AGRIS

Data provider:

Icon data provider

The National Agricultural Library is one of four national libraries of the United States, with locations in Beltsville, Maryland and Washington, D.C. It houses one of the world's largest and most accessible agricultural information collections and serves as the nexus for a national network of state land-grant and U.S. Department of Agriculture field libraries. In fiscal year 2011 (Oct 2010 through Sept 2011) NAL delivered more than 100 million direct customer service transactions.

فعّال (مزود البيانات قام بتقديم البيانات الوصفية السنة الماضية)
Journal Article

مقال مجلة

Study on discrimination of white tea and albino tea based on near‐infrared spectroscopy and chemometrics  [2014]

Chen, Yi; Deng, Jing; Wang, Yuanxing; Liu, Boping; et al.

استعراض النص الكامل

BACKGROUND: White tea and albino tea have their own nutritional characteristics, but from the appearance they are quite similar to each other. It is not easy to distinguish them with existing analytical tools or by visual inspection. The current study proposed a rapid method to discriminate them based on near‐infrared (NIR) spectroscopy associated with supervised pattern recognition methods. RESULTS: For this purpose, discriminant partial least‐squares (DPLS) and discriminant analysis (DA) were employed to build classification models on the basis of a reduced subset of wavenumbers and different pretreatment methods. A completely independent validation set was also used to test the model performance. The results of the DA model showed that with the SNV Karl Norris derivative spectral pre‐treatment samples from the two different origins could be 100% correctly discriminated. Similarly, for the DPLS model, the best classification results were obtained with the multiplicative scattering correction (MSC) + first derivative spectral pre‐treatments; the accuracy of identification was 98.48% for the calibration set and 100% for the validation set. CONCLUSION: The overall results demonstrated that NIR spectroscopy with pattern recognition could be successfully applied to discriminate white tea and albino tea quickly and non‐destructively without the need for various analytical determinations. © 2013 Society of Chemical Industry
المجلة
Journal of the science of food and agriculture
الرقم التسلسلي المعياري الدولي (ردمد) : 0022-5142

معلومات ببليوغرافية

اللغة:
English
النوع:
Journal Article
في أجريس منذ:
2014
المجلد:
94
الإصدار:
5
صفحة البداية:
1026
صفحة النهاية:
1033
الناشر:
John Wiley & Sons, Ltd
جميع العناوين:
"Study on discrimination of white tea and albino tea based on near‐infrared spectroscopy and chemometrics"@eng
Loading...

معلومات ببليوغرافية

اللغة:
English
النوع:
Journal Article
في أجريس منذ:
2014
المجلد:
94
الإصدار:
5
صفحة البداية:
1026
صفحة النهاية:
1033
الناشر:
John Wiley & Sons, Ltd
جميع العناوين:
"Study on discrimination of white tea and albino tea based on near‐infrared spectroscopy and chemometrics"@eng