Altered patterns of maltose and glucose fermentation by brewing and wine yeasts influenced by the complexity of nitrogen source

Maltose and glucose fermentations by industrial brewing and wine yeasts strains were strongly affected by the structural complexity of the nitrogen source. In this study, four Saccharomyces cerevisiae strains, two brewing and two wine yeasts, were grown in a medium containing maltose or glucose supplemented with a nitrogen source varying from a single ammonium salt (ammonium sulfate) to free amino acids (casamino acids) and peptides (peptone). Diauxie was observed at low sugar concentration for brewing and wine strains, independent of nitrogen supplementation, and the type of sugar. At high sugar concentrations altered patterns of sugar fermentation were observed, and biomass accumulation and ethanol production depended on the nature of the nitrogen source and were different for brewing and wine strains. In maltose, high biomass production was observed under peptone and casamino acids for the brewing and wine strains, however efficient maltose utilization and high ethanol production was only observed in the presence of casamino acids for one brewing and one wine strain studied. Conversely, peptone and casamino acids induced higher biomass and ethanol production for the two other brewing and wine strains studied. With glucose, in general, peptone induced higher fermentation performance for all strains, and one brewing and wine strain produced the same amount of ethanol with peptone and casamino acids supplementation. Ammonium salts always induced poor yeast performance. The results described in this paper suggest that the complex nitrogen composition of the cultivation medium may create conditions resembling those responsible for inducing sluggish/stuck fermentation, and indicate that the kind and concentration of sugar, the complexity of nitrogen source and the yeast genetic background influence optimal industrial yeast fermentation performance.

Solid-state fermentation: a continuous process for fungal tannase production

Truly continuous solid-state fermentations with operating times of 2-3 weeks were conducted in a prototype bioreactor for the production of fungal (Penicillium glabrum) tannase from a tannin-containing model substrate. Substantial quantities of the enzyme were synthesized throughout the operating periods and (imperfect) steady-state conditions seemed to be achieved soon after start-up of the fermentations. This demonstrated for the first time the possibility of conducting solid-state fermentations in the continuous mode and with a constant noninoculated feed. The operating variables and fermentation conditions in the bioreactor were sufficiently well predicted for the basic reinoculation concept to succeed. However, an incomplete understanding of the microbial mechanisms, the experimental system, and their interaction indicated the need for more research in this novel area of solid-state fermentation. (C) 2004 Wiley Periodicals, Inc.

Molecular analysis of maltotriose active transport and fermentation by Saccharomyces cerevisiae reveals a determinant role for the AGT1 permease

Incomplete and/or sluggish maltotriose fermentation causes both quality and economic problems in the ale-brewing industry. Although it has been proposed previously that the sugar uptake must be responsible for these undesirable phenotypes, there have been conflicting reports on whether all the known alpha-glucoside transporters in Saccharomyces cerevisiae (MALx1, AGT1, and MPH2 and MPH3 transporters) allow efficient maltotriose utilization by yeast cells. We characterized the kinetics of yeast cell growth, sugar consumption, and ethanol production during maltose or maltotriose utilization by several S. cerevisiae yeast strains (both MAL constitutive and AM inducible) and by their isogenic counterparts with specific deletions of the AGT1 gene. Our results clearly showed that yeast strains carrying functional permeases encoded by the MAL21, MAL31, and/or MAL41 gene in their plasma membranes were unable to utilize maltotriose. While both high-and low-affinity transport activities were responsible for maltose uptake from the medium, in the case of maltotriose, the only low-affinity (K-m, 36 +/- 2 mM) transport activity was mediated by the AGT1 permease. In conclusion, the AGT1 transporter is required for efficient maltotriose fermentation by S. cerevisiae yeasts, highlighting the importance of this permease for breeding and/or selection programs aimed at improving sluggish maltotriose fermentations.

