## 3 Introduction  
Sugar beet molasses (molasses) is a common raw material used primarily in industrial fermentations, characterized by high dry matter and phenolic compound content [1; 2]. Sugar beet molasses provides high osmotic pressure during osmotic drying and has been recently utilized as a cost-effective alternative medium [3; 4; 5] to other conventional osmotic solutions for drying meat [6; 7; 8], fruits [9], vegetables [10], and plants [11]. In addition, it is shown that molasses's chemical compounds, such as polyphenols and inorganic salts, provide significant potential in reducing foodborne bacteria activities [12; 13]. Osmotic pressure, by which molasses is characterized with high values, is a colligative property of the solution, while osmolality presents a solution to the osmotic concentration, the measure of osmotic pressure [14]. Microorganisms experience osmotic stress when in contact with a hyperosmotic solution, such as molasses. Osmotic pressure changes cause significant stress on bacteria cells by leading to dehydration and shrinkage in hypertonic environments [15; 16]. Commission Regulation (EU) No 2073/2005 [17] identifies _Salmonella_, _E. coli_, and _L. monocytogenes_ as the most important microorganisms according to the food safety and process hygiene criteria. From a public health perspective, these three microorganisms are important for the following reasons:  
* _Salmonella_ is the most essential pathogen originating from poultry, owing to salmonellosis, one of the most frequent diseases in public health [18];
* _E. coli_ is an indirect indicator of fecal contamination and is exceptionally significant because of the highly pathogenic isolates of 0157:H7 [19; 20];
* _L. monocytogenes_, a significant foodborne pathogen, is sometimes correlated with poultry products and occasionally leads to clinical disease in poultry [19]. The microorganisms mentioned above possess different mechanisms to endure harsh environmental conditions. For example, _Salmonella_ exposure to an environment characterized by high osmotic pressure leads to water loss and subsequent significant cell shrinkage, a consequent increase of all intracellular metabolites' concentrations. In addition, instant plasmolysis can result in the inhibition of a variety of physiological processes, ranging from nutrient uptake to DNA replication [21]. _E. coli_ possesses different mechanisms that can persevere osmotic and desiccation stress and show long-term viability in challenging environmental conditions [22], while _L. monocytogenes_ have developed processes to withstand increased osmotic pressure via compatible solutes, intracellular accumulation, and the modification of the adaptive cell envelope and proteomes [23; 24]. A number of proteins are involved in the osmotic stress response of _L. monocytogenes_ cells [25]. These proteins include transport ones, compatible solute uptake, cell wall modification proteins, regulatory proteins, and proteins acting against general stress [21]. The possibility of applying artificial neural networks (ANNs) in diverse utilizations has caused it to become essential in modeling and optimizing food control and preservation processes [26; 27]. Artificial neural networks (ANNs) are applicable for clustering data libraries, understanding distribution patterns, and recognizing internal pathways. An ANN consists of a matrix with the cells as the network neurons, while the synapses are the connections between the cells [28; 29]. Synapses are specific negative or positive correlations between values in the cells. An ANN's structure defines the number of synapses of each cell or neuron. It can be only one of or several of them. The input neuron is the cell with entered data, while the output neuron is the cell with total values. The hidden neurons contain the algorithm that calculates a specific function or activation function, and these cells connect the input and output neurons.