Method for predicting degree that rice is contaminated by aspergilli based on electronic nose

Abstract

The invention discloses a method for predicting the degree that rice is contaminated by aspergilli based on an electronic nose. The method comprises the steps that after the rice is subjected to ultraviolet sterilization, the aspergilli is inoculated on the rice; by using the electronic nose, samples obtained after the rice stored for different time is inoculated are subjected to headspace gas detection; by using the plate count method, the number of bacterial colonies on the rice samples is detected; according to principal component analysis, an electronic nose sensor array is optimized, andthe optimized sensor response signals are subjected to feature extraction by using the stable value method; a prediction model based on electronic nose signal feature values and the number of the bacterial colonies is built by using the modified support vector machine (GA-SVM) algorithm optimized based on the genetic algorithm, the regression model with a large correlation index and a low root-mean-square error is selected as a final prediction model for the number of the bacterial colonies, and therefore, the predicted number of the colony forming units is obtained. The method can quickly predict the degree that the rice is contaminated by the aspergilli, the rice samples are not damaged, the operation is simple, a good prediction effect si achieved, and the method is higher in practicalapplication value.

Description

technical field [0001] The invention belongs to the field of microbial detection and relates to a method for rapidly predicting the degree of rice infection by Aspergillus fungi based on an electronic nose. Background technique [0002] Rice is one of the most important food varieties in the world. About 50% of the world's population uses rice as a staple food, and more than 2 billion people in Asia use rice and its products as the main source of calorie intake. Over the years, my country's rice output has ranked first in the world, accounting for about 30% of the world's total rice output, accounting for about 1 / 3 of the domestic total grain output. And with the improvement of people's living standards and the increase of population, its consumption is also in a gradual upward trend. However, grains are rich in nutrients, and are very susceptible to fungal infection and deterioration under suitable moisture and temperature conditions. It is reported that the loss of agric...

AI Technical Summary

Problems solved by technology

[0003] Aiming at the problems of complex time-consuming, low efficiency and high cost of the current fungal detection methods, the present invention provides a method for rapidly predicting the degree of rice infection by Aspergillus fungi based on an electronic nose, which can more accurately and quickly identify contaminated rice degree without damaging the rice sample

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