A prediction method of mechanical damage degree of tea tree based on electronic nose

Abstract

The invention discloses an electronic nose based prediction method of the mechanical damage degree of a tea tree. The method comprises the steps of: selecting a no-damage tea tree as a detection object, performing mechanical damage to the tea tree in different degrees, putting the tea tree into a sample headspace device of an electronic nose and standing for a certain period of time, and then detecting the tea tree by the electronic nose; meanwhile, by using a no-damage tea tree as a control group, optimizing an electronic nose sensor array according to stepwise discriminant analysis, performing feature extraction to an optimized sensor response signal by using a stable value method, a wavelet analysis method and a quadratic term fitting method respectively, and selecting an optimal feature extraction method by two different pattern recognition algorithms; and finally establishing a quantitative prediction model between the feature value and the mechanical damage degree of the tea tree by a partial least squares regression algorithm. An identification method which can rapidly predict the mechanical damage degree of the tea tree is provided, the tea tree sample is not damaged, the operation is simple, and the prediction method has a good prediction effect and high popularization and utilization values.

Description

technical field [0001] The invention relates to a method for quickly detecting crop damage, in particular to a method for predicting the degree of mechanical damage of tea trees based on an electronic nose. Background technique [0002] According to statistics, the annual consumption of tea in my country has reached about 660,000 tons, and the per capita tea consumption is 0.45 kg / year. Tea has had an important impact on Chinese society, history, culture and real life. From a global perspective, tea has become a global natural beverage. And it is popular all over the world with its natural and healthy reputation, and its total consumption ranks first among all soft drinks except water. [0003] In addition, tea contains a variety of beneficial substances and has complete medical and health care effects. Such as tea polyphenols, which have the functions of anti-oxidation, scavenging free radicals, anti-cancer, bactericidal and anti-virus, anti-aging, beauty, regulating blo...

AI Technical Summary

Problems solved by technology

During the process of tea pruning and picking, tea leaves will be mechanically damaged, and every year due to mechanical damage to tea trees, the yield and quality of tea will cause huge losses

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