Petisco C, García-Criado B, Mediavilla S, Vázquez de Aldana B R, Zabalgogeazcoa I, García-Ciudad A
Instituto de Recursos Naturales y Agrobiología, CSIC, Apdo. 257, 37071, Salamanca, Spain.
Anal Bioanal Chem. 2006 Nov;386(6):1823-33. doi: 10.1007/s00216-006-0816-4. Epub 2006 Oct 11.
Near-infrared reflectance spectroscopy (NIRS) was used to estimate N, neutral detergent fibre (NDF), acid detergent fibre (ADF), lignin and cellulose contents in leaves of a heterogeneous group of 17 woody species from the Central Western region of the Iberian Peninsula. The sample set consisted of 182 samples of leaves of deciduous and evergreen species, showing a wide range of concentrations determined by reference methods: 6.60-35.2 g kg-1 (N), 15.5-66.0% (NDF), 10.2-57.3% (ADF), 3.45-27.4% (lignin) and 5.79-31.3% (cellulose). Reflectance spectra, obtained for samples of dried and ground leaves, were recorded as log1/R (R=reflectance) from 1,100 to 2,500 nm. NIRS calibrations were developed using multiple linear (MLR) and partial least-squares (PLSR) regressions, and tested by external validation. Spectral data were transformed to the first and second derivative (1D, 2D). The PLSR method and derivative transformations provided the best statistics and showed lower standard errors of calibration (SEC) and higher coefficients of multiple determination (R2). In the external validation the standard errors of prediction (SEP) were 0.76 g kg-1 (N), 2.11% (NDF), 1.47% (ADF), 0.85% (lignin) and 0.86% (cellulose). The results obtained show that NIRS is very effective for the estimation of these organic constituents in leaf tissue of woody species. This technique can be used in ecological or ecophysiological studies as an alternative to the more time-consuming standard methods.
近红外反射光谱法(NIRS)用于估算伊比利亚半岛中西部地区17种不同木本植物叶片中的氮(N)、中性洗涤纤维(NDF)、酸性洗涤纤维(ADF)、木质素和纤维素含量。样本集包括182个落叶和常绿树种叶片样本,通过参考方法测定的浓度范围很广:6.60 - 35.2 g kg⁻¹(N)、15.5 - 66.0%(NDF)、10.2 - 57.3%(ADF)、3.45 - 27.4%(木质素)和5.79 - 31.3%(纤维素)。对干燥和研磨后的叶片样本获得的反射光谱记录为1100至2500 nm波长下的log1/R(R = 反射率)。使用多元线性(MLR)和偏最小二乘(PLSR)回归建立NIRS校准模型,并通过外部验证进行测试。光谱数据转换为一阶和二阶导数(1D,2D)。PLSR方法和导数转换提供了最佳统计结果,校准标准误差(SEC)较低,多重决定系数(R²)较高。在外部验证中,预测标准误差(SEP)分别为0.76 g kg⁻¹(N)、2.11%(NDF)、1.47%(ADF)、0.85%(木质素)和0.86%(纤维素)。所得结果表明,NIRS在估算木本植物叶片组织中的这些有机成分方面非常有效。该技术可用于生态或生态生理学研究,作为耗时较长的标准方法的替代方法。