SysSensory: A Web based Decision Support System for Sensory Analysis

SysSensory: A Web based Decision Support System for Sensory Analysis

Helena Alvelos (Center for Research and Development in Mathematics and Applications, Department of Economics, Management, Industrial Engineering and Tourism, University of Aveiro, Aveiro, Portugal), Leonor Teixeira (Institute of Electronics and Informatics Engineering of Aveiro / Research Unit on Governance, Competitiveness and Public Policies, Department of Economics, Management, Industrial Engineering and Tourism, University of Aveiro, Aveiro, Portugal), Ana Luísa Ferreira Andrade Ramos (Research Unit on Governance, Competitiveness and Public Policies, Department of Economics, Management, Industrial Engineering and Tourism, University of Aveiro, Aveiro, Portugal) and Ana Raquel Xambre (Center for Research and Development in Mathematics and Applications, Department of Economics, Management, Industrial Engineering and Tourism, University of Aveiro, Aveiro, Portugal)
Copyright: © 2020 |Pages: 15
DOI: 10.4018/JITR.2020040104
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Abstract

Sensory analysis is an area of the food industry to evaluate products' organoleptic characteristics. It encompasses a tasting process that produces large amounts of data used both in decisions about the products and to evaluate the tasters. In this context, some tools that usually support Industrial Engineering processes, can help making more reliable and timely decisions. The aim of this work is then to present a decision support system – SysSensory – developed to help food companies' deal with that data, by means of collecting, processing and visualizing it. Therefore, some statistical techniques incorporated in the system are explained, the specification of the system is described and some of the system's user interfaces are presented. SysSensory is considered a valuable contribute for researchers on Sensory Analysis, Statistics, as well as Information Technologies, and also for the food industry, for which it can be an innovative tool.
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Theoretical Background

Supporting the decision process in Sensory Analysis is complex and incorporates knowledge from different areas. In fact, Zeng, Ruan, and Koehl (2008) state that “sensory evaluation is a multidisciplinary topic which needs the common efforts of researchers, engineers, managers, and consultants having different professional backgrounds and different knowledge profiles”. The same authors (Zeng, Ruan, & Koehl, 2008) identify the need for the development of new computing methods or adapting existing techniques in order to model and analyze sensory evaluation from sensory data.

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