基于PLS算法的生物质秸秆元素分析NIRS快速检测
NIRS rapid detection of elemental analysis for straw biomass based on PLS algorithm

为探讨利用近红外光谱技术快速检测生物质秸秆中N、C、H、S和O元素的可行性，采集并制备水稻、小麦、油菜和玉米秸秆样本199个，采用近红外光谱(NIRS) 分析技术，结合偏最小二乘(PLS）化学计量学算法，在7400～5550 cm-1波段范围内，比较不同光谱预处理方法的定标效果，建立最优的生物质秸秆中N、C、H、S和O元素的定量分析模型，并用独立的验证集样本对模型进行验证。验证结果表明： 所建立的N元素的定量分析模型可用于实际检测； O元素的定量分析模型可进行实际估测； 采用近红外技术用于C元素定量分析是可行的，但模型需要进一步优化； H、S元素采用NIRS技术无法进行定量分析。
To investigate the feasibility of fast detection of the elements of N, C, H, S and O of straw biomass by using the near-infrared spectroscopy (NIRS) technology, 199 straw samples have been collected and prepared, including the straw of rice, wheat, canola and corn. Near-infrared diffuse reflectance spectroscopy combined with PLS chemometric algorithms has been used to compare the calibration effect with different spectral pretreatment methods in 7400-5550 cm-1 wavelength range, and the optimal calibration analysis models for N, C, H, S and O element of straw biomass have been established, then the independent samples of validation set were used to validate the model. The validation results show that the established quantitative analysis model for N element can be used in practical detecting; the established quantitative analysis model for O element can be used in practical estimation; the quantitative analysis model of C element by using near-infrared technology is feasible, but the model needs to be further optimized; H and S element can not be quantitatively analyzed by using NIRS technology.