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Development of an Intelligent Quality Control Model Based on Speaking Plant Approach and Kansei Information for Moss Greening Product

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2007 ASAE Annual Meeting  073104.(doi:10.13031/2013.23249)
Authors:   Mirwan Ushada, Haruhiko Murase
Keywords:   Artificial neural network, Kansei index, Local environment, Textural features, Wet weight

In this study, sub-systems of intelligent quality control based on speaking plant approach and kansei information were proposed. It consists of quality and quantity (growth) model. It utilizes Artificial Neural Network (ANN), plant response, kansei index and texture analysis. The first ANN model for quality is proposed to define the relationship between textural features and kansei index. Kansei index is measured using visual appearances as the representation of plant factory owner. The target point of the model is customer of moss product. The second ANN model for growth is proposed to define the relationship among plant response, textural features and temperature. Plant response is measured by using wet weight. The target point of the model is plant factory parameter.

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