CNR-IVALSA, Istituto per la Valorizzazione del Legno e delle Specie Arboree, via Madonna del Piano, 10, I-50019, Sesto Fiorentino, FI, Italy.
Appl Spectrosc. 2013 May;67(5):553-62. doi: 10.1366/12-06819.
Wood degradation in waterlogged conditions, although slow, is relevant in some specific contexts, such as in the case of cultural heritage preservation (e.g., ancient shipwrecks found under the water table). This decay process induces the selective depletion of the biopolymers constituting wood cell walls and mainly of their structural polysaccharides (both cellulose and hemicelluloses). Assessment of residual composition of cell walls is normally carried out using conventional chemical analyses, which, however, require elevated amounts of material. The present work reports on a new approach to quantitatively determine the residual chemical composition of wood (in terms of amount of lignin and holocellulose) and therefore its extent of degradation. This was accomplished by acquiring attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectra on material still in waterlogged conditions, which was simply placed in optical contact with the ATR crystal. Data for the calibration set were obtained by means of wet analyses, and the calibration model was based on multivariate statistical analysis through partial least square regression. Acquired spectra showed signals higher and better resolved than for dry wood. Calibration was selected after comparing two different normalization procedures and after processing signals of two different spectral ranges. Furthermore, the exclusion of some outliers led to a substantial improvement in the error parameters (R(2) and root mean square error of cross validation) associated with the calibration model, thus allowing for the selection of the best model. The stability of this best model was also established by means of the leave-more-out method. Finally, a procedure of external validation confirmed that the proposed model also could be applied to similar (for instance, belonging to Pinaceae) wood remains from other excavations.
在一些特定情况下，水涝条件下的木材降解虽然缓慢，但仍然很重要，例如在文化遗产保护方面（例如，在地下水位以下发现的古代沉船）。这个降解过程会导致构成木材细胞壁的生物聚合物以及主要的结构性多糖（纤维素和半纤维素）选择性消耗。细胞壁的残留成分评估通常使用常规化学分析进行，然而，这种方法需要大量的材料。本工作报告了一种新的方法，可以定量确定木材的残留化学成分（以木质素和全纤维素的量来表示），从而确定其降解程度。这是通过在水涝条件下简单地将材料置于与 ATR 晶体光学接触的位置，来获取衰减全反射傅里叶变换红外（ATR FT-IR）光谱来实现的。校准集的数据是通过湿法分析获得的，校准模型基于多元统计分析，通过偏最小二乘回归建立。与干木材相比，获得的光谱显示出更高、分辨率更好的信号。通过比较两种不同的归一化程序，并对两个不同光谱范围的信号进行处理后，选择了校准。此外，排除一些异常值会显著改善与校准模型相关的误差参数（R² 和交叉验证均方根误差），从而可以选择最佳模型。通过“留出更多样本法”也可以确定最佳模型的稳定性。最后，外部验证程序证实，所提出的模型也可以应用于其他挖掘地点的类似木材（例如，属于松科）。
