2022
DOI: 10.3390/foods12010123
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Variation of Major Chemical Composition in Seed-Propagated Population of Wild Cocoa Tea Plant Camellia ptilophylla Chang

Abstract: Excessive intake of high-caffeine tea will induce health-related risk. Therefore, breeding and cultivating tea cultivars with less caffeine is a feasible way to control daily caffeine intake. Cocoa tea (Camellia ptilophylla Chang) is a wild tea plant which grows leaves with little or no caffeine. However, the vegetative propagation of cocoa tea plants is difficult due to challenges with rooting. Whether natural seeds collected from wild cocoa tea plants can be used to produce less-caffeinated tea remains unkno… Show more

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Cited by 2 publications
(2 citation statements)
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“…In addition, we found that biological activities of identified key metabolites that were enriched by NSND processing have consistently been proved in previous studies, 28,52,55,57,65,67,73‐78 supporting our findings (Table 3). Among them, gallocatechin and furoaloesone showed the largest binding energy with most of the targeted proteins.…”
Section: Resultssupporting
confidence: 91%
“…In addition, we found that biological activities of identified key metabolites that were enriched by NSND processing have consistently been proved in previous studies, 28,52,55,57,65,67,73‐78 supporting our findings (Table 3). Among them, gallocatechin and furoaloesone showed the largest binding energy with most of the targeted proteins.…”
Section: Resultssupporting
confidence: 91%
“…In this section, the experimental results obtained in this study are discussed and compared with the results of other studies. Some of the excellent work on tea includes the following publications: P Olha et al [38] studied the positive antioxidant and anti-diabetic effects of tea polyphenols on tea drinkers, P Chen et al [39] conducted a study to analyse the cultivation suitability of tea trees, J Ye et al [40] studied the effects of applying different amounts of organic fertilisers on tea yield and quality, and XQ Zheng et al [41] studied the effects of tea plant chemical composition. Unlike previous work, this study used a link prediction algorithm to link multiple types of tea and tea-suitable people, combining some of the characteristics of tea and using an improved link prediction algorithm for the predictive analysis of tea-suitable people.…”
Section: Discussionmentioning
confidence: 99%