AI Optimization in Protein Isolate Production

ASNS Ingredient is implementing a research project under the Recovery Fund titled “Latvian Food Competence Center – Digitalization”, in accordance with the “Latvian Recovery and Resilience Facility Plan, Reform and Investment Direction 2.2 ‘Digital Transformation and Innovation of Enterprises’, Investment 2.2.1.3.i ‘Support for the Introduction of New Products and Services in Business'” implementation regulations.

Research title: “Application of Optimization Algorithms in the Production Process and Recipe Development of Protein Isolate.”

The research project is being carried out within the framework of the project of SIA “Latvijas pārtikas kompetences centrs“, No. 2.2.1.3.i.0/1/24/A/CFLA/002, in cooperation with SIA FIDEA.

Project implementation period: 02.01.2025 – 28.12.2026.

The goal of the project is to develop a prototype of an AI algorithm that will improve the recipes of produced protein isolate and by-products, increasing production efficiency and the quality of the final product.

The main activities include collecting data from production equipment, developing and validating AI algorithms, and integrating them into a cloud system. As a result of the project, a modern AI solution platform will be created, enabling faster and more accurate optimization of production processes, providing the company with a significant competitive advantage.

Within the framework of the research project, it is planned to develop artificial intelligence and linear mathematics algorithms for recipe optimization, as well as interactive panels for training and visualizing these algorithms. In addition, further development will involve analyzing model quality and exploring potential applications in the high-value food industry. The project is also expected to have a significant positive environmental impact (a green product), replacing meat and other products in food.

Planned project activities:

• Collection of laboratory data
• Development of a processing model
• Model validation in the laboratory
• Method development for implementation in the production facility
• Initial data collection from industrial equipment
• Transmission of industrial equipment data to the cloud
• Development of an administration panel

Expected result: A created and practically validated prototype.

It is expected that the implementation of such algorithms in production will reduce the number and scale of labor, time, costs, and unsuccessful attempts when trying to identify a new protein isolate recipe with specific properties. For example, if customers seek a protein isolate powder that produces a gel-like final product when used in food development, using algorithmic optimization tools, the manufacturer will be able to reach the desired result much faster and with fewer resources.

By using models capable of processing big data, the manufacturer positions itself among the few companies ready for future opportunities. Additionally, AI algorithms can help identify inefficiencies and anomalies in production processes that would not be possible without such models. It may even become possible to predict food quality non-conformities before the full production process is completed. All this will enable the manufacturer to save resources, make the company more sustainable, and improve profitability, supporting the Latvian economy.

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