Analysis of Water Consumption in Fruit and Vegetable Processing Plants with the Use of Artificial Intelligence

Abstract

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.

The Use of Artificial Neural Networks in Agricultural Plants

“…They use 634 data to analyze the results of optimizing fruit and vegetable processing technology. The results obtained that the lowest water consumption will be achieved when the concentrate production is at a ratio of 2 to 1 for juices and beverages [57]. Computational and data processing capabilities using ML have also been used to increase vegetable yields [58].…”

Multi-Criteria Optimization of Energy and Water Consumption in Fruit- and Vegetable-Processing Plants in Poland

“…It should be added that the results of the modeling of water consumption in fruit-and vegetable-processing plants by Trajer et al. [20] showed a definite impact of the production structure on the consumption.…”

“…The problem affects in particular African countries, where the demand for water, energy and food resources is increasing and communities have limited availability and affordability in these areas [19]. Optimization of water consumption in fruit and vegetable processing was achieved with the use of genetic algorithms [20]. The results obtained allow for the appropriate selection of the production structure to ensure the lowest water consumption.…”

Characteristics of Resistivity Variation in Deep Granite and In-Situ Detection Applications

“…It can result in project delays and increased construction costs in less severe cases, while in more severe cases, it can lead to well flooding and abandonment. Both research and engineering practice have consistently shown that water hazards have become the primary risk in the construction of deep well projects [5][6][7][8] . Therefore, improving the accuracy and reliability of engineering geological and hydrogeological investigations within the vertical shaft project area is a prerequisite for scientifically assessing water inflow risks and effectively managing water disaster.…”