Abstract
This study was conducted to evaluate the prediction of sensory property of smoke from the leaf chemical property and characterize leaf chemical components for the best tobacco taste's leaves in burley tobacco. For analytical and sensory evaluations, sixteen grades were used. The major leaf chemical components to predict the sensory property of smoke were ether extract for tobacco-like, chloride for impact and total nitrogen/nicotine for irritation. Within ${\pm}20\;%$ range of difference, the predictable probabilities of sensory property of smoke from the leaf chemical properties were 100 % for tobacco-like, impact and irritation. As a result of K-means cluster analysis on the basis of tobacco taste, the desirable leaf chemical component contents were $6.5{\sim}6.8\;%$ in ether extract, $0.25{\sim}0.30\;%$ in chloride and $1.26{\sim}1.54$ in total nitrogen/nicotine ratio. This study suggest that the some regression equations may be useful to predict the sensory components of tobacco smoke from a few selected leaf chemical properties in burley tobacco and to select the burley tobacco leaves for enhance the tobacco taste of cigarette.