CAJ | 학술논문

建立了一种傅里叶变换红外光谱（Fourier transform infrared spectroscopy ，FTIR）快速无损鉴别当归及其不同炮制品多糖的新方法。生当归（unprocessed Angelica sinensis ，UAS）经炮制为酒当归（angelica sinensis parched with wine ，WAS ）、土当归（angelica sinensis parched with soil ，SAS ）、油当归（angelica sinensis parched with oil ，OAS）和当归炭（charred angelica sinensis ，CAS），为了有效、合理地使用当归及其不同炮制品多糖，对其进行鉴别分析很有必要。首先获取当归及其不同炮制品多糖的 FT IR ，运用离散小波变换方法（discrete Wavelet transform ，DWT ）对其进行分解，然后选取2，3，4尺度下的高频信息作为特征信息，分别提取其小波熵作为特征值，采用BP神经网络进行训练，再用训练所得模型对当归及其不同炮制品多糖的FT IR小波提取出的特征值进行智能判别。通过对30个样本进行预测，判别率高达93.3％，说明基于FT IR离散小波特征提取及BP神经网络分类法识别当归及其不同炮制品多糖，具有较优的可行性。
건립료일충부리협변환홍외광보（Fourier transform infrared spectroscopy ，FTIR）쾌속무손감별당귀급기불동포제품다당적신방법。생당귀（unprocessed Angelica sinensis ，UAS）경포제위주당귀（angelica sinensis parched with wine ，WAS ）、토당귀（angelica sinensis parched with soil ，SAS ）、유당귀（angelica sinensis parched with oil ，OAS）화당귀탄（charred angelica sinensis ，CAS），위료유효、합리지사용당귀급기불동포제품다당，대기진행감별분석흔유필요。수선획취당귀급기불동포제품다당적 FT IR ，운용리산소파변환방법（discrete Wavelet transform ，DWT ）대기진행분해，연후선취2，3，4척도하적고빈신식작위특정신식，분별제취기소파적작위특정치，채용BP신경망락진행훈련，재용훈련소득모형대당귀급기불동포제품다당적FT IR소파제취출적특정치진행지능판별。통과대30개양본진행예측，판별솔고체93.3％，설명기우FT IR리산소파특정제취급BP신경망락분류법식별당귀급기불동포제품다당，구유교우적가행성。
A new rapid and nondestructive method for identifying polysaccharides from A ngelica sinensis and its different pro-cessed products was developed ,and this method was based on Fourier transform infrared spectroscopy (FTIR) .In the clinic of traditional Chinese medicine ,unprocessed Angelica sinensis(UAS) is of ten used after processed ,the common processed prod-uctsare Angelicasinensis parchedwithwine(WAS),Angelicasinensis parchedwithsoil(SAS),Angelicasinensis parchedwith oil(OAS) and Charred Angelica sinensis(CAS) .In order to use polysaccharides from Angelica sinensis and its processed prod-ucts effectively and reasonably in clinic ,it is very necessary to identify them .FTIR of polysaccharides from A ngelica sinensis and its different processed products was determined ,and then it was decomposed by discrete wavelet transform (DWT ) .The high frequency information in scale 2 ,3 and 4 was selected as feature information ,from which the each wavelet entropy was ex-tracted as characteristic value .BP neural network was trained with these characteristic values .The trained BP neural network was used to identify polysaccharides from Angelicasinensis and its different processed products .According to 30 prediction sam-ples ,the correct rate for recognition was 93 .3% ,which indicates that :it has better feasibility to identify polysaccharides from Angelicasinensis and its different processed products by this method ,which is based on FTIR ,discrete wavelet transform and BP neural network .