Biology subjects

Koech, R.

Publications and source records attributed to Koech, R..

3 recordsLinked to original sources

bioRxiv2025

BIOCHEMICAL COMPOSITION OF SPECIALTY TEA EXTRACTS FROM MULTISTAGE EXTRACTIONS USING SOLVENTS TREATMENTS

Diversification and value addition in tea has received considerable attention in recent past. This has been occasioned by increased tea volumes in the world market, especially the aerated product that has led to over flooding. Additionally, health benefits associated with diversified products such as green tea and extracts has elicited a lot of interests in both the industry and external players in finding out alternative ways of tea consumption. The aim of this study was to determine biochemical composition of the various tea extract products generated at different points of a multistage extraction process. The extraction process consisted of hot distilled water, methylene chloride and ethyl acetate steps. The products of purple, yellow, green, black orthodox teas, matcha and the semi aerated oolong were used as raw materials for the extracts. Total polyphenols content, individual catechins and caffeine content were assayed using UV-spectrophotometer and High Performance Liquid Chromatography-Photo diode array HPLC-PDA. Analysis of variance (ANOVA) was used for statistical purposes to detect significant differences between the extraction methods with the least significant difference (LSD) used to separate the means in the assayed tea samples. Results generated indicated that total polyphenols, individual catechins and caffeine content were significantly different (p[≤]0.05) in the assayed tea samples. Water extracts showed high total yield (82.2%), while methylene chloride recorded the least (2.63%). Ethyl acetate tea extracts showed high phenolic content that ranged from 11. 4% to78.1%. Ethyl acetate extract was rich in total catechins content (46.6% to 75.9%). Water extracts had significantly (p[≤]0.05) high amounts of total catechins (12.3% to 27.6%) compared to residual extracts (5.4% to 8.9%) contrary to methylene chloride extracts which had low total catechin contents (1.2% to 4.5%). Caffeine was predominant in methylene chloride tea extracts and ranged from 29.97% to 58.99% pointing to high solvent affinity. Based on this results, ethyl acetate proved to be the ideal solvent for obtaining extract rich in polyphenols, and methylene chloride for isolation of natural caffeine. For high yield of all polyphenols, water was found to be the solvent of choice of tea extracts without regarding the specific class of compound to be isolated. This study confirmed that specialty tea extracts are a promising source of bioactive compounds, suggesting they could be very attractive for use as dietary supplements, cosmetic ingredients and in food industries.

biochemistry↗

bioRxiv2019

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

SummaryO_LIGenomic selection in tea (Camellia sinensis) breeding has the potential to accelerate efficiency of choosing parents with desirable traits at the seedling stage. C_LIO_LIThe 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. C_LIO_LITwo-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. C_LIO_LIOf 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. C_LIO_LIExtreme Learning Machine model had better prediction ability for catechin, astringency, brightness, briskness, and colour based on putative QTLs + annotated proteins + KEGG pathway approach. C_LIO_LIThe 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. C_LI

genomics↗

bioRxiv2018

Combined linkage and association mapping of putative QTLs controlling black tea quality and drought tolerance traits

The advancements in genotyping have opened new approaches for identification and precise mapping of Quantitative Trait Loci (QTLs) in plants, particularly by combining linkage and association mapping (AM) analysis. In this study, a combination of linkage and the AM approach was used to identify and authenticate putative QTLs associated with black tea quality traits and percent relative water content (%RWC). The population structure analysis clustered two parents and their respective 261 F1 progenies from the two reciprocal crosses into two clusters with 141 tea accessions in cluster one and 122 tea accessions in cluster two. The two clusters were of mixed origin with tea accessions in population TRFK St. 504 clustering together with tea accessions in population TRFK St. 524. A total of 71 putative QTLs linked to black tea quality traits and %RWC were detected in interval mapping (IM) method and were used as cofactors in multiple QTL model (MQM) mapping where 46 putative QTLs were detected. The phenotypic variance for each QTL ranged from 2.8-23.3% in IM and 4.1-23% in MQM mapping. Using Q-model and Q+K-model in AM, a total of 49 DArTseq markers were associated with 16 phenotypic traits. Significant marker-trait association in AM were similar to those obtained in IM, and MQM mapping except for six more putative QTLs detected in AM which are involved in biosynthesis of secondary metabolites, carbon fixation and abiotic stress. The combined linkage and AM approach appears to have great potential to improve the selection of desirable traits in tea breeding.

genomics↗