WEB SAS: sistema web para realização de testes de aceitação de alimentos de acordo com método afetivo de análise sensorial seguindo a escala hedônica

Abstract

Sensory analysis is an important area of ​​food science and technology that allows, based on sensory perceptions, to evaluate the characteristics of the most varied food products, using humans as a measuring instrument to evaluate characteristics such as appearance, aroma, flavor, sound and texture, as these characteristics directly reflect the intention of consumers to purchase or not a product. Normally, food acceptance tests involving sensory analysis are carried out by teams assembled to analyze and provide evaluative scores for the characteristics of the foods tasted. The scores provided will be interpreted to measure the level of acceptance and understand whether the food needs changes. The procedure for food acceptance tests involving sensory analysis is often done manually without using technological resources to collect and analyze the data, making the procedure time-consuming, and there are few software options with this functionality. Given this context, a responsive web application (here called Web SAS) was developed to automate some data collection and analysis procedures related to food acceptance tests considering the hedonic scale. The system was developed in a Model-View-Controller (MVC) architecture, using ReactJS, NodeJS and MongoDB technologies, having been tested in the field in carrying out food acceptance tests, in addition to being subjected to a usability test, following the System Usability Scale (SUS), in which it obtained good results.