This paper analyzes the correlations between selected technical, process and production factors, equipment profiles and water consumption statistics in four types of dairy plants. Dairy plants were surveyed both individually and in groups. Water consumption was most highly correlated (r > 0.868) with equipment profiles. The highest water consumption was observed in dairy plants operating milk powder departments. In those plants, organization and production factors could significantly reduce water consumption levels because in addition to milk powder, those plants also supplied eight other products. The indicators of water consumption per unit of the final product were correlated (at 0.820 > | r | > 0.663) with equipment profiles, the degree of process automation and employment. Variations in water consumption per unit of the final product were best explained in small plants supplying several products. The presented equations can be used to optimize water demand of various types of equipment and to determine the correlations with energy consumption for wastewater treatment. Our results can contribute to the development of water consumption models in dairy plants and the implementation of clean production standards.

Fruit and vegetable processing has a significant impact on the environment due to its consumption of a significant amount of water. Water consumption mainly depends on the type of production and the technology used. Water in fruit and vegetable processing plants is used as a raw material, an energy carrier, and in hydro transport, as well as for washing raw materials and maintaining production hygiene. The variety of technological operations carried out in the production process and the seasonality of production make it difficult to objectively assess the use of water in fruit and vegetable processing plants. Few available publications in this field provide numerical values of water unit consumption indices, with none entering into the cause-and-effect relationships of water use in plants in this industry. The aim of this study was to analyze the research to date and to verify the following research hypothesis: the structure of processing and the relationship between the weights of individual products have an impact on water consumption in fruit and vegetable processing plants. For this purpose, neural models of water consumption were developed for the largest agri-food processing plants in Poland that use similar technology. Water consumption was then optimized using genetic algorithms for the processing structure. The results confirmed the hypothesis that production structure has a significant impact on the rationalization of water consumption. The optimization results show that the production of concentrates, juices, and drinks has the greatest impact on water consumption. The lowest water consumption will be achieved when the production of concentrates is at a 2 to 1 ratio to the production of juices and drinks.

Fruit and vegetable processing comes 6th in terms of energy consumption in the agri-food industry. At the same time, 88.4% of the industry’s final energy consumption structure is thermal energy, which depends heavily on electricity consumption. In addition, fruit and vegetable processing has a significant impact on the environment due to consumption of significant amounts of water. Reducing these three indicators simultaneously would increase the efficiency of the process while improving environmental protection. This paper proposes neural models of thermal energy, electricity and water consumption for selected major fruit- and vegetable-processing plants in Poland. These models were the basis for formulating a multi-criteria optimization task. Optimization of thermal energy, electricity and water consumption was carried out using genetic algorithms. The optimization results in the sense of Pareto can be the basis for the use of sustainable technology in selected fruit- and vegetable-processing plants.