Method for detecting crab freshness grade based on machine olfaction

Abstract

The invention provides a method for detecting a crab freshness grade based on machine olfaction. The method aims at collecting smell information and detecting TVB-N of crab samples at different storage periods; pre-treating obtained smell information, wherein the step of pre-treating comprises average-filtering, baseline treatment, and removal of abnormal data; then selecting characteristics capable of effectively representing the smell information; reducing dimensions by adopting non-linear dimension-reducing Laplacian Eigenmap according to a multi-dimension characteristic; establishing a prediction model of the crab freshness grade since a visualized analysis result corresponds to a TVB-N detection result; taking classified information of the visualized result as outputting of the prediction model, and taking the effective characteristics as inputting; and testing the trained model by using a unknown sample to obtain a result of a final crab freshness grade. According to the invention, novel machine olfaction technology is adopted to detect the crab freshness grade. The method has advantages of simple sample treatment and fast detection speed, and has no damage on crabs, and has huge application value in aquatic product markets and people's daily lives.

Description

technical field [0001] The invention provides a method for detecting the freshness level of crabs based on machine sense of smell, and relates to the technical field of detection methods. Background technique [0002] In recent years, various food safety incidents have become increasingly prominent and exposed. As a big country in the production and consumption of aquatic products, my country has placed the safety of aquatic products in an extremely important position. For crab aquatic products, freshness is the biggest factor that consumers consider when buying, and when crabs are dying or dead, due to the decomposition of their own enzymes and the growth of various bacteria, the flesh will deteriorate and thus Cause sour-smelly fermentation, slowly volatilize gases with rotten characteristics such as nitrogen-containing products, amines, ammonia, alcohols, sulfur-containing products, and sometimes even produce toxic substances such as histamine, which cannot be destroyed u...

AI Technical Summary

Problems solved by technology

For crab aquatic products, freshness is the biggest factor that consumers consider when buying, and when crabs are dying or dead, due to the decomposition of their own enzymes and the growth of various bacteria, the flesh will deteriorate and thus Cause sour-smelly fermentation, slowly volatilize gases with rotten characteristics such as nitrogen-containing products, amines, ammonia, alcohols, sulfur-containing products, and sometimes even produce toxic substances such as histamine, which cannot be destroyed under high-temperature cooking If this toxin is eaten and causes food poisoning, the consequences will be disastrous

Traditional crab quality testing methods are mainly divided into sensory testing and physical and chemical testing, but sensory testing is affected by subjectivity, physical and chemical testing is more complex, takes a long time and is destructive.

[0003] At present, many patents have mentioned the introduction of the detection method for the freshness level of aquatic products, but no description has been found for the detection method for the freshness level of crabs. For products, the smell information changes relatively weakly during the storage process, so for common pattern recognition algorithms, including principal component analysis, linear discriminant analysis, etc., they cannot extract such weak change information, which reduces the detection accuracy

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