Sensory evaluation and prediction of bulk wine by physicochemical indicators based on PCA-PSO-LSSVM method
Xu Zhang
College of Information and Electrical Engineering, China Agricultural University, Beijing, China
Contribution: Investigation, Methodology, Software, Writing - review & editing
Search for more papers by this authorHao Li
College of Information and Electrical Engineering, China Agricultural University, Beijing, China
Contribution: Investigation, Methodology, Software, Writing - original draft
Search for more papers by this authorWeisong Mu
College of Information and Electrical Engineering, China Agricultural University, Beijing, China
Contribution: Project administration, Resources, Supervision
Search for more papers by this authorValentina Gecevska
Ss. Cyril and Methodius University, Skopje, Macedonia
Contribution: Validation, Writing - review & editing
Search for more papers by this authorXiaoshuan Zhang
College of Engineering, China Agricultural University, Beijing, China
Contribution: Project administration, Resources, Supervision
Search for more papers by this authorCorresponding Author
Jianying Feng
College of Information and Electrical Engineering, China Agricultural University, Beijing, China
Correspondence
Feng Jianying, College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China.
Email: [email protected]
Contribution: Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing - review & editing
Search for more papers by this authorXu Zhang
College of Information and Electrical Engineering, China Agricultural University, Beijing, China
Contribution: Investigation, Methodology, Software, Writing - review & editing
Search for more papers by this authorHao Li
College of Information and Electrical Engineering, China Agricultural University, Beijing, China
Contribution: Investigation, Methodology, Software, Writing - original draft
Search for more papers by this authorWeisong Mu
College of Information and Electrical Engineering, China Agricultural University, Beijing, China
Contribution: Project administration, Resources, Supervision
Search for more papers by this authorValentina Gecevska
Ss. Cyril and Methodius University, Skopje, Macedonia
Contribution: Validation, Writing - review & editing
Search for more papers by this authorXiaoshuan Zhang
College of Engineering, China Agricultural University, Beijing, China
Contribution: Project administration, Resources, Supervision
Search for more papers by this authorCorresponding Author
Jianying Feng
College of Information and Electrical Engineering, China Agricultural University, Beijing, China
Correspondence
Feng Jianying, College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China.
Email: [email protected]
Contribution: Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing - review & editing
Search for more papers by this authorAbstract
It is difficult to implement the sensory quality evaluation of bulk wine before and after transportation due to geographical, time, cost, and personnel limitation. This study aimed to use the physicochemical indicators of bulk wine to construct an evaluation model of sensory quality. First, this paper designed and carried out the simulation experiment of bulk wine transportation and obtained experimental data on physicochemical and sensory indicators of wine. Afterwards, principal component analysis (PCA) was used to reduce the dimension and fuse features of the physicochemical index. Then, the extracted features were used as the input of the evaluation model, least square support vector machine (LSSVM) was constructed for sensory evaluation, and particle swarm optimization (PSO) algorithm was selected to optimize LSSVM parameters. Finally, the PCA-PSO-LSSVM model was practically applied in sampled winery. The results showed that comparing models’ accuracy the PCA-PSO-LSSVM model was superior to traditional models LSSVM and PSO-LSSVM, there is significant difference between PCA-PSO-LSSVM and LSSVM, and the predictive accuracy in appearance and taste attributes was high and the overall prediction accuracy was 86.6%. The application results revealed the changes of sensory quality for bulk wine after transportation. This research provides a set of simple and feasible methods for the sensory evaluation of bulk wine.
Practical applications
To study the method of using the basic physicochemical index of wine to intelligently evaluate the sensory attributes of bulk wine, so as to realize the accurate evaluation of the quality of bulk wine after transportation. By comparing the comprehensive and accurate quality evaluation before and after the bulk wine transportation, it is helpful for wine companies to understand the impact of the transportation link on the wine quality, further improve the transportation method of bulk wine, and ensure the quality of the wine has important practical significance.
CONFLICT OF INTEREST
The authors have declared no conflicts of interest for this article.
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