From Empirical Wood Knowledge to Predictive Wood Physics

This resource was prepared primarily to organize and preserve a working collection of journals and books related to wood science and technology for future reference, reading, and research. It includes a journal guide, selected books grouped by subject, foundational mathematics and engineering texts, and a 282-row source-preservation bibliography. The book collection draws on “Books in the field of wood science and technology” by Niemz, Teischinger, and Sandberg (2025). This second version revises and expands the original resource under an updated title. The accompanying essay asks what modern wood physics and artificial intelligence contribute to practical prediction for an unfamiliar individual piece of wood when essential model inputs remain difficult to measure. It discusses growth geometry, anisotropic tensors, mathematically generated virtual growth structures, and the potential and limitations of inference from specific gravity and visually observed annual rings. The resource includes an English PDF and editable Jupyter notebook with Quarto metadata for Typst PDF output. It is a working bibliographic collection and conceptual synthesis, rather than a report of new experimental validation.