Rapid detection method of peroxide value of vegetable oil

Abstract

A method for quickly detecting the peroxide value of vegetable oil and relates to a peroxide value detection method. The method comprises the following steps: S1, preparing a modeling sample; S2, measuring the peroxide value of the modeling sample; S3, collecting a Raman spectrum of the modeling sample; S4, establishing an optimum prediction model by a double-correction set; S5, measuring the peroxide value of a to-be-detected sample: acquiring the Raman spectrum of the to-be-detected sample, extracting a modeling waveband spectrum, evaluating an angle value of the spectrum of the to-be-detected sample and a reference spectrum, and substituting the angle value into the optimum prediction model to measure the peroxide value of the to-be-detected value. The method realizes quick detection on the peroxide value of large-batch vegetable oil by acquiring the Raman spectrum data of the vegetable oil sample and establishing a vegetable oil peroxide value prediction model by combining an angle measurement method, has the characteristics of high model accuracy, stability and anti-jamming capability, and is easy to popularize and use in quick detection on the peroxide value of the vegetable oil.

Description

technical field [0001] The invention relates to a method for detecting the peroxide value, in particular to a method for rapidly detecting the peroxide value of vegetable oil. Background technique [0002] The peroxide value of vegetable oil is an indicator of the degree of oxidation of oils and fatty acids, and is used to indicate whether vegetable oil has deteriorated due to oxidation. Long-term consumption of vegetable oil with excessive peroxide value is very harmful to human health, because peroxide can damage the structure of cell membrane, leading to gastric cancer, liver cancer, arteriosclerosis, myocardial infarction, hair loss and weight loss. The traditional method for detecting the peroxide value of edible vegetable oil is titration, but the titration method is complicated and time-consuming. In recent years, with the development of modern detection technology, some new technologies have been continuously used in the field of food detection, such as the partial ...

AI Technical Summary

Problems solved by technology

For this kind of spectral intensity instability, commonly used multiplicative correction methods include standard normal variable transformation (SNV) and multiple scatter correction (also called multiplicative scatter correction, MSC). SNV assumes that all variables have the same standard deviation, However, MSC assumes that multiplicative and additive changes are much larger than sample concentration or chemical properties, and these assumptions will be less effective for samples with wide changes in component properties.

Furthermore, the Extended Multivariate Scattering Correction method (EMSC) requires spectra of all pure substances in the sample that contribute to the spectra, limiting the application

The Optical Path Length Evaluation and Correction Algorithm (OPLEC) further proposes the Multiplicative Effect Model (MEM) for scattering correction. The above method can eliminate the multiplicative effect, but the principle and steps are relatively complicated

Due to the influence of the external measurement environment, the change of measurement conditions, and the interaction between components in complex systems, etc., the spectral intensity value of vegetable oil and the corresponding peroxide value have a nonlinear monotonic relationship, so the above methods are difficult. Promote the use in the detection of peroxide value of vegetable oil

The patent application with application publication number CN104931482A discloses a "Raman spectrum-based detection method for oxidative rancidity of Ganoderma lucidum spore oil", which can realize dynamic monitoring of oxidative rancidity of Ganoderma Rapid detection of oxidation value, but it still has the following disadvantages: the sample size of this method is small, only a single wave number (1655cm -1 ), the evaluation graph of Raman intensity and peroxide value was obtained by nonlinear fitting, and the stability of the light source, the transmission, scattering and focusing of the sample, the change of the integration time, and the change of the refractive index with the concentration of the liquid sample were not considered. Influenced by multiplicative effect, weak anti-interference ability

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