About 1.25 million households grow Robusta in 270,000 hectares, earning at least US $ 3.2 million annually. This study aimed at establishing Ugandan leaf DNA and biochemical fingerprint variability that influence quality in C. canephora green bean. Leaf DNA of 135 C. canephora germplasm collections was evaluated with SSR markers. More 45 4 bean samples from 21 districts and research stations were assessed using Near Infra Red Spectroscopy (NIRS) at the National Crops Resources Research Institute at Namulonge, Uganda. Caffeine content of 16 Robusta accessions was estimated using HPLC and NIRS to verify the precision of the two methods. Transformation of the spectral data into numerical data using predictive models and DNA screening was done at the Centre for International Agricultural Research Development, France. Correlation coefficients quantified the strength of paired biochemical compound relationship at 5% significance level. PCA of biochemical compounds with tree age and altitude was compared with multivariate groups from the factorial step discriminant analysis. The results revealed three major genetic diversity groups of heritable traits and four multivariate groups that reflected a combined influence of inherent traits and environment. Caffeine content from HPLC and NIRS technique which is fast and cheaper was insignificantly different. Ugandan collections had more fat (10.44 to 15.94% of dry matter), wide sucrose range (2.48-7.34% dm) and chlorogenic acid (10.88 to 15.64 % of dry matter) than those reported in previous studies, reflecting high diverse flavours and aroma. The more CGA content than caffeine alkaloid (1.41-3.29% dm) meant not all bean CGA was converted to caffeine chlorogenate as previously reported. The significantly negative correlation between caffeine, chlorogenic acid with trigonelline, sucrose and fat contents implied coffee brew with less caffeine was less bitter and rich in flavour and aroma. Enormous Ugandan genetic and biochemical co