Non-destructive preservation state estimation of waterlogged archaeological wooden artifacts

Abstract

Non-destructive preservation state estimation is an essential prerequisite for the preservation and conservation of waterlogged archaeological wooden artifacts. Herein, Near Infrared (NIR) spectroscopy coupled with orthogonal partial least squares discriminant analysis (OPLS-DA) were applied to assess sixty-four waterlogged archaeological woods collected from seven excavation sites in the period range of 2900 BCE-1912 CE, aiming at developing a non-destructive, accurate and rapid preservation state estimation methodology. The role of non-decayed recent wood of relevant species on preservation state estimation was studied in prior, showing the use of non-decayed recent wood could not improve the predictive ability. Besides, the high variability in terms of chemical structure between archaeological softwoods and archaeological hardwoods did affect the preservation state estimation. Thus, a simple OPLS-DA model of non-destructively distinguishing archaeological hardwoods from softwoods, R2Xcum of 0.659, R2Ycum of 0.836 and Q2cum of 0.763, was established to avoid and overcome destructive approach for wood identification. Then, the well-defined three grouped separations of slightly-decayed, moderately-decayed and severely-decayed waterlogged archaeological woods were revealed in OPLS-DA models, providing R2Xcum of 0.793, R2Ycum of 0.738, Q2cum of 0.680, and R2Xcum of 0.780, R2Ycum of 0.901, Q2cum of 0.870, for waterlogged archaeological hardwoods and waterlogged archaeological softwoods respectively. Potential predictive wood spectral bands were screened and tentatively identified as hydroxyls of crystalline cellulose, acetyl groups of hemicelluloses, C-H bands of lignin, which guaranteed the elimination of non-structural compounds, such as water and inorganic components interference. Furthermore, the developed NIR methodology was validated by an extensively used destructive method consisting of anatomical characteristics, maximum water content and basic density analyses. The results indicated that NIR coupled to chemometrics could non-destructively and accurately predict the preservation states of waterlogged archaeological wooden artifacts and avoid the interference of water and inorganic deposits.