Abstract: A metabonomics-based tobacco leaf mildewing identification method, which comprises: obtaining tobacco leaf samples of the same variety, and carrying out artificial mildewing on a certain amount of tobacco leaf samples to obtain mildewed tobacco leaves; measuring volatile and semi-volatile components in the tobacco leaves before and after the tobacco leaf samples are mildewed by adopting a solid phase microextraction-gas chromatography-mass spectrometry method; performing data processing on the collected mass spectrum data to obtain the proportion content of different types of compounds in the mildewed sample and the normal sample, and further obtaining the change difference of the content of volatile compounds in the tobacco leaf sample before and after mildewing; and establishing a tobacco leaf mildewing identification model according to the discrimination variables. The accuracy and efficiency of tobacco mildew identification can be improved, the quality of tobacco shreds is improved.

Abstract: It is disclosed here engineered cellulolytic microorganisms capable of producing ethanol from lignocellulosic feedstock with high yield. Multiple genes in Thermoanaerobacterium saccharolyticum that are involved in the pyruvate to ethanol pathway are disclosed which may be transferred into C. thermocellum or other natively cellulolytic microorganisms.