Perspectives of using artificial intelligence elements in bread baking

Abstract

Enterprises of bread baking sector produce traditional everyday products and, at the same time, this sector remains one of the most conservative ones. There are always new types of raw materials and additives on the market, but new recipes are developed traditionally based on the results of test baking. However, a technologically justified solution is not always optimal regarding nutritional value. The purpose of this work is consideration of the possibilities and prospects of using elements of artificial intelligence (AI) in bread baking based on examples from other sectors of the food industry and study the AI’s ability to analyze and evaluate (categorise) existing recipes of bread products. The initial stage of AI use is machine learning (ML), but today there are no unified electronic databases that can be used to fulfil the task. We took approved collections of recipes as the basis for filling such databases. In addition, technologically acceptable variations of the main recipe components and their mutual substitution were carried out. The base was analyzed using Microsoft Azure Machine Learning service and Google Cloud Machine Learning Engine. Normalised database with 5,000 variants of recipes of bakery products that can be manufactured in conditions of both large industrial companies and small bakeries were created. The ML showed that the system effectively determines the main components of recipes and can independently, with high accuracy, classify recipes entered by the user into categories "bread" or "enriched bread". The work showed the possibility and viability of using AI elements in the baking industry. The database can be used to design new bakery products with specified recipe composition and (after improvement) to model applications with specified chemical composition or biological value.