Incomplete pregnancy and risk of ovarian cancer : results from two Australian case-control studies and systematic review

Although full-term pregnancies reduce the risk of ovarian cancer, it has not been conclusively established whether incomplete pregnancies also influence risk. We investigated the relationship between a history of incomplete pregnancy and incident epithelial ovarian cancer among over 4,500 women who participated in two large Australian population-based case-control studies in 1990-1993 and 2002-2005. They provided responses to detailed questions about their reproductive histories and other personal factors. Summary odds ratios (OR) and confidence intervals (CI) derived from each study using the same covariates were aggregated. We found no significant associations between the number of incomplete pregnancies and ovarian cancer, for parous (OR = 0.98, 95% CI: 0.89, 1.08) or nulliparous (OR = 1.06, 95% CI: 0.75, 1.48) women, nor for the number of spontaneous or induced abortions and ovarian cancer for parous women (OR = 0.95, 95% CI 0.82, 1.09; OR = 1.08, 95% CI: 0.86, 1.36) or nulliparous women (OR = 1.2, 95% CI: 0.6, 2.4; OR = 0.8, 95% CI: 0.47, 1.38), respectively. A systematic review of 37 previous studies of the topic confirmed our findings that a history of incomplete pregnancy does not influence a woman’s risk of epithelial ovarian cancer.

Clarification of cane juice for fermentation

Fermentation feedstocks in the sugar industry are based on cane juice, B molasses or final molasses. Brazil has been producing ethanol by directing sugarcane juice to fermentation directly or using lower quality juice as a diluent with B molasses to prepare the fermentation broth. One issue that has received only limited interest particularly from outside Brazil is the most appropriate conditions for clarification of the juice going to fermentation. Irrespective of whether the juice supply is the total flow from the milling tandem or a diffuser station or a part of the total flow, removal of the insoluble solids is essential. However, the standard defecation process used by sugar factories around the world to clarify juice can introduce unwanted calcium ions and remove other nutrients such as phosphorus and nitrogen that are considered essential for the fermentation process. An investigation was undertaken by SRI to assess the effects on the constituents of cane juice when subjected to the typical clarification process in an Australian factory and what conditions would be needed to provide a clarified juice suitable for fermentation. Typical juices from one factory were clarified in laboratory trials under a range of pH conditions and the resulting clarified juices analysed. The results indicated that pH had a major effect on the residual concentrations of key constituents in the clarified juice and that the selected clarification conditions are determined by the nominated quality criteria of clarified juice feedstock for fermentation. Further trials were conducted in overseas factories to confirm the results obtained in Australia. It became apparent that the preferred specifications for clarified juice going to fermentation varied from country to country. Each supplier of fermentation technology had criteria applying to clarified juice feedstock that would have a major impact on the standard of clarification required to achieve compliance with the criteria.

Civics and citizenship education in the national history curriculum : conducting the same music or rehearsing an incomplete tune?

This paper raises some questions about teaching and teacher education in the social sciences in response to the decision to implement a national curriculum in Australia. In particular, it contends that the decision to focus on discipline-specific knowledge in the social sciences will not necessarily meet the hopes of the Melbourne Declaration and deliver a 21st century curriculum that prepares students for the future. In doing so, it suggests that social educators need to engage with the broader discourse and political context shaping the push for curriculum reform in Australia and makes reference to the marginalisation of civics and citizenship education in the latest draft of the Australian curriculum: History.

Using incomplete online metric maps for topological exploration with the Gap Navigation Tree

This paper presents a general, global approach to the problem of robot exploration, utilizing a topological data structure to guide an underlying Simultaneous Localization and Mapping (SLAM) process. A Gap Navigation Tree (GNT) is used to motivate global target selection and occluded regions of the environment (called “gaps”) are tracked probabilistically. The process of map construction and the motion of the vehicle alters both the shape and location of these regions. The use of online mapping is shown to reduce the difficulties in implementing the GNT.

