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Analytical Letters Volume 50, 2017 - Issue 10
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BIOANALYTICAL

Quantification of Antioxidant Properties in Popular Leaf and Bottled Tea by High-performance Liquid Chromatography (HPLC), Spectrophotometry, and Voltammetry

Nathan HockerSchool of Medicine, Southern Illinois University, Springfield, IL, USA
,
Chaoqiuyu WangDepartment of Chemistry, Illinois Wesleyan University, Bloomington, IL, USA
,
Jennifer ProchotskyDepartment of Chemistry, Illinois Wesleyan University, Bloomington, IL, USA
,
Atul EppurathDepartment of Chemistry, Illinois Wesleyan University, Bloomington, IL, USA
,
Lydia RuddSchool of Nursing, St Johns College, Springfield, IL, USA
&
Manori PereraDepartment of Chemistry, Illinois Wesleyan University, Bloomington, IL, USACorrespondence[email protected]
Pages 1640-1656 | Received 26 Aug 2016, Accepted 24 Sep 2016, Published online: 31 Jul 2017

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Chong Woon Cho, Rustamov Rustam, Dan Gao, Hyung Min Kim & Jong Seong Kang. (2023) Characterization of the Bioactive Components in Aronia melanocarpa (Black Chokeberry) Fruit Extracts and Purified Fractions by Spectrophotometry and High-Performance Liquid Chromatography (HPLC). Analytical Letters 56:14, pages 2291-2308.
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Xiaohan Yuan, Chaoqiuyu Wang & Manori Perera. (2023) Quantitative Determination of the Radical Scavenging Activity of Antioxidants in Black Tea Combined with Common Spices Using Ultraviolet-Visible Spectroscopy. Analytical Letters 56:4, pages 682-691.
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Slađana Popović, Ana Pantelić, Željka Milovanović, Jelena Milinkov & Milka Vidović. (2017) Analysis of Tea for Metals by Flame and Graphite Furnace Atomic Absorption Spectrometry with Multivariate Analysis. Analytical Letters 50:16, pages 2619-2633.
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Articles from other publishers (6)

Md. Rashed Hasan, Mohammad Majedul Haque, Md. Amirul Hoque, Shahin Sultana, Mohammad Mahbubur Rahman, Md. Aftab Ali Shaikh & Md. Khabir Uddin Sarker. (2024) Antioxidant activity study and GC-MS profiling of Camellia sinensis Linn. Heliyon 10:1, pages e23514.
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Na Luo, Yunlong Li, Baohua Yang, Biyun Liu & Qianying Dai. (2022) Prediction Model for Tea Polyphenol Content with Deep Features Extracted Using 1D and 2D Convolutional Neural Network. Agriculture 12:9, pages 1299.
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Jinhua Shao, Chao Wang, Yiling Shen, Jinlei Shi & Dongqing Ding. (2022) Electrochemical Sensors and Biosensors for the Analysis of Tea Components: A Bibliometric Review. Frontiers in Chemistry 9.
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Baohua Yang, Lin Qi, Mengxuan Wang, Saddam Hussain, Huabin Wang, Bing Wang & Jingming Ning. (2019) Cross-Category Tea Polyphenols Evaluation Model Based on Feature Fusion of Electronic Nose and Hyperspectral Imagery. Sensors 20:1, pages 50.
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U.G. Spizzirri, G. Carullo, L. De Cicco, A. Crispini, F. Scarpelli, D. Restuccia & F. Aiello. (2019) Synthesis and characterization of a (+)-catechin and L-(+)-ascorbic acid cocrystal as a new functional ingredient for tea drinks. Heliyon 5:8, pages e02291.
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Baohua Yang, Yue Zhu, Mengxuan Wang & Jingming Ning. (2019) A Model for Yellow Tea Polyphenols Content Estimation Based on Multi-Feature Fusion. IEEE Access 7, pages 180054-180063.
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