A food texture evaluation method using a magnetic food texture sensor is proposed for the visualization of food texture. The food texture sensor measures two time-series waves, one of force and one of vibration, during fracture of a food sample. Twenty profiles were extracted from the two waves. The evaluation method selected the profiles to use in the logistic model and determined the coefficients of the model based on the results of sensory tests. Laboratory experiments confirmed that the logistic model evaluated the food textures as radar charts. In addition, the model can potentially evaluate the food textures of unknown foods.
An effective evaluation method of food texture is required for food development. A conventional evaluation method is sensory test-based evaluation. Although the sensory test directly evaluates food texture, it requires many subjects and high cost. Another evaluation method is a use of food texture instruments. The instruments quantify food texture. However, its sensor has the simple function which measures load. Its evaluation performance is not enough for food texture evaluation. In this paper, we propose a food texture sensor. The sensor is based on a human tooth, and has the structure which is composed of a contactor, an elastomer membrane and a base. Two kinds of sensing elements detect displacement of the contactor. The sensing elements work as fast and slow adaptive receptors. In this paper, first the structure and function of human tooth are described. Second, the structure of the sensor is illustrated, and the principle is explained. Finally, a fabricated prototype is demonstrated. In addition, the effectiveness of the sensor is confirmed through experiments using the prototype and foods.
Food texture plays an important role in food preferences, and contributes to health through chewing and safety during swallowing in the elderly and children. Sensory evaluation by human panelists is a general method for evaluating food texture. However, sensory evaluation is qualitative, and is affected by individual differences and environmental factors. Commercially available food texture instruments are equipped with only one load cell, and are not sufficiently sensitive for detailed food texture measurements. In this study, we present a magnetic food texture sensor, which has a structure that mimics a human tooth. The principle of the sensor is based on changes in magnetic field strength. By using giant magnetoresistive elements and inductors, the sensor measures a load and vibration occurs on the contact surface. The sensor was used to experimentally assess four foods. The results show clear differences among the four foods. In addition, we demonstrated that the measurement data could be classified using a support vector machine analysis. These results reveal the characteristics of the sensor, which measures load and vibration simultaneously.
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