茶叶掺糖含量检测算法中光谱数据有效性及冗余度研究

基于近红外光谱(NIRS)技术和遗传算法-反向传播(GA-BP)神经网络建立模型，分析茶叶掺蔗糖样品的1～2.5 μm原始光谱数据的有效性及冗余度。固定样本数据，对模型的参数优化选择后建立茶叶蔗糖含量定量检测模型。将1～2.5 μm原始数据分1～1.7，1～1.3，1.3～1.7，1.7～2.5和2～2.2 μm。利用建立的模型对同一分辨率下的不同波段进行模型训练。预测结果表明，1～1.7和1～2.5 μm波段存在数据冗余。仅使用1.3～1.7或1.7～2.5 μm波段即可有效建立模型。预测模型对同一波段下的不同分辨率进行研究，从2 nm到20 nm改变分辨率，当波段范围为1～2.5 μm时，模型的R均介于0.9和0.95之间，且RMSEP也在1.7和2.1之间。当波段范围为1～1.7 μm时，模型的R均在0.9和0.93之间，且RMSEP也在1.95和2.25之间。结果表明，1～2.5 μm原始数据中确实存在波长范围和光谱分辨率的冗余。通过光谱特征分析和算法建模，可以显著提高光谱数据获取的有效性；对于茶叶中蔗糖含量的检测，可以采用更窄的波长范围和更低的光谱分辨率。

Validity and Redundancy of Spectral Data in the Detection Algorithm of Sucrose-Doped Content in Tea

Near-infrared spectroscopy (NIRS) technology integrated with Genetic Algorithm-Back Propagation (GA-BP) neural network was used to spectral sucrose-doped content in 162 tea samples in the NIR wavelength range of 1~2.5 μm. The parameters of the GA and BP neural network were optimized by the sample set to analyze the validity and redundancy of spectral bands. The raw data in the range of 1~2.5 μm was divided into 1~1.7, 1~1.3, 1.3~1.7, 1.7~2.5 and 2~2.2 μm sets. The established quantitative detection model was used to conduct model training on different wavelength bands at the same resolution. The prediction results show that, for the target content, data redundancy appears in both 1~1.7 and 1~2.5 μm bands. The model could be effectively extracted using only 1.3~1.7 or 1.7~2.5 μm band. The prediction model was also conducted using different spectral resolutions from 2 to 20 nm in the same band. In the wavelength range of 1~2.5 μm, the R was between 0.9 and 0.95 when the RMSEP ranged from 1.7 to 2.1. While in the wavelength range of 1~1.7 μm, the R was in the range of 0.9 to 0.93 when the RMSEP was between 1.95 and 2.25. The results indicate that, for the target content, redundancy exists in the 1~2.5 and 1~1.7 μm bands on both wavelength range and spectral resolution. Through the analysis of spectral features and modeling of the algorithm, the effectiveness of spectral data acquirement could be improved dramatically; for the detection of sucrose-doped content in tea, a much narrower wavelength range and lower spectral resolution could be adopted.