A Rule-Based Quality Analytics System for the Global Wine Industry

Lee, Carmen K.H., Law, Mo Yin Kris and Ip, Andrew W.H. 2021, A Rule-Based Quality Analytics System for the Global Wine Industry, Journal of Global Information Management, vol. 29, no. 3, pp. 1-18, doi: 10.4018/jgim.20210701.oa1.

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Title A Rule-Based Quality Analytics System for the Global Wine Industry
Author(s) Lee, Carmen K.H.
Law, Mo Yin KrisORCID iD for Law, Mo Yin Kris orcid.org/0000-0003-3659-0033
Ip, Andrew W.H.
Journal name Journal of Global Information Management
Volume number 29
Issue number 3
Start page 1
End page 18
Total pages 18
Publisher IGI Global
Place of publication Harrisburg, Pa.
Publication date 2021
ISSN 1062-7375
1533-7995
Keyword(s) Association Rules
Data Mining
Global Wine Industry
Physiochemical Property
Predictive Analytics
Quality Management
Sensorial Property
Wine Production
Summary The global wine-making industry has faced challenges due to the increasing demands of consumers, particularly in emerging markets such as China, Brazil, India, and Russia. Controlling the quality during wine production is one of the key challenges faced by global winemakers to produce wine with appropriate sensorial properties tailored to specific markets. The wine production quality is constituted from a number of environmental factors such as climate, soil, and temperature, which affect the sensorial properties and the overall quality. This paper proposed a rule-based quality analytics system (RBQAS) to capture physicochemical data during wine production and to investigate the hidden patterns from the data for quality prediction. It consists of IoT for data capture on a real-time basis, followed by association rule mining to identify relationships between sensorial and physicochemical properties of wine.
Language eng
DOI 10.4018/jgim.20210701.oa1
Indigenous content off
Field of Research 0806 Information Systems
0807 Library and Information Studies
1702 Cognitive Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30144052

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