Abstract
In this paper, the authors used an acoustic wave acting as a disturbance (acoustic vibration), which travelled in all directions on the whole surface of a dried strawberry fruit in its specified area. The area of space in which the acoustic wave occurs is defined as the acoustic field. When the vibrating surface—for example, the surface of the belt—becomes the source, then one can observe the travelling of surface waves. For any shape of the surface of the dried strawberry fruit, the signal of travelling waves takes the form that is imposed by this irregular surface. The aim of this work was to research the effectiveness of recognizing the two trials in the process of convection drying on the basis of the acoustic signal backed up by neural networks. The input variables determined descriptors such as frequency (Hz) and the level of luminosity (dB). During the research, the degree of crispiness relative to the degree of maturity was compared. The results showed that the optimal neural model in respect of the lowest value of the root mean square turned out to be the Multi-Layer Perceptron network with the technique of dropping single fruits into water (data included in the learning data set Z2). The results confirm that the choice of method can have an influence on the effectives of recognizing dried strawberry fruits, and also this can be a basis for creating an effective and fast analysis tool which is capable of analyzing the degree of ripeness of fruits including their crispness in the industrial process of drying fruits.
Highlights
The customer expectations and information included in the EU Commission Regulation changed the criteria of the quality evaluation of products
Networks characterized by the greatest ability for classification were defined by the Multi-Layer Perceptron (MLP) model [41,42,43]
Individual structures differ in terms of the number of neurons in the hidden layer
Summary
The customer expectations and information included in the EU Commission Regulation changed the criteria of the quality evaluation of products. The approval of products has influence on, among other things, the looks [1], taste, aroma and texture [2], safety and nutritional values of products [3,4]. It is not allowed to accept an inadequate quality of fresh fruits, which can be, among other things, immature, overripe, moldy or too dirty. Sensors 2020, 20, 499 to choose a balanced diet. They nourish themselves increasingly healthily, which leads to an increased demand for healthy snacks. By selecting a proper method for the control of parameters during the drying process, products can keep their attractive sensory features and nutritional values
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