market. For the method of traceability of origin, the present invention takes 129 saffron samples collected from 7 different countries as the research object, utilizes the combined metrology analysis technology of ATR-FTIR, and establishes a method with less restrictions on the analysis samples (without considering the sampling method). year, processing, storage, brand, grade and other factors) saffron origin discrimination model, the method of the present invention has high accuracy, fast analysis speed, less sample consumption, low detection cost, and no standard product

Images