Apart from water, tea is the world’s most widely consumed beverage. Tea is produced in more than 50 countries with an annual production of approximately 4.7 million tons. The market segment for specialty tea has been expanding rapidly owing to increased demand, resulting in higher revenues and profits for tea growers and the industry. Accurate varietal identification is critically important to ensure traceability and authentication of premium tea products, which in turn contribute to on-farm conservation of tea genetic diversity. Using a set of single nucleotide polymorphism (SNP) markers developed from the expressed sequence tag (EST) database of Camilla senensis, we genotyped deoxyribonucleic acid (DNA) samples extracted from a diverse group of tea varieties, including both fresh and processed commercial loose-leaf teas. The validation led to the designation of 60 SNPs that unambiguously identified all 40 tested tea varieties with high statistical rigor (p<0.0001). Varietal authenticity and genetic relationships among the analyzed cultivars were further characterized by ordination and Bayesian clustering analysis. These SNP markers, in combination with a high-throughput genotyping protocol, effectively established and verified specific DNA fingerprints for all tested tea varieties. This method provides a powerful tool for variety authentication and quality control for the tea industry. It is also highly useful for the management of tea genetic resources and breeding, where accurate and efficient genotype identification is essential.

Horticulture Research is a new Open Access, fully peer-reviewed journal which will publish the best and most interesting research focusing on all major horticultural crops from around the world.

Accurate genotype identification is imperative for effective use of Coffea canephora L. germplasm to breed new varieties with tolerance or resistance to biotic and abiotic stresses (including moisture stress and pest and disease stresses such as coffee berry borer and rust) and for high yield and improved cup quality. The present study validated 192 published single nucleotide polymorphism (SNP) markers and selected a panel of 120 loci to examine parentage and labeling errors, genetic diversity, and population structure in 400 C. canephora accessions assembled from different coffee-producing countries and planted in a field gene bank in Ghana. Of the 400 genotypes analyzed, both synonymous (trees with same SNP profiles but different names, 12.8%) and homonymous (trees with same name but different SNP profiles, 5.8%) mislabeling were identified. Parentage analysis showed that 33.3% of the progenies derived from controlled crossing and 0% of the progenies derived from an open pollinated biclonal seed garden had parentage (both parents) corresponding to breeder records. The results suggest mislabeling of the mother trees used in seed gardens and pollen contamination from unwanted paternal parents. After removing the duplicated accessions, Bayesian clustering analysis partitioned the 270 unique genotypes into two main populations. Analysis of molecular variance (AMOVA) showed that the between-population variation accounts for 41% of the total molecular variation and the genetic divergence was highly significant (Fst = 0.256; P < 0.001). Taken together, our results demonstrate the effectiveness of using the selected SNP panel in gene bank management, varietal identification, seed garden management, nursery verification, and coffee bean authentication for C. canephora breeding programs.