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Columbus State University

Fuzzy Expert Systems: A More Human-Based Approach for Sensorial Evaluation of Coffee-Bean Attributes to Derive Quality Scoring

Abstract

dc:description.abstract

<p>In the coffee industry, "cupping" is the process of sensorial evaluations of coffee beans, also known as Sample Evaluation. This process is done for three major reasons: to determine the actual sensory differences between coffee samples, to describe the flavors of the samples, and to determine preference of product. In totality, cupping targets the measurement of the coffee's quality related to fragrance, taste, and appearance which are expressed with a final numerical score. When cupping, the expert judge writes down the individual components' scores (fragrance, aftertaste, acidity, body, etc.) and ranks their intensities for reference. Despite the fact the cuppers are using natural language statements in their judgment, they are required to use numerical values to evaluate the coffee bean attributes. Fuzzy systems allow an intuitive way of representing the judge's knowledge, by linguistically modeling the judge's perception of the coffee's attributes for sensorial evaluation of coffee-bean attributes to enhance the <em>Specialty Coffee Association of America</em> cupping process to derive quality scoring when grading specialty coffees. With a fuzzy expert system the judge's perception could be better assisted with a collection of linguistically expressed terms instead of numbers (complementary terms acting as shapers of the coffee bean's attribute score's gradation of meaning).</p>

Degree

thesis:*
Name thesis:degree_name
Computer Science - Applied Computing Track
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
TSYS School of Computer Science
Year dc:date.available
2016

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Livio, Javier A.
Contributors dc:contributor
  • Dr. Rania Hodhod
  • Dr. Shamim Khan
  • Dr. Alfredo Perez

Subjects

dc:subject × 9

Rights

Language dc:language
English

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:csuepress.columbusstate.edu:theses_dissertations-1233

Chain of custody

source
Harvested from
Columbus State University
Base URL
csuepress.columbusstate.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Livio, Javier A.. Fuzzy Expert Systems: A More Human-Based Approach for Sensorial Evaluation of Coffee-Bean Attributes to Derive Quality Scoring. Thesis thesis, 2016. https://csuepress.columbusstate.edu/theses_dissertations/242