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Once upon a Time, There Was a Piece of Wood: Present Knowledge and Future Perspectives in Fungal Deterioration of Wooden Cultural Heritage in Terrestrial Ecosystems and Diagnostic Tools.

Daniela IsolaHyun-Ju LeeYong-Jae ChungLaura ZucconiClaudia Pelosi
Published in: Journal of fungi (Basel, Switzerland) (2024)
Wooden Cultural Heritage (WCH) represents a significant portion of the world's historical and artistic heritage, consisting of immovable and movable artefacts. Despite the expertise developed since ancient times to enhance its durability, wooden artefacts are inevitably prone to degradation. Fungi play a pivotal role in the deterioration of WCH in terrestrial ecosystems, accelerating its decay and leading to alterations in color and strength. Reviewing the literature of the last 25 years, we aimed to provide a comprehensive overview of fungal diversity affecting WCH, the biochemical processes involved in wood decay, and the diagnostic tools available for fungal identification and damage evaluation. Climatic conditions influence the occurrence of fungal species in threatened WCH, characterized by a prevalence of wood-rot fungi (e.g., Serpula lacrymans , Coniophora puteana ) in architectural heritage in temperate and continental climates and Ascomycota in indoor and harsh environments. More efforts are needed to address the knowledge fragmentation concerning biodiversity, the biology of the fungi involved, and succession in the degradative process, which is frequently centered solely on the main actors. Multidisciplinary collaboration among engineers, restorers, and life sciences scientists is vital for tackling the challenges posed by climate change with increased awareness. Traditional microbiology and culture collections are fundamental in laying solid foundations for a more comprehensive interpretation of big data.
Keyphrases
  • climate change
  • cell wall
  • big data
  • healthcare
  • artificial intelligence
  • machine learning
  • systematic review
  • oxidative stress
  • risk factors
  • quality improvement
  • human health
  • particulate matter
  • heat stress
  • deep learning