Olive oil fast detection method adopting Raman spectrum characteristic peak signal intensity ratio

Abstract

An olive oil fast detection method adopting the signal intensity ratio of Raman spectrum characteristic peak comprises: scanning a test sample via a Raman spectrometer; attaining the Raman spectrometric chart of flat baseline via software; using the intensity of the peak corresponding to 1441cm<-1> wavelength as unit 1, to do spectra graph normalization; using the intensity ratio between the peak of 1265cm<-1> wavelength and the peak of 1441cm<-1> wavelength as horizontal coordinate and using the intensity ratio between the peak of 1265cm<-1> wavelength and the peak of 1441cm<-1> wavelength as longitudinal coordinate to draw chart, thereby calibrating the coordinates of the sample; using the longitudinal coordinate of 0.7 line as a boundary line for dividing real and false olive oils. The invention realizes fast, non-loss, low-cost and in-situ identification on real and false olive oils, and realizes in-situ and fast identification on the olive oil added with other different oils and the olive oils of different levels. The olive oil fast detection method has simple operation interface, and can visually distinguish olive oil from soybean oil, sunflower oil, rapeseed oil, corn oil, peanut oil and false olive oil.

Description

technical field [0001] The invention relates to a non-destructive detection technology for olive oil, in particular to a rapid detection method for olive oil using the signal intensity ratio of Raman spectrum characteristic peaks. Background technique [0002] Food safety issues have become the focus of global attention. Food safety incidents have spread widely, causing huge social impact and economic losses, and also posing an increasingly serious threat to human living environment and even health and safety. Fuyang "big-headed doll" incident, turbot incident and red-hearted duck egg scandal have aroused widespread attention at home and abroad. Time after time of food safety issues and crises have tested the capabilities of food regulatory agencies, and how to ensure food safety has become a major concern of the whole people. [0003] There are undoubtedly many reasons for these situations. One of the main reasons is that the detection technology is backward, and there is ...

AI Technical Summary

Problems solved by technology

The current reports generally use a large-volume Raman spectrometer and are based on a pattern recognition method. This method is abstract and has low accuracy. It requires operators to have professional knowledge and a dedicated data processing system. Therefore, it is difficult to popularize and promote, let alone on-site Rapid detection is not conducive to timely discovery and monitoring of management problems

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