Portable Raman optical spectrum olive oil discrimination data processing system

Abstract

The invention provides a portable Raman spectrum data processing system for olive oil real and false identification, comprising a Raman spectrometer, a housing, an analyzer panel, and a calculation and control device for the micro-controller. Wherein a near-infrared laser with a emission wavelength of 785nm is selected as the laser source the Raman spectrometer the laser energy parameter is selected between 100-200mw, time division parameter is selected between 5-20s. An optimum Raman peak strength is calculated from the two parameters mentioned, 5 spectrum scans are continuously carried out, and an average Raman spectrum of the 5 scanning is finally obtained, which ranges from 250-2300cm[-1]. The test sample is scanned with a resolution between 4-10cm[-1]. The calculation and control device for the micro-controller is used for obtaining Raman spectrum with flat baseline, with spectrum drawn by using corresponding strength of spectrum between 1265cm[-1] to 1441cm[-1] as horizontal axis, using corresponding strength of spectrum between 1657cm[-1] to 1441cm[-1] as vertical axis, and marking points of the sample therein.

Description

technical field [0001] The invention relates to a data processing system, in particular to a portable Raman spectroscopic data identification processing system for the authenticity of olive oil. 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 a lack of rapid screening and detect...

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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