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Quality evaluation of Chinese red wine based on cloud model.

Qingwei Xu¹, Kaili Xu¹

¹School of Resources and Civil Engineering, Northeastern University, Shenyang, China.

Journal of Food Biochemistry

|October 15, 2019

Summary

This study introduces a novel cloud model for red wine quality evaluation, integrating fuzziness and randomness for complex assessments. The proposed method successfully classified a red wine sample as "Good," validating its effectiveness.

Keywords:

cloud algorithm cloud model golden section method red wine sensory evaluation

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Area of Science:

Food Science
Artificial Intelligence
Data Analysis

Background:

Red wine quality determination involves numerous qualitative and quantitative factors.
Traditional evaluation methods struggle with the inherent complexity and uncertainty of wine quality assessment.
The global red wine market is substantial, with China being the largest consumer since 2013.

Purpose of the Study:

To introduce the cloud model, a novel approach for uncertainty transformation, into red wine quality evaluation.
To propose a new comprehensive cloud model algorithm based on the addition of two cloud models.
To validate the efficacy of the cloud model in red wine quality assessment.

Main Methods:

Development of a novel comprehensive cloud model algorithm.
Application of the cloud model to red wine quality evaluation.
Validation using gray relational analysis and fuzzy evaluation methods.

Main Results:

The proposed cloud model successfully evaluated a red wine sample as 'Good'.
The results demonstrated the model's capability to handle the uncertainty inherent in red wine quality assessment.
Validation confirmed the suitability of the cloud model for this application.

Conclusions:

The cloud model offers a robust method for evaluating red wine quality by addressing fuzziness and randomness.
This novel approach provides a valuable tool for the wine industry, enhancing quality assessment accuracy.
The study successfully integrated artificial intelligence techniques with sensory evaluation for wine quality analysis.