Integrasi Kecerdasan Buatan dan Fermentasi Presisi untuk Pengembangan Protein Alternatif Berkelanjutan

Abstract

The growing global demand for protein and the increasing need for sustainable food systems have accelerated the development of alternative proteins as a solution to reduce the environmental impacts associated with animal-based food production. Among emerging technologies, precision fermentation has gained significant attention due to its ability to produce high-value proteins through engineered microorganisms. However, the complexity of biological systems and the need for continuous process optimization remain major challenges for large-scale implementation. This study aims to analyze the integrative role of artificial intelligence and precision fermentation in advancing sustainable alternative protein production. A qualitative approach was employed through a systematic literature review and conceptual analysis of reputable scientific publications addressing alternative proteins, precision fermentation, artificial intelligence, and bioprocess engineering. The findings reveal that artificial intelligence contributes to four critical areas, namely protein engineering, microbial strain optimization, fermentation process control, and the development of digital twins for data-driven decision-making. The integration of these technologies enhances production efficiency, accelerates innovation cycles, reduces development costs, and improves environmental sustainability through optimized resource utilization. This article argues that the convergence of artificial intelligence and precision fermentation represents a new paradigm for alternative protein production characterized by greater adaptability, efficiency, and sustainability. The study provides a conceptual contribution to the biotechnology and food innovation literature while offering practical and policy insights for supporting the transition toward sustainable food systems.