The application of different multivariate statistical approaches for the interpretation of a complex data matrix obtained during the period 2004-2005 from Uluabat Lake surface water is presented in this study. The dataset consists of the analytical results of a 1 year-survey conducted in 12 sampling stations in the Lake. Twelve parameters (T, pH, DO, PO(-3)(4), NH(4)-N, NO(2)-N, NO(3)-N, SO(3-)(4), BOD, COD, TC, FC) were monitored in the sampling sites on a monthly basis (except December 2004, January and February 2005, a total of 1,296 observations). The dataset was treated using cluster analysis, principle component analysis and factor analysis on principle components. Cluster analysis revealed two different groups of similarities between the sampling sites, reflecting different physicochemical properties and pollution levels in the studied water system. Three latent factors were identified as responsible for the data structure, explaining 77.35% of total variance in the dataset. The first factor called the microbiological factor explained 32.34% of the total variance. The second factor named the organic-nutrient factors explained 25.46% and the third factor called physicochemical factors explained 19.54% of the variances, respectively.

The present study investigated the isolation and identification of airborne fungi from three different urban stations located in Eskisehir (Turkey). Air samples were taken by exposing a Petri dish with Rose-Bengal streptomycin agar medium for 15 min and after incubation the number of growing colonies was counted. The sampling procedure for fungi was performed 35 times at the research stations weekly between March and November 2001. A total of 2518 fungal and 465 actinomycetes colonies were counted on 420 Petri plates over a nine-month period. In total, some 20 mould species belonging to 12 genera were isolated. Alternaria alternata, Cladosporium cladosporioides and Scopulariopsis brevicaulis were the most abundant species in the study area (13.66, 5.80 and 5.50% of the total, respectively). Relationships between fungal spore numbers, aerosol air pollutants (that is the particulate matter in the air) and sulphur dioxide together with the meteorological conditions were examined using statistical analysis. Number of fungi and actinomycetes were tested by multivariate analysis (MANOVA) according to the areas and months. Fungal numbers were nonsignificant according to the areas and months ( p > 0.05), but the number of actinomycetes recorded was significant ( p < 0.01).

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The current study describes the phytochemical profile, antimicrobial, mutagenic, and antimutagenic activity of Perovskia atriplicifolia Benth. essential oil, collected in Pakistan. The sample of essential oil was obtained from aerial parts of the plant by hydrodistillation and analyzed by gas chromatography-mass spectrometry. From the 18 compounds identified, the major compounds were camphor (28.91%), limonene (16.72%), a-globulol (10.21%), trans-caryophyllene (9.30%), and a-humulene (9.25%). Antimicrobial activity of the oil was evaluated using agar diffusion method and agar dilution method. The antimicrobial test results showed that the oil had a significant potential antimicrobial activity against 10 bacteria and 5 fungal strains. Furthermore, the mutagenic and antimutagenic activity of the oil was investigated through the Salmonella=microsome test system, with and without S9 metabolic fraction in Salmonella typhimurium TA98 and TA100. None of the tested concentrations of oil was found mutagenic. However, all tested concentrations did show an increase in antimutagenic activity with or without S9 fraction against 2-aminofluorene and daunomicina, but not sodium azide. Results presented here suggest that the essential oil of P. atriplicifolia possesses antimicrobial properties and is therefore a potential source of antimicrobial ingredients for the food and pharmaceutical industry. In addition, that it also has antimutagenic activity raises the importance of this essential oil in this area.

In the present study, nine terverticillate Penicillium isolates (P. griseofulfum, P. puberulum, P. crustosum, P. aurantiogriseum, P. chrysogenum, P. primulinum, P. expansum, P. viridicatum, Eupenicillium egyptiacum) from 56 soil samples were characterized genetically by a PCR method. The DNAs of the strains were isolated using the glass beads and vortexing extraction method and then used for PCR amplification with the internal transcribed spacer 1 (ITS1) and ITS4 universal fungal specific primers. The ITS regions of fungal ribosomal DNA (rDNA) were sequenced through the CEQ 8000 Genetic Analysis System. ITS-5.8S sequences obtained were compared with those deposited in the GenBank Database. The results indicated that the identification of Penicillium species with PCR based methods provided significant information about the solution to taxonomy and improve food safety and to protect the users from harmful contaminants such as mycotoxins, which must be controlled during the production of agricultural materials as well as during the processing of food and feed.