Artificial Intelligence in Alginite Research – Reinterpreting a Forgotten Hungarian Mineral Resource for Climate Adaptation and Water Retention

Abstract

Climate change, increasing water scarcity, and the growing demand for sustainable agricultural solutions have renewed interest in natural soil amendment materials worldwide. Hungarian alginite deposits were extensively investigated between the 1970s and 1990s; however, most research results remain archived in hard-copy reports, making their comprehensive evaluation difficult.

This paper presents the application of an artificial intelligence-supported Retrieval-Augmented Generation (RAG) knowledge base for the digitization, organization, and reinterpretation of archived  alginite literature. Approximately 120 Hungarian, German, Slovak, and English documents were processed and integrated into a unique searchable knowledge base.

The AI-assisted analysis enabled rapid synthesis of decades of research, identification of recurring scientific findings, and recognition of promising research and industrial opportunities relevant to present-day climate adaptation and agricultural water retention. The study demonstrates that while artificial intelligence cannot replace expert  geological interpretation, it can significantly accelerate literature review, support scientific synthesis, and facilitate the identification of new research directions based on historical geological knowledge.