摘要
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,陈皮内侧光谱数据可获得最优的鉴别结果,鉴别准确率为91.67%;通过最大最小归一化预处理后,陈皮外侧光谱数据可获得最优鉴别结果,鉴别准确率为70.83%;在2种预处理组合的鉴别结果中,有9个组合方式结合陈皮外侧光谱数据实现了对陈皮产地的100%鉴别分析,对于陈皮内侧光谱数据的最佳预处理组合为去趋势校正+最大最小归一化,鉴别准确率为95.83%;而3个预处理组合的鉴别准确率较2个预处理的结果低,表明采用预处理种类过多时可能会扣除有用信息。结果表明:近红外光谱技术结合光谱预处理可以实现不同产地陈皮的无损鉴别分析,其中陈皮外侧光谱数据结合优化光谱预处理方法可实现陈皮产地的100%鉴别分析。
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.
作者
余梅
李尚科
杨菲
郑郁
李跑
蒋立文
刘霞
YU Mei;LI Shang-ke;YANG Fei;ZHENG Yu;LI Pao;JIANG Li-wen;LIU Xia(College of Food Science and Technology,Hunan Provincial Key Laboratory of Food Science and Biotechnology,Hunan Agricultural University,Changsha 410128,China;School of Medicine,Hunan Normal University,Changsha410013,China;Hunan Agricultural Product Processing Institute,Hunan Academy of Agricultural Sciences,Changsha 410125,China)
出处
《分析测试学报》
CAS
CSCD
北大核心
2021年第1期65-71,共7页
Journal of Instrumental Analysis
基金
国家自然科学基金(31601551,31671931)
湖南省自然科学基金(2019JJ50240)
湖南省教育厅科学研究项目优秀青年项目(18B118)
中国博士后科学基金面上项目(2019M650187)。
关键词
陈皮
近红外光谱技术
优化光谱预处理
主成分分析
citri reticulatae pericarpium
near infrared spectroscopy technology
optimized spectral pretreatments
principal component analysis
