Department of Chemistry, University of Science and Technology of China, Hefei 230026, China.
Water Res. 2010 Apr;44(7):2229-34. doi: 10.1016/j.watres.2009.12.049. Epub 2010 Jan 7.
A near-infrared-reflectance (NIR) spectroscopy-based method is established to determine the main components of aquatic plants as well as their anaerobic rumen biodegradability. The developed method is more rapid and accurate compared to the conventional chemical analysis and biodegradability tests. Moisture, volatile solid, Klason lignin and ash in entire aquatic plants could be accurately predicted using this method with coefficient of determination (r(2)) values of 0.952, 0.916, 0.939 and 0.950, respectively. In addition, the anaerobic rumen biodegradability of aquatic plants, represented as biogas and methane yields, could also be predicted well. The algorithm of continuous wavelet transform for the NIR spectral data pretreatment is able to greatly enhance the robustness and predictive ability of the NIR spectral analysis. These results indicate that NIR spectroscopy could be used to predict the main components of aquatic plants and their anaerobic biodegradability.
建立了一种基于近红外反射（NIR）光谱的方法，用于确定水生植物的主要成分及其厌氧瘤胃生物降解性。与传统的化学分析和生物降解性测试相比，该方法更快、更准确。使用该方法可以准确预测整个水生植物中的水分、挥发性固体、克氏木质素和灰分，其决定系数（r（2））值分别为 0.952、0.916、0.939 和 0.950。此外，还可以很好地预测水生植物的厌氧瘤胃生物降解性，表现为沼气和甲烷产量。NIR 光谱数据的连续小波变换算法预处理能够极大地增强 NIR 光谱分析的稳健性和预测能力。这些结果表明，NIR 光谱可用于预测水生植物的主要成分及其厌氧生物降解性。