Handling incomplete data in survival analysis with multiple covariates

This paper studies the missing covariate problem which is often encountered in survival analysis. Three covariate imputation methods are employed in the study, and the effectiveness of each method is evaluated within the hazard prediction framework. Data from a typical engineering asset is used in the case study. Covariate values in some time steps are deliberately discarded to generate an incomplete covariate set. It is found that although the mean imputation method is simpler than others for solving missing covariate problems, the results calculated by it can differ largely from the real values of the missing covariates. This study also shows that in general, results obtained from the regression method are more accurate than those of the mean imputation method but at the cost of a higher computational expensive. Gaussian Mixture Model (GMM) method is found to be the most effective method within these three in terms of both computation efficiency and predication accuracy.

Intelligent reliability analysis with incomplete covariates

The reliability analysis is crucial to reducing unexpected down time, severe failures and ever tightened maintenance budget of engineering assets. Hazard based reliability methods are of particular interest as hazard reflects the current health status of engineering assets and their imminent failure risks. Most existing hazard models were constructed using the statistical methods. However, these methods were established largely based on two assumptions: one is the assumption of baseline failure distributions being accurate to the population concerned and the other is the assumption of effects of covariates on hazards. These two assumptions may be difficult to achieve and therefore compromise the effectiveness of hazard models in the application. To address this issue, a non-linear hazard modelling approach is developed in this research using neural networks (NNs), resulting in neural network hazard models (NNHMs), to deal with limitations due to the two assumptions for statistical models. With the success of failure prevention effort, less failure history becomes available for reliability analysis. Involving condition data or covariates is a natural solution to this challenge. A critical issue for involving covariates in reliability analysis is that complete and consistent covariate data are often unavailable in reality due to inconsistent measuring frequencies of multiple covariates, sensor failure, and sparse intrusive measurements. This problem has not been studied adequately in current reliability applications. This research thus investigates such incomplete covariates problem in reliability analysis. Typical approaches to handling incomplete covariates have been studied to investigate their performance and effects on the reliability analysis results. Since these existing approaches could underestimate the variance in regressions and introduce extra uncertainties to reliability analysis, the developed NNHMs are extended to include handling incomplete covariates as an integral part. The extended versions of NNHMs have been validated using simulated bearing data and real data from a liquefied natural gas pump. The results demonstrate the new approach outperforms the typical incomplete covariates handling approaches. Another problem in reliability analysis is that future covariates of engineering assets are generally unavailable. In existing practices for multi-step reliability analysis, historical covariates were used to estimate the future covariates. Covariates of engineering assets, however, are often subject to substantial fluctuation due to the influence of both engineering degradation and changes in environmental settings. The commonly used covariate extrapolation methods thus would not be suitable because of the error accumulation and uncertainty propagation. To overcome this difficulty, instead of directly extrapolating covariate values, projection of covariate states is conducted in this research. The estimated covariate states and unknown covariate values in future running steps of assets constitute an incomplete covariate set which is then analysed by the extended NNHMs. A new assessment function is also proposed to evaluate risks of underestimated and overestimated reliability analysis results. A case study using field data from a paper and pulp mill has been conducted and it demonstrates that this new multi-step reliability analysis procedure is able to generate more accurate analysis results.

Microalgal biomass as a fermentation feedstock for bioethanol production

BACKGROUND The increasing cost of fossil fuels as well as the escalating social and industrial awareness of the environmental impacts associated with the use of fossil fuels has created the need for more sustainable fuel options. Bioethanol, produced from renewable biomass such as sugar and starch materials, is believed to be one of these options, and it is currently being harnessed extensively. However, the utilization of sugar and starch materials as feedstocks for bioethanol production creates a major competition with the food market in terms of land for cultivation, and this makes bioethanol from these sources economically less attractive. RESULT This study explores the suitability of microalgae (Chlorococum sp.) as a substrate for bioethanol production via yeast (Saccharomycesbayanus)under different fermentation conditions. Results show a maximum ethanol concentration of 3.83 g L -1 obtained from 10 g L-1 of lipid-extracted microalgae debris. CONCLUSION This productivity level (∼38% w/w), which is in keeping with that of current production systems endorses microalgae as a promising substrate for bioethanol production.