1. Introduction
Chokeberry (
Aronia melanocarpa L.) is a rich source of valuable nutrients, among other things, vitamins and polyphenols. It is also characterized by a high content of antioxidants, which have a positive influence on improving eyesight as well as lower blood pressure [
1,
2] and lead to early inhibition of cancerogenic stages [
3,
4,
5]. The basic antioxidants that can be found in chokeberry fruit are anthocyanins [
6]. Anthocyanins are pigments, which give chokeberry fruit a characteristic dark color [
7]. Color intensity depends on pH; when pH is low, the color is intensely red; when pH rises, the color changes into dark blue [
8]. Chokeberry also contains valuable tannins (tanning agents), which are responsible for its sensory characteristics, giving chokeberry fruit a very characteristic tart taste [
9]. On account of that product obtained from chokeberry, including chokeberry powders, are widely used in functional and pro-health food as well as in all food industries as natural red and dark-blue dye. The still increasing customer awareness in recent years in terms of healthy nutrition leads to an increase in demand for food of natural origin characterized by pro-health properties. At the same time, a dynamically developing trend of foodstuffs fast to make at any moment and in any place, determine the development of instant food technology [
10]. Dried vegetable products, especially fruit products, are ideal semifinished goods used in the production of this type of food. Fruits could be dried as whole fruits or their particles, pastes, and juices. A very disadvantageous phenomenon regarding dried food products is the shrinkage of dried material, so changes in the shape and texture of the finished dried product are related to the breaking of capillaries during the drying process [
11]. In the case of drying paste and fruit juices, the most commonly used method is spray-dried method with carrier five such powders on a large scale is not easy due to their stickiness [
12].
These phenomena are linked with ahigh content of simple sugars and organic acids, which are characterized by the low temperature of verification (Tg). During the process of spray-drying, powders of different morphology and particle microstructure are formed [
10,
13]. It results from different conditions of drying such as the way and conditions of spraying liquid (i.e., rotary atomizer and its rotary speed), inlet temperature of drying air (inlet and outlet air temperature), physicochemical parameters of feed to be dried [
13]. One of the examples is increasing the inlet air temperature, which causes an increase in the speed of drying, and at the same time, causes lower shrinking of particles [
14]. In consequence, powder particles are characterized by bigger size and other microstructure are formed [
15]. When the inlet temperature of the spray-dried powder is low, the majority of particles show withered surfaces while increasing the inlet temperature results in a larger number of particles of smooth surfaces [
16]. A different situation occurs when rotary atomizer speed, then there is a tendency to form particles characterized by smaller sizes [
17]. The microstructure of powder particles, in turn, has an influence on functional parameters, which directly determine the abilities of their application. Flowability is one of the most important features of powders because it affects the powders’ behaviors in various processes, e.g., transport, mixing, and dosage [
5]. Parameters which have a substantial influence on powder looseness, among other things, are the particle size distribution, loose bulk density, tapped bulk density, the density of the powder particles, the volume of the interstitial air, moisture [
5,
18,
19,
20]. A particularly important parameter to characterize features of fruit powders on account of packaging processes, transport, and storing is loose and tapped bulk density. Fleck compaction in powder (compressibility) influences bulk density. Loose bulk density is a volume of loosely poured powdered material, while tapped bulk density that is shaken down is a volume of powder compressed in a normalized way (empty volumes between particles are eliminated) [
21,
22,
23]. Apart from numerous physical features of fruit powders, bioactive features are also crucial, which results from retaining properties of fresh fruit juices from which they are produced. It has an enormous meaning in the application of those powders, as pro-pro-health additives or as natural dyes used in the food and pharmaceutical industry [
5,
16,
20,
24]. In industrial production of such powders, a key issue is getting suitable quality, which is determined by given values of various physical and chemical parameters. Marking all parameters in the laboratory is time-consuming; thus a search for fast techniques of assessing the quality of powders during the production process is being continued at all times [
10].
In the face of diversity of neural networks resulting from using numerous architectures, a really important stage is the selection of those, which, in an ambiguous way, are able to solve a given problem that is under research. Classification is understood as finding such a classifier, which allows dividing the set of elements into groups, called classes [
25,
26,
27]. Elements belonging to one group are called objects. There can be differences between them, but not in case of properties, on account of which, they were assigned to a given class. One of the examples of neural networks used most commonly in classification issues is Multi-Layer Perceptron (MLP) [
28,
29]. It is a unidirectional network using a method of learning with a teacher [
30,
31], possessing a multi-layer architecture with at least one hidden layer [
10]. The only possible communication is the one between neurons in adjacent layers. The activating function for hidden neurons has a non-linear character (sigmoid character) [
32].
The aim of the research was to provide assessment and quality identification of chokeberry powders on the grounds of its dyeing capabilities as well as to gain the highest bioactivity (i.e., the highest content of anthocyanin and the highest value of antioxidant potential). In addition to the above, the quality assessment also included measuring the proper level of powders’ looseness (indirectly via microstructure and morphology of particles). In order to achieve this goal, a vision technique with a digital camera was used, using dying power on the outer surface as well as electron microscopy using the shapes of the inner structure (morphology structure) of spray-dried chokeberry juices. The utilitarian goal was to devise a neural model capable of classifying research samples of chokeberry powders, which does not stand out from industrial patterns with defined dyeing and bioactive properties and were as looseness properties in terms of color and structure. The authors verified the research results for the formulated neural models. The assessment error called RMS served as a quality indicator of the formulated models. The formulated neural models were characterized by a high degree of accuracy classification. Due to the above, the research aim of the paper was executed.
4. Conclusions
Utilization of the two vision techniques with a digital camera and scanning microscope found out that more efficient recognition of quality classes of stay dried chokeberry juice occurs when using color ratio. The best color space model having an influence on the ability to recognize digital images turned out to be the model YCbCr. On the basis of the PCA analysis, it was pointed out that the strongest correlation occurs for the component Y of the model YCbCr. Neural models, in which shape coefficients are included, demonstrated, like in the case of strawberry micro-particles [
10], that the efficiency of recognizing micro-particles is dependent on their diameter. On the basis of the PCA analysis, the strongest correlation occurs between Feret coordinates and other input variables determining shape coordinates. Size reduction of input variables in the PCA analysis, improved efficiency of recognizing the image of digital pictures as well as SEM, and at the same time improving the level of trying neural models.
The selection of input variables on account of the selection of factors in the process of drying substantially responds to the improvement of the abilities of the training network. The best-classified parameters in the process of drying were received during recognizing the degree of saccharification (DE) of carrier and different temperatures of drying between trials. It is confirmed by laboratory research of physicochemical and bioactive parameters that were done. An increase in inlet air temperature in the process of spray drying has a positive influence on changes in micro-particles, i.e., their sudden growth, and this results in increased efficiency of fruit powders as well as its looseness; however, it has a negative influence on bioactive properties [
5]. In case of the degree of saccharification of the carrier (DE), substantial statistical changes were noted down regarding the size of particles and powder looseness [
5]. The worst classification abilities in case variations of rotary atomizer speed are also confirmed by the quality assessment conducted in the laboratory. In the case of this variable for most marked parameters, substantial statistical changes in quality were not detected [
5].
The biggest classification abilities were reached by network typology, the Multi-Layer Perceptron. Neural models, which were characterized by the highest quality of degree classification on the level of 0.99, were reached by MLP networks with structure. 15:15-25-3:1, 12:12-3-2:1 and 15:15-10-2:1.