[Discrimination of Armeniacae Semen Amarum from different processed products and various rancidness degrees by electronic nose and support vector machine].
Zhongguo Zhong Yao Za Zhi
; 45(10): 2389-2394, 2020 May.
Article
in Zh
| MEDLINE
| ID: mdl-32495597
ABSTRACT
This study was aimed to develop a simple, rapid and reliable method for identifying Armeniacae Semen Amarum from different processed products and various rancidness degrees. The objective odor information of Armeniacae Semen Amarum was obtained by electronic nose. 105 batches of Armeniacae Semen Amarum samples were studied, including three processed products of Armeniacae Semen Amarum, fried Armeniacae Semen Amarum and peeled Armeniacae Semen Amarum, as well as the samples with various rancidness degrees without rancidness, slight rancidness, and rancidness. The discriminant models of different processed products and rancidness degrees of Armeniacae Semen Amarum were established by Support Vector Machine(SVM), respectively, and the models were verified based on back estimation of blind samples. The results showed that there were differences in the characteristic response radar patterns of the sensor array of different processed products and the samples with different rancidness degrees. The initial identification rate was 95.90% and 92.45%, whilst validation recognition rate was 95.38% and 91.08% in SVM identification models. In conclusion, differentiation in odor of different processed and rancidness degree Armeniacae Semen Amarum was performed by the electronic nose technology, and different processed and rancidness degrees Armeniacae Semen Amarum were successfully discriminated by combining with SVM. This research provides ideas and methods for objective identification of odor of traditional Chinese medicine, conducive to the inheritance and development of traditional experience in odor identification.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Drugs, Chinese Herbal
/
Electronic Nose
Type of study:
Clinical_trials
/
Diagnostic_studies
/
Prognostic_studies
Language:
Zh
Journal:
Zhongguo Zhong Yao Za Zhi
Journal subject:
FARMACOLOGIA
/
TERAPIAS COMPLEMENTARES
Year:
2020
Document type:
Article
Affiliation country:
China