基于近红外光谱技术与优化光谱预处理的陈皮产地鉴别研究

采集不同产地陈皮内侧和外侧的近红外光谱,采用不同光谱预处理方法进行预处理,筛选得到最佳光谱预处理方法,结合主成分分析法建立了陈皮产地的鉴别模型.实验发现,陈皮原始光谱中存在明显的基线漂移与背景干扰.使用单一光谱预处理可在一定程度上消除干扰的影响.经标准正态变量变换、多元散射校正、一阶导数、二阶导数与连续小波变换预处理后...

Identification on Different Origins of Citri Reticulatae Pericarpium Using Near Infrared Spectroscopy Combined with Optimized Spectral Pretreatments

The near infrared spectra for the outer skin and inner capsule of citri reticulatae pericarpium from different habitats were collected.Different spectral pretreatment methods were used and the best method was selected. The identification model of citri reticulatae pericarpium origin was established by principal component analysis.It was found that there were obvious baseline drift and background interference in the raw spectra.The interferences could be eliminated to a certain extent by using single spectral pretreatment method.After using pretreatments of standard normal variate transform,multivariate scattering correction,first derivative,second derivative and continuous wavelet transform,the best identification results for the inner capsule data could be obtained,with an accuracy of 91.67%,while the optimal identification results for the outer skin data could be obtained by the maximum and minimum normalization pretreatment with an accuracy of 70.83%.A 100% of identification accuracy could be obtained by 9 combinations of two pretreatment methods for the outer skin data,and the optimal pretreatment combination for the inner capsule data was de-trending+maximum-minimum normalization,with an accuracy of 95.83%.However,the accuracies for three pretreatment combinations were lower than those for two pretreatment combinations,which indicated that useful information might be deducted if too many kinds of pretreatments were used.Results showed the nondestructive identification on citri reticulatae pericarpium of different origins could be achieved based on the combination of near infrared spectroscopy and spectral pretreatments,in which a 100% accuracy could be realized by using the outer skin data to optimizing combination of spectral pretreatment.