Simultaneous Recognition of Species, Quality Grades, and Multivariate Calibration of Antioxidant Activities for 12 Famous Green Teas Using Mid- and Near-Infrared Spectroscopy Coupled with Chemometrics
المؤلفون المشاركون
Xu, Lu
She, Yuan-Bin
Fan, Yao
Yang, Tianming
Shi, Qiong
Fu, Hai-Yan
Xie, Shunping
Hu, Ou
Guo, Xiaoming
Lan, Wei
المصدر
Journal of Analytical Methods in Chemistry
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-01-02
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
In this paper, mid- and near-infrared spectroscopy fingerprints were combined to simultaneously discriminate 12 famous green teas and quantitatively characterize their antioxidant activities using chemometrics.
A supervised pattern recognition method based on partial least square discriminant analysis (PLSDA) was adopted to classify the 12 famous green teas with different species and quality grades, and then optimized sample-weighted least-squares support vector machine (OSWLS-SVM) based on particle swarm optimization was employed to investigate the quantitative relationship between their antioxidant activities and the spectral fingerprints.
As a result, 12 famous green teas can be discriminated with a recognition rate of 100% by MIR or NIR data.
However, compared with individual instrumental data, data fusion was more adequate for modeling the antioxidant activities of samples with RMSEP of 0.0065.
Finally, the performance of the proposed method was evaluated and validated by some statistical parameters and the elliptical joint confidence region (EJCR) test.
The results indicate that fusion of mid- and near-infrared spectroscopy suggests a new avenue to discriminate the species and grades of green teas.
Moreover, the proposed method also implies other promising applications with more accurate multivariate calibration of antioxidant activities.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Fu, Hai-Yan& Hu, Ou& Xu, Lu& Fan, Yao& Shi, Qiong& Guo, Xiaoming…[et al.]. 2019. Simultaneous Recognition of Species, Quality Grades, and Multivariate Calibration of Antioxidant Activities for 12 Famous Green Teas Using Mid- and Near-Infrared Spectroscopy Coupled with Chemometrics. Journal of Analytical Methods in Chemistry،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1169147
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Fu, Hai-Yan…[et al.]. Simultaneous Recognition of Species, Quality Grades, and Multivariate Calibration of Antioxidant Activities for 12 Famous Green Teas Using Mid- and Near-Infrared Spectroscopy Coupled with Chemometrics. Journal of Analytical Methods in Chemistry No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1169147
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Fu, Hai-Yan& Hu, Ou& Xu, Lu& Fan, Yao& Shi, Qiong& Guo, Xiaoming…[et al.]. Simultaneous Recognition of Species, Quality Grades, and Multivariate Calibration of Antioxidant Activities for 12 Famous Green Teas Using Mid- and Near-Infrared Spectroscopy Coupled with Chemometrics. Journal of Analytical Methods in Chemistry. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1169147
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1169147
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر