Metabolomic markers for agronomic traits and their possible biochemical mechanisms in black tea Camellia sinensis (L.) O. Kuntze

Climate change is causing droughts, which are affecting crop production globally, and disrupting plant metabolism. Due to the unpredictable natural droughts that occur, causing tea farmers significant losses in tea estates, a Short-time Withering Assessment of Probability for Drought Tolerance (SWAPDT) method for distinguishing between drought tolerant (DT) and drought susceptible (DS) Camellia sinensis cultivars was developed based on cultivars from the Tea Research Foundation for Central Africa in Malawi, and validated on 400 samples from the Tea Research Institute in Kenya. From the results, a sample size of 20 tea trees was deemed sufficient to accurately determine the drought susceptibility of a large tea field of approximately 5 - 20 hectares, containing 50 000 - 200 000 tea trees, were the difference between their mean values is approximately 6%. Tea production and subsequently its quality rely on evenly distributed rainfall. Tea consumers concern themselves with the quality of tea, in particular its flavour and aroma. To breed for these phenotypic traits is challenging due to these being qualitative traits inherited from parents, and influenced by environment. Two C. sinensis populations, 60 Commercial cultivars and 250 NonCommercial cultivars (TRFK St. 504 and TRFK St. 524) were employed in a part of this study to identify the Quantitative Trait Loci (QTL) responsible for yield, drought tolerance and quality centred on a genetic map constructed using the DArTseq platform. The map comprised 15 linkage groups analogous to chromosome haploid number of tea plant (2n = 2x = 30) and spanned 1260.1 cM with a mean interval of 1.1 cM between markers. Sixteen phenotypic traits were evaluated in both populations, and three, 11 and 46 putative QTLs were discovered after mapping on the 15 linkage groups, associated with tea quality from Gas Chromatography-Mass Spectrometry (GC-MS), Nuclear Magnetic Resonance (1H-NMR) and Ultra-Performance Liquid Chromatography (UPLC) data respectively. The variance explained by the QTLs varied from 4.6 to 96.3%, with an average of 28%. Using the KEGG database, the putative QTLs linked to yield, drought tolerance and quality were secondary metabolites associated with tea phenolic biomolecules and abiotic stress. Principal Component Analysis was performed on the GC-MS, 1H-NMR and UPLC data, and from these, the UPLC data showed clearer separation and clustering between the Commercial and NonCommercial cultivars. With focus on the UPLC data, it was narrowed down to the five catechins, four theaflavins and caffeine; these were used to develop several logistic regression models. The model based on only the fresh leaf catechins classified over 90% of the 310 genotypes as either Commercial or NonCommercial cultivars. This model may be useful in predicting the suitability for commercialization of promising selections from mature seedling fields, based on the analysis of their dried green leaves. Last, 20 Commercial and 20 NonCommercial cultivars were analysed using UPLC-MS. New metabolites were identified as contributing to drought tolerance, yield and higher quality of the Commercial as compared to the NonCommercial cultivars.Thesis (PhD (Biochemistry))--University of Pretoria, 2021.BiochemistryPhD (Biochemistry)Unrestricte