Genome‐enabled prediction models for black tea ( Camellia sinensis ) quality and drought tolerance traits

2020 ◽  
Vol 139 (5) ◽  
pp. 1003-1015
Author(s):  
Robert K. Koech ◽  
Pelly M. Malebe ◽  
Christopher Nyarukowa ◽  
Richard Mose ◽  
Samson M. Kamunya ◽  
...  
Keyword(s):  
Drought Tolerance ◽  
Camellia Sinensis ◽  
Prediction Models ◽  
Black Tea

Identification of novel QTL for black tea quality traits and drought tolerance in tea plants (Camellia sinensis)

2018 ◽  
Vol 14 (1) ◽  
Author(s):  
Robert K. Koech ◽  
Pelly M. Malebe ◽  
Christopher Nyarukowa ◽  
Richard Mose ◽  
Samson M. Kamunya ◽  
...  
Keyword(s):  
Drought Tolerance ◽  
Camellia Sinensis ◽  
Black Tea ◽  
Quality Traits ◽  
Tea Quality ◽  
Tea Plants

scholarly journals Genome-enabled prediction models for black tea (Camellia sisnesnsis) quality and drought tolerance traits

2019 ◽  
Author(s):  
Robert. K. Koech ◽  
Pelly M. Malebe ◽  
Christopher Nyarukowa ◽  
Richard Mose ◽  
Samson M. Kamunya ◽  
...  
Keyword(s):  
Drought Tolerance ◽  
Genomic Selection ◽  
Prediction Models ◽  
Black Tea ◽  
Future Application ◽  
Phenotypic Traits ◽  
List Type ◽  
Putative Qtls ◽  
Validation Population ◽  
Prediction Approach

SummaryGenomic selection in tea (Camellia sinensis) breeding has the potential to accelerate efficiency of choosing parents with desirable traits at the seedling stage.The study evaluated different genome-enabled prediction models for black tea quality and drought tolerance traits in discovery and validation populations. The discovery population comprised of two segregating tea populations (TRFK St. 504 and TRFK St. 524) with 255 F1 progenies and 56 individual tea cultivars in validation population genotyped using 1 421 DArTseq markers.Two-fold cross-validation was used for training the prediction models in discovery population, and the best prediction models were consequently, fitted to the validation population.Of all the four based prediction approaches, putative QTLs (Quantitative Trait Loci) + annotated proteins + KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathway-based prediction approach, showed robustness and usefulness in prediction of phenotypes.Extreme Learning Machine model had better prediction ability for catechin, astringency, brightness, briskness, and colour based on putative QTLs + annotated proteins + KEGG pathway approach.The percent variables of importance of putatively annotated proteins and KEGG pathways were associated with the phenotypic traits. The findings has for the first time opened up a new avenue for future application of genomic selection in tea breeding.

scholarly journals UPLC-MS based metabolomics analysis reveals metabolite compositional differences between Kenyan Commercial and NonCommercial black tea (Camellia sinensis L.) cultivars.

2021 ◽  
Author(s):  
Christopher Nyarukowa
Keyword(s):  
Drought Tolerance ◽  
Camellia Sinensis ◽  
Antioxidant Properties ◽  
Epigallocatechin Gallate ◽  
Black Tea ◽  
Global Supply Chains ◽  
Tea Quality ◽  
Production And Consumption ◽  
Health Promoting ◽  
Tea Production

Camellia sinensis (L.) O. Kuntze (tea) is one of the most widely consumed beverages across the world, serving as an essential commodity crop for several developing countries. A bulk of tea’s health-promoting properties are attributed to the antioxidant properties of EGCg, its predominant polyphenol. As a result of these health benefits, tea production and consumption has expanded and promoted the development of tea industries globally. Tea cultivation is dependent on a good distribution of rainfall, and the current changes in climate pose a significant threat to its global supply chains. Through the efforts of the International Centre for Tropical Agriculture (CIAT), predictions of future climate changes in the tea growing regions of Kenya between now and 2050 have been generated. A study was conducted to develop models to identify key tea growing regions that will remain ideal for tea farming and also investigate the metabolomic differences between 243 drought susceptible NonCommercial (NComm) and 60 Commercial (Comm) cultivars. Non-targeted, high-resolution UPLC-MS was used to attain a new profound understanding of the metabolomic multiplicity between the Comm and NComm groups and to elucidate their association with tea liquor quality and drought tolerance. Several metabolites, namely argininosuccinate, caffeic acid, caffeine, catechin, citric acid, epicatechin, epigallocatechin gallate, gallic acid, gluconic acid, glucose, maltose, quercetin and theanine were found to clearly differentiate between the Comm and NComm cultivars. These detected metabolites were linked to improved tea quality and drought tolerance in the Comm cultivars.

Effect of Black Tea (Camellia sinensis) Extract on Thyroid Physiology During Pregnancy in Experimental Animal Model

2021 ◽  
Author(s):  
Avijit Dey ◽  
Ritwika Chatterjee ◽  
Mousumi Das ◽  
Monalisa Sinha ◽  
Rimita Saha ◽  
...  
Keyword(s):  
Animal Model ◽  
Experimental Animal ◽  
Camellia Sinensis ◽  
Black Tea ◽  
Experimental Animal Model

Effect of black tea brew of Camellia sinensis on sexual competence of male rats

2008 ◽  
Vol 118 (3) ◽  
pp. 373-377 ◽  
Author(s):  
W.D. Ratnasooriya ◽  
T.S.P. Fernando
Keyword(s):  
Camellia Sinensis ◽  
Black Tea ◽  
Male Rats

Studies on black tea (Camellia sinensis) extract as a potential antioxidant and a probable radioprotector

2013 ◽  
Vol 52 (2) ◽  
pp. 269-278 ◽  
Author(s):  
Sandip Pal ◽  
Chabita Saha ◽  
Subrata Kumar Dey
Keyword(s):  
Camellia Sinensis ◽  
Black Tea

A mechanism of the thearubigin fraction of black tea (camellia sinensis) extract protecting against the effect of tetanus toxin.

2002 ◽  
Vol 27 (5) ◽  
pp. 441-447 ◽  
Author(s):  
Eiki SATOH ◽  
Toshiaki ISHII ◽  
Yoshio SHIMIZU ◽  
Shin-ichi SAWAMURA ◽  
Masakazu NISHIMURA
Keyword(s):  
Camellia Sinensis ◽  
Tetanus Toxin ◽  
Black Tea
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