发酵冬虫夏草菌粉水分腺苷的近红外光谱定量分析及波段选择

研究发现基于800～2 500 nm波段的近红外光谱可对发酵冬虫夏草菌粉中水分和腺苷进行良好的定量分析。选取了4 277.63～4 316.20 cm-1，4 887.06～4 941.07 cm-1，5 056.78～5 172.50 cm-1和5 218.78～5 303.64 cm-1四个特征波段;4 902.49～4 817.64 cm-1和4 740.49～4 107.91 cm-1两个特征波段，分别对水分和腺苷建立了偏最小二乘法(partial least-square，PLS)回归模型。采用全波段建模水分和腺苷的预测相关系数r分别为0.868 3和0.788 2，预测均方根误差RMSEP分别为0.001 999和0.000 134, 剩余预测偏差RPD分别为1.974 4和1.640 7。而采用特征波段建模，其对水分和腺苷的预测相关系数r分别为0.869 1和0.829 0，预测均方根误差分别为0.001 934和0.001 250，剩余预测偏差分别为2.040 7和1.847 6。结果表明，采用对这两项指标特征波长建模后，不仅预测效果有不同程度的提高，还提高了建模速度，为检测仪器的开发提供了依据。

Near-Infrared Spectroscopy Analysis of Adenosine and Water in Fermentation Cordyceps Powder and Wavelength Assignment

Based on near-infrared spectroscopy,four characteristic wavebands 4 277.63~4 3166.20,4 887.06~4 941.07,5 056.78~5 172.50 and 5 218.78~5 303.64 cm-1,and two characteristic wavebands 4 902.49~4 817.64 and 4 740.49~4 107.91 cm-1 were chosen to establish the partial least squares(PLS) regression model of water and adenosine in fermentation cordyceps powder,respectively.The prediction results of water and adenosine contents of the whole spectra PLS model were as follows: correlation coefficients(r) were 0.868 3 and 0.788 2,RMS error predictions(RMSEP) were 0.001 999 and 0.000 134,the remaining prediction deviations(RPD) were 1.974 4 and 1.640 7,respectively.However,using characteristic wavebands modeling can achieve a better performance with r of 0.869 1 and 0.829 0,RMSEP of 0.001 934 and 0.001 250,and RPD of 2.040 7 and 1.847 6 for water and adenosine respectively,and can largely improve calibration speed,providing the theoretical basis for the development of the testing instruments.So choosing the characteristic wavebands in this work to determine the water and adenosine in fermentation cordyceps powder is more effective.