Yeast population used in industrial production of fuel-ethanol may vary according to the plant process condition and to the environmental stresses imposed to yeast cells. Therefore, yeast strains isolated from a particular industrial process may be adapted to such conditions and should be used as starter strain instead of less adapted commercial strains. This work reports the use of PCR-fingerprinting method based on microsatellite primer (GTG)5 to characterize the yeast population dynamics along the fermentation period in six distilleries. The results show that indigenous fermenting strains present in the crude substrate can be more adapted to the industrial process than commercial strains. We also identified new strains that dominate the yeast population and were more present either in molasses or sugar cane fermenting distilleries. Those strains were proposed to be used as starters in those industrial processes. This is the first report on the use of molecular markers to discriminate Saccharomyces cerevisiae strains from fuel-ethanol producing process.

Aims:  To identify and characterize the main contaminant yeast species detected in fuel‐ethanol production plants in Northeast region of Brazil by using molecular methods. Methods and Results:  Total DNA from yeast colonies isolated from the fermentation must of industrial alcohol plants was submitted to PCR fingerprinting, D1/D2 28S rDNA sequencing and species‐specific PCR analysis. The most frequent non‐Saccharomyces cerevisiae isolates were identified as belonging to the species Dekkera bruxellensis, and several genetic strains could be discriminated among the isolates. The yeast population dynamics was followed on a daily basis during a whole crop harvesting period in a particular industry, showing the potential of D. bruxellensis to grow faster than S. cerevisiae in industrial conditions, causing recurrent and severe contamination episodes. Conclusions:  The results showed that D. bruxellensis is one of the most important contaminant yeasts in distilleries producing fuel‐ethanol from crude sugar cane juice, specially in continuous fermentation systems. Significance and Impact of the Study:  Severe contamination of the industrial fermentation process by Dekkera yeasts has a negative impact on ethanol yield and productivity. Therefore, early detection of D. bruxellensis in industrial musts may avoid operational problems in alcohol‐producing plants.

Monitoring for wild yeast contaminants is an essential component of the management of the industrial fuel ethanol manufacturing process. Here we describe the isolation and molecular identification of 24 yeast species present in bioethanol distilleries in northeast Brazil that use sugar cane juice or cane molasses as feeding substrate. Most of the yeast species could be identified readily from their unique amplification-specific polymerase chain reaction (PCR) fingerprint. Yeast of the species Dekkera bruxellensis, Candida tropicalis, Pichia galeiformis, as well as a species of Candida that belongs to the C. intermedia clade, were found to be involved in acute contamination episodes; the remaining 20 species were classified as adventitious. Additional physiologic data confirmed that the presence of these major contaminants cause decreased bioethanol yield. We conclude that PCR fingerprinting can be used in an industrial setting to monitor yeast population dynamics to early identify the presence of the most important contaminant yeasts.

Aims: The present work focuses on the possibility to use conserved primers that amplify yeast ITS1-5AE8S-ITS2 ribosomal DNA locus (rDNA) to detect the presence of non-Saccharomyces cerevisiae yeast in fermentation must of bioethanol fermentation process. Methods and Results: Total DNA was extracted from pure or mixed yeast cultures containing different cell concentrations and different contaminant/fermenting yeast concentrations and submitted to PCR. Upon improvement of detection limits and DNA extraction protocol, must samples of distillery were checked for the presence of contaminant yeast. Contaminant rDNA bands were detected only in industrial samples during contamination episodes, but not in noncontaminated must. Conclusions: The method described here could detect the presence of contaminant yeast from industrial must in eight hours after sampling. Significance and Impact of the Study: The improved procedure may help to avoid severe contamination episodes at fermentation industries by decreasing the detection time from 5 days to 8 h and possible quantification of contaminant yeasts that can impose economical loss to the process.

No abstract