Fuzzy-neural-network-based tea leaf appearance quality quantification method

A technology of fuzzy neural network and quantification method is applied in the field of quantification of tea appearance quality to achieve the effect of good adaptability, improved adaptability, and accurate prediction of appearance quality.

Inactive Publication Date: 2012-07-18
DAMIN FOODSTUFF ZHANGZHOU CO LTD
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After searching, there are no relevant research reports on using instruments to quantitatively analyze the a...

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  • Fuzzy-neural-network-based tea leaf appearance quality quantification method
  • Fuzzy-neural-network-based tea leaf appearance quality quantification method
  • Fuzzy-neural-network-based tea leaf appearance quality quantification method

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Embodiment Construction

[0018] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0019] As a special embodiment of the present invention, figure 1 Shown is the principle step diagram of the method for quantitatively analyzing the appearance quality of tea leaves by using computer vision technology combined with fuzzy neural network method in the present invention. The method of the present invention comprises the following steps:

[0020] Step 1: Select a batch of representative tea samples (here refers to the same type of tea, such as green tea or black tea or oolong tea, etc.), and more than 3 tea judges with national qualification certificates, refer to the national standard GB / T14487-2008 , in the form of collective scoring and password review, under fair and just conditions, the appearance quality of each batch of tea samples is scored according to the 100-point system, and wrong, inconsistent or incomplete sensory scor...

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Abstract

The invention discloses a fuzzy-neural-network-based tea leaf appearance quality quantification method, which comprises the following steps of: (a) selecting a batch of representative samples, and carrying out sensory evaluation on the tea leaf samples by tea leaf tasters with national certificates so as to obtain the appearance grading values of the tea leaf samples; (b) obtaining the visible images of the appearances of tea leaves by adopting a computer vision technology, respectively extracting shape features and color features after carrying out pretreatment on the visible images, and carrying out principal component analysis on all extracted feature variables to obtain a group of uncorrelated new variables; (c) establishing a fuzzy-neural-network-based tea leaf appearance quality quantitative evaluation model, taking the front p principal component factors extracted in the step (b) as an input layer of a network, and taking the sensory evaluation grading value of the appearances of the tea leaves as a desired output of a fuzzy neural network model, wherein the fuzzy-neural-network-based tea leaf appearance quality quantitative evaluation model comprises an input layer, a fuzzy layer, a fuzzy rule calculation layer and an output layer; and (d) calculating the graded value of the appearance quality of unknown tea leaf samples by using the established fuzzy neural network model for tea leaf appearance quality.

Description

technical field [0001] The invention relates to an objective quantification method of tea appearance quality, in particular to a quantification method of tea appearance quality based on fuzzy neural network. Background technique [0002] The quality of tea is a comprehensive reflection of the cooperation and coordination of various components in tea, but the components of tea are very complex and cannot be expressed through the quantification of some internal components; therefore, at home and abroad, the quality of tea, Classification and value determination are mainly evaluated through human senses. The sensory evaluation method is relatively simple, and can identify and describe the flavor characteristics of tea, but the sensory evaluation results are determined by the sensory experience of tea judges, which is obviously random and uncertain, highly subjective, and poor in consistency . The use of instruments to quantify tea quality indicators can effectively avoid the ...

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Application Information

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IPC IPC(8): G01B11/24G01J3/46G06N3/02
Inventor 蒋艾青岳鹏翔
Owner DAMIN FOODSTUFF ZHANGZHOU CO LTD
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