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Developing food sensory test system with preference test (Hedonic and Hedonic quality) wheat bread case study

机译:用偏好测试(享乐和享乐品质)小麦面包开发食品感官测试系统案例研究

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Bread is a food source of carbohydrates that are often consumed by the community. Various types of bread were produced to meet consumer's curiosity, one of which is wheat bread. Manufacturers must be able to produce quality wheat bread and liked by consumers. Increasing the quality of bread will certainly have an impact on sales to be generated. One of the efforts in improving the quality of wheat bread is by doing the Hedonic test and Hedonic Quality test. This study aims to develop a system capable of providing an assessment of wheat bread. This study develops machine learning system with supervised learning algorithm, then using the results of the initial Organoleptic test as Knowledge-Based (KB). This test involved detection, recognition, discrimination, scaling and ability to express likes or dislikes (hedonic quality), using expert judgment. Hedonic quality is used as a variable for assessing wheat bread products with 4 variables, which include flavor, taste, appearance, and texture. While the hedonic test using two classes: likes or dislikes. This KB used as Naive Bayes Classifier algorithm initial knowledge, The test results using 10 fold shown average accuracy 98.8%, while the final goal of the development of this system will create a system capable of providing an assessment of a wheat bread product.
机译:面包是社区经常消耗的碳水化合物的食物来源。为了满足消费者的好奇心,生产了各种类型的面包,其中一种是小麦面包。制造商必须能够生产优质的小麦面包并受到消费者的喜爱。面包质量的提高必将对将要产生的销售产生影响。改善小麦面包品质的一项工作是进行Hedonic测试和Hedonic Quality测试。这项研究旨在开发一种能够对小麦面包进行评估的系统。本研究开发了带有监督学习算法的机器学习系统,然后将最初的感官测试结果用作基于知识的知识库(KB)。该测试包括使用专家判断来检测,识别,区分,缩放和表达喜欢或不喜欢的能力(享乐品质)。享乐质量用作评估小麦面包产品的变量,具有四个变量,包括风味,味道,外观和质地。而享乐测试使用两个类:喜欢或不喜欢。此知识库用作Naive Bayes分类器算法的初步知识,使用10倍的测试结果显示平均准确度为98.8%,而该系统开发的最终目标将创建一个能够提供全麦面包产品评估的系统。

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