Abstract
The potential of visible and near infrared (Vis-NIR) spectroscopy to distinguish wet-pockets from normal subalpine fir (Abies lasiocarpa Hook) wood was evaluated. Two specimen classes were used, namely, wood with more than half of the surfaces covered by wet-pockets (WW), and wood completely free of wet-pockets (NW). A partial least square (PLS) regression model was derived and calibrated to predict moisture content ranging from 0 to 210%, and its usefulness for moisture-based sorting of green lumber was assessed. Samples were sorted into the two classes after Vis-NIR scanning via two models: (1) soft independent modeling of class analogy (SIMCA) and (2) PLS discriminant analysis. The SIMCA model using second derivatives and wavelengths spanning 650 to 1150 nm successfully classified 98% of WW and NW in the green state, while it resulted in misclassification of 96% of the specimens after air-drying. The discriminant PLS model using wavelengths spanning 650–1150 nm, correctly classified WW and NW 96% in the green state and 100% after air-drying, respectively. These results clearly demonstrate the applicability of Vis-NIR spectroscopy to discriminate wet-pockets from normal wood.
Zusammenfassung
Untersucht wurde die Möglichkeit, Nasskern von Tannenholz (Abies lasiocarpa Hook) von normalem Holz mittels Spektroskopie im sichtbaren und im Nahinfrarotbereich (Vis-NIR) zu unterscheiden. Zwei Gruppen von Prüfkörpern wurden untersucht: Holz mit über 50 % Nasskern an der Oberfläche (WW) und Holz ohne Nasskern (NW). Zur Bestimmung des Feuchtegehaltes im Bereich 0 bis 210 % wurde ein partielles Regressionsmodell (PLS) hergeleitet und kalibriert sowie dessen Anwendbarkeit zur Sortierung von frischem Schnittholz nach der Holzfeuchte beurteilt. Nach der Vis-NIR-Prüfung wurden die Proben mittels zweier verschiedener Diskriminanzanalysen (SIMCA, PLS) in die zwei Gruppen eingeteilt. Mit dem SIMCA-Modell, das zwei Ableitungen und Wellenlängen im Bereich von 650 bis 1150 nm verwendet, konnten 98 % WW und NW im frischem Zustand richtig zugeordnet werden, wohingegen nach der Lufttrocknung 96 % falsch klassifiziert wurden. Das PLS-Modell mit Wellenlängen im Bereich 650 bis 1150 nm klassifizierte im frischen Zustand 96 % WW und NW richtig und nach Lufttrocknung 100 % richtig. Diese Ergebnisse belegen deutlich die Anwendbarkeit der Vis-NIR-Spektroskopie zur Unterscheidung zwischen Nasskern und normalem Holz.
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Watanabe, K., Mansfield, S.D. & Avramidis, S. Wet-pocket classification in Abies lasiocarpa using spectroscopy in the visible and near infrared range. Eur. J. Wood Prod. 70, 61–67 (2012). https://doi.org/10.1007/s00107-010-0490-2
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DOI: https://doi.org/10.1007/s00107-010-0490-2