Forest Botany and Tree Physiology, Büsgen Institute, Georg August University Göttingen, Büsgenweg 2, 37077 Göttingen, Germany.
Plant Methods. 2011 Apr 10;7:9. doi: 10.1186/1746-4811-7-9.
There is an increasing demand for renewable resources to replace fossil fuels. However, different applications such as the production of secondary biofuels or combustion for energy production require different wood properties. Therefore, high-throughput methods are needed for rapid screening of wood in large scale samples, e.g., to evaluate the outcome of tree breeding or genetic engineering. In this study, we investigated the intra-specific variability of lignin and energy contents in extractive-free wood of hybrid poplar progenies (Populus trichocarpa × deltoides) and tested if the range was sufficient for the development of quantitative prediction models based on Fourier transform infrared spectroscopy (FTIR). Since lignin is a major energy-bearing compound, we expected that the energy content of wood would be positively correlated with the lignin content.
Lignin contents of extractive-free poplar wood samples determined by the acetyl bromide method ranged from 23.4% to 32.1%, and the calorific values measured with a combustion calorimeter varied from 17260 to 19767 J g-1. For the development of calibration models partial least square regression and cross validation was applied to correlate FTIR spectra determined with an attenuated total reflectance (ATR) unit to measured values of lignin or energy contents. The best models with high coefficients of determination (R2 (calibration) = 0.91 and 0.90; R2 (cross-validation) = 0.81 and 0.79) and low root mean square errors of cross validation (RMSECV = 0.77% and 62 J g-1) for lignin and energy determination, respectively, were obtained after data pre-processing and automatic wavenumber restriction. The calibration models were validated by analyses of independent sets of wood samples yielding R2 = 0.88 and 0.86 for lignin and energy contents, respectively.
These results show that FTIR-ATR spectroscopy is suitable as a high-throughput method for lignin and energy estimations in large data sets. Our study revealed that the intra-specific variations in lignin and energy contents were unrelated to each other and that the lignin content, therefore, was no predictor of the energy content. Employing principle component analyses we showed that factor loadings for the energy content were mainly associated with carbohydrate ring vibrations, whereas those for lignin were mainly related to aromatic compounds. Therefore, our analysis suggests that it may be possible to optimize the energy content of trees without concomitant increase in lignin.
人们对可再生资源的需求日益增长,以取代化石燃料。然而,不同的应用,如生产二次生物燃料或燃烧以产生能源,需要不同的木材特性。因此,需要高通量的方法来快速筛选大量样本中的木材,例如,评估树木育种或基因工程的结果。在这项研究中,我们研究了杂交杨后代(杨属黑杨×三角杨)的无提取木质素的木材中木质素和能量含量的种内变异性,并测试了其范围是否足以基于傅里叶变换红外光谱(FTIR)开发定量预测模型。由于木质素是一种主要的含能化合物,我们预计木材的能量含量与木质素含量呈正相关。
用乙酰溴法测定的无提取杨木样品的木质素含量范围为 23.4%至 32.1%,用燃烧量热计测量的热值为 17260 至 19767 J g-1。为了开发校准模型,应用偏最小二乘回归和交叉验证将衰减全反射(ATR)单元测定的 FTIR 光谱与木质素或能量含量的测量值相关联。在数据预处理和自动波数限制后,获得了最佳的模型,具有较高的决定系数(校准 R2(0.91 和 0.90);交叉验证 R2(0.81 和 0.79))和较低的交叉验证均方根误差(RMSECV = 0.77%和 62 J g-1),分别用于木质素和能量的测定。通过对独立组的木材样品进行分析,校准模型得到了验证,木质素和能量含量的 R2 分别为 0.88 和 0.86。
这些结果表明,FTIR-ATR 光谱法适用于大型数据集的木质素和能量估计的高通量方法。我们的研究表明,木质素和能量含量的种内变化彼此无关,因此木质素含量不是能量含量的预测因子。通过主成分分析,我们表明能量含量的因子负荷主要与碳水化合物环振动有关,而木质素的因子负荷主要与芳香族化合物有关。因此,我们的分析表明,在不增加木质素含量的情况下,可能有可能优化树木的能量含量。