Современные технологии блокчейна и искусственного интеллекта для контроля биопленки в пищевой промышленности. Обзор

Образование биопленки и ее устойчивость к применяемым традиционным методам очистки и дезинфекции в процессе переработки пищевых продуктов представляют значительную угрозу безопасности и качеству пищевых продуктов. Эти устойчивые микробные сообщества способствуют загрязнению, порче и, как следствие, развитию заболеваний пищевого происхождения, что подчеркивает необходимость инновационных и технологически ориентированных стратегий контроля. Целью данного научного обзора является анализ текущих и потенциальных возможностей применения блокчейна и искусственного интеллекта для мониторинга, контроля и предотвращения образования биопленок, а также определение направлений будущих исследований и практического применения этих технологий в области безопасности пищевых продуктов. Материалом для данного обзора послужили научные публикации 2020–2025 годов. Поиск проводили по ключевым словам в научных базах данных Scopus и Web of Science, Google Scholar и в Научной электронной библиотеке eLIBRARY.ru. Отбор публикаций проводили в два этапа: сначала по названию и аннотации, а затем на основе анализа полнотекстовых статей, соответствующих критериям включения. Анализ научных исследований последних лет показал, что такие современные цифровые технологии, как искусственный интеллект, открывают новые возможности для эффективного управления биопленками. В режиме реального времени блокчейн обеспечивает прослеживаемость санитарного состояния, случаев микробного загрязнения и принятых мер на всех этапах пищевой цепи. Кроме того, машинное обучение и мониторинг на основе датчиков способствуют оперативному контролю микробиологической стабильности, оценке рисков размножения микроорганизмов. В совокупности эти инструменты способствуют принятию решений на основе данных и более активному предотвращению загрязнения. Вместе с тем следует отметить, что интеграция данных требует значительных материальных затрат. Дальнейшие исследования должны быть направлены на совершенствование моделей искусственного интеллекта за счет повышения качества и расширения объема данных, а также на оценку надежности датчиков в промышленных условиях. Не менее важным направлением является изучение нормативно-правовой базы, обеспечивающей баланс между внедрением инноваций и соблюдением требований безопасности.

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