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AI and Machine Learning Sustainability Wood Drying Open Access Journal article

Bibliometric analysis of global trends and emerging technologies in wood drying

Felipe da Silva Gomes, Pedro Gutemberg de Alcântara Segundinho, Fabrício Gomes Gonçalves, Josinaldo de Oliveira Dias, Juarez Benigno Paes, Rodolpho Stephan Santos Braga, Glaucileide Ferreira, Nédia Pereira Correia Mendes Correia, Antonio Marcos Silva Pereira Figueiredo

12 March 2026 · Cadernos Cajuína

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Abstract

Wood drying is a crucial, energy-intensive stage in the timber industry that directly impacts final product quality. This study maps the recent global scientific output on the topic, employing a bibliometric and systematic analysis to identify key trends, challenges, and the underlying knowledge structure. A search of the Web of Science and Scopus databases yielded 56 articles published between 2020 and 2025, selected for thematic relevance and publication in journals with a Journal Citation Report (JCR) score ≥ 1.0. The results reveal a strong geographical concentration of research, with China and Brazil as the leading countries in publication volume. Thematic analysis classified the literature into five main axes (from computational modeling to advanced monitoring) and identified a clear transition from conventional methods to a "Smart Drying" model. The current trend converges towards the integration of simulations, non-destructive sensors, and machine learning, aiming to transform drying into a predictive, adaptive, and sustainable process to optimize both quality and efficiency.

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