Masters Degrees (Microbiology)
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Browsing Masters Degrees (Microbiology) by Author "Bush, T."
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Item Seasonal variation of microflora and their effects on the quality of wood chips intended for pulping.(2013) Govender, Lucretia.; Bush, T.; Govinden, Roshini.Eucalyptus, pine and wattle are the predominant exotic wood species used in the production of dissolving pulp in South Africa. On entering the mill, wood is chipped and stored in outdoor piles where it becomes vulnerable to microbial degradation and spontaneous combustion. Major losses of stored chips are due to high temperatures and combustion caused by heat energy released by microbial fermentation. Changes in the chemistry of the wood chips caused by the metabolic activity of indigenous microflora combined with the inherent chemical characteristics of each wood species could have a potential impact on final pulp quality and yield. Therefore the objective of this study was to analyse the microbial (bacteria and fungi) communities present in commercial wood chip piles and correlate this with changes in the chemistry of the wood in summer and winter. The molecular fingerprinting technique of Denaturing Gradient Gel Electrophoresis (DGGE) was optimized for the detection of microbial diversity in commercial wood chips. Wood chips were collected from an industrial wood yard and milled to different specifications. A total of four primer sets with GC-clamps were tested in nested PCR for DGGE analysis. 16S and 18S rRNA genes were amplified using 338f-GC/518r; 933F-GC/1387R (bacteria) and NS26/518R-GC; EF4F/518R-GC (fungi), respectively. Several gel gradients were examined to determine optimal separation of bacterial (40/60%, 35/50%, 30/60%) and fungal (35/50%, 20/45%, 25/50%) PCR-DGGE products. Comparison of the DGGE profiles revealed greater diversity in the milled wood chips amplified using primer sets; 338F-GC/518R (16S) and NS26/518R-GC (18S) with gradients of 30/60% (16S) and 25/50% (18S). Once optimized, this standardized protocol was tested against five samples to assess its applicability to woodyard samples. 16S and 18S DGGE profiles were generated and amplicons excised from gels, re-amplified, sequenced and the microorganism from which the DNA originated was determined. In the second phase a cross-sectional study of wood chip piles from a commercial dissolving pulp mill was conducted with sample collected in summer and winter using the optimized PCR-DGGE technique. Microbial strains were identified after sequencing of 16S and 18S rRNA amplicons separated by DGGE. Chemical characteristics of the wood chips were evaluated by conducting extractive analyses using HPLC. Due to unpredictable combinations of different wood species in commercial wood chip piles, the third phase involved the investigation of individual Eucalyptus species. The microflora indigenous to the two Eucalyptus species (E. dunnii and E. nitens) and a combination of the two were subjected to winter and summer simulations for one month during which samples were tested for wood chemistry properties, microflora and the final samples were used to generate dissolving pulp. Using the PCR-DGGE method eighteen bacterial and twelve fungal species were identified from the five samples collected from the commercial wood chip pile, compared to the ten bacterial and nine fungal isolates which were identified using the culturing technique and standard 16S and 18S rRNA gene sequence analysis. Predominant genera in the optimization phase of this study were Klebsiella spp. (×3), Bacillus spp. (×2), Pantoea spp. (×2), Pseudomonas spp. (×2) and Paecilomyces spp. (×2). Application of the optimized DGGE technique to samples collected from the commercial pulping mill in summer and winter revealed variable profiles indicating a range of bacterial and fungal strains that varied in intensity in the areas and seasons sampled. Seventy nine (45 in summer and 34 in winter) and 29 (20 in summer and 9 in winter) distinct amplicons representing bacteria and fungi, respectively, were visualized. Predominant genera in summer were Pantoea rodasii, Inquilinus limosus, Streptococcus sp., Klebsiella spp., Diversispora sp., Boletaceae sp., Scutellospora sp., and Ophiostoma bicolour. In winter the prevailing genera were Leuconostoc palmae, Streptococcus sp., Bacillus spp., Diversispora sp., Boletaceae sp., and Bullera sp. Lower cellulose levels in summer correlated significantly with high microbial loads and the predominance of Bacillus spp., suggesting that in warm humid environments storage should not exceed 1-2 weeks. No correlations were determined between the decreased hot water levels in winter and microbial activity, however they were correlated to increased exposure of those samples to environmental factors. Chemistry data on the wood chips imparts the quality of the wood which only permitted projection of final pulp quality. This inadequacy was addressed in the third phase which included identification of microbial strains, originating from the individual Eucalyptus species, after sequencing of 16S and 18S rRNA amplicons separated by DGGE. Fungal and bacterial species were also isolated, cultured, identified and screened for lignocellulolytic enzyme activity. Ninety two and 88% of the fungi isolated were capable of producing cellulase and xylanase, respectively. Significant correlations exist between the microflora, seasons (greater diversity and loading in summer) and the chemical and physical properties of wood chips (lower cellulose and viscosity in summer) as well as Eucalyptus species (significantly higher cellulose and viscosity for the combination and E. nitens). Indigenous microflora of each wood species may be one of the contributing factors to poor/good pulp quality, as significant correlations were made between enzyme production of microorganisms and wood chemistry which ultimately has an impact on the final pulp quality and yields. This investigation provides proof of concept that combining wood species with different deterioration rates results in an overall improvement in pulp quality and thus paves the way for a practical and applicable approach to managing quality of chips.