Two-dimensional correlation spectroscopy multi-scale modeling method for olive oil impurity identification

Abstract

The invention discloses a two-dimensional correlation spectroscopy multi-scale modeling method for olive oil impurity identification. The method comprises selecting the optimal two-dimensional wavelet basis, carrying out multi-scale decomposition and all layer respective reconstitution through the optimal two-dimensional wavelet basis, carrying out modeling and predicting on each layer of the reconstituted correlation spectrum through NPLS, acquiring a root-mean-square error subjected to cross validation, carrying out submodel fusion through the calculated weight, and evaluating multiscale-two dimensional correlation spectrum model result and performances through the predicted root-mean-square error and correlation coefficient. Compared with the routine model, the modeling method substantially improves a precision and reliability of a conventional Raman spectroscopy model, finds novel symptom information in a sample spectrum, prevents information loss, realizes simple and reliable Raman spectrum analysis and can be widely used in complex system spectral analysis.

Description

technical field [0001] The invention relates to a modeling method, in particular to a two-dimensional correlation spectrum multi-scale modeling method suitable for identification of olive oil adulteration. Background technique [0002] Olive oil is produced in the coastal countries of the Mediterranean Sea and has a history of thousands of years. It is known as the "Queen of Vegetable Oils" by the West. It can not only promote blood circulation, improve the endocrine system, not only has rich nutrition, but also has certain beauty effects , so it has won the favor of more and more consumers. The value of olive oil far exceeds other types of vegetable oils. In order to pursue high profits, unscrupulous traders blend a large amount of cheap vegetable oils with olive oil for extraction by pressing, such as sunflower oil, soybean oil, and hazelnut oil. Once these low-quality adulterated oils enter the market, they may pose a serious threat to human health, so a method that can ...

AI Technical Summary

Problems solved by technology

However, due to the complexity and serious overlapping of the Raman spectrum peaks of olive oil, especially the similar characteristics of the Raman spectrum peaks of various types of oils, the traditional Raman spectrum has poor resolution for olive oil doping identification.

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