Background and Objective: Surveying of Balekhloo River’ s water is necessary because it is one of the main branches of Gharasoo River in Ardabil and supplying water for Yamchi dam Due to the presence of contaminant sources such as wastewater, residential areas, and industrial, agricultural and mineral water, river morphology. Today evaluation of water quality based on macro invertebrates variety has completed chemical methods of pollution recognizes. Method: In this study water quality examination of Balekhloo River in Ardebil, macro invertebrates were sampled in 5 stations along the river in 2 times of year (low water season and high water season). For results’ simulation measuring of some physico chemical parametres were perfomed. Macro invertebrates were identified and evaluated with Shannon winner variety index, Margalef biotic index and Pielou similarity index. Findings: In this study, ten orders of invertebrates in 23 categories were identified and counted and result simulation laboratory measured of physico chemical parameters like DO, Nitrate, PH, Debi and velocity. Discussion and Conclusion: Results showed that there are similarities between physical, chemical and biological indexes and Margalef biotic index was known more suitable bio assessment index to determine water quality in Balekhloo River. Finally, by comparison of physical, chemical and bio index parameters of Balekhloo River’ s water quality was classified into three region low, moderate and high pollution.

IntroductionThe distribution of plants in different habitats is influenced by environmental and edaphic conditions. Identifying the relationship between soil factors and vegetation, as well as the specific soil characteristics in which these species are found, is one of the important goals of this research. Taking steps in this direction will help prevent habitat destruction and facilitate the restoration of damaged areas. Let me know if you need any further adjustments! Materials and methods The study identified three representative areas using the physiognomic-systematic method, focusing on the habitat of Ferula assafoetida L. Areas with less than 15% coverage were classified as low-density, those with 15-30% coverage as medium-density, and areas with more than 30% coverage as high-density. In each representative area, eight transects of 1000 meters were systematically established and positioned perpendicularly to each other. To account for slope variations in sampling, quadrat sampling along the transects was employed. The plot size was determined using the minimum level method, with species density measured in 2 x 2 square meter plots across a total of 240 plots. To prepare soil samples, two soil profiles were dug at a distance of 500 meters along each transect, resulting in a total of 48 profiles from which soil samples were collected at depths of 0 to 30 cm. In each representative area, three transects of 1000 meters were placed perpendicularly, with ten sampling bases spaced 100 meters apart along each transect. The collected samples were transported to the Water and Soil Laboratory of Hormozgan University for analysis. The amount of gum collected from each base was measured using a digital scale with an accuracy of 0.001 grams. A comparison of the production of this plant gum was conducted across the different habitats. The changes in edaphic factors in representative areas were analyzed using SPSS software with the GLM test, revealing low density at 15.8 bases per hectare, medium density at 27.8 bases per hectare, and high density at 46.9 bases per hectare of Ferula assafoetida L. Results In the areas with low density, the soil acidity level was measured at 7.4, while in the medium-density area, it was 7.8, and in the high-density area, it reached 8. These results indicate that soil acidity is higher in densely populated areas and lower in areas with low density, suggesting that Ferula assafoetida is more compatible with alkaline soils. As soil acidity increases, the density of this plant decreases. The analysis of density changes in relation to organic matter percentage showed that organic matter has a direct effect on plant density; as organic matter increases, so does the density of the plant. Conversely, when the soil has low organic matter content, the density of Ferula assafoetida declines. Additionally, the comparison of average potassium levels revealed that the low-density area had the lowest potassium content, while the high-density area had the highest. The combined levels of calcium and magnesium were also lowest in the low-density area and highest in the dense Angozeh habitat. Furthermore, the number of Ferula assafoetida bases per unit area increased in regions with higher sand content, whereas the number of bases decreased in clay soils. This plant is not compatible with saline or acidic soils. ConclusionUnderstanding the ecological needs and performance of plant species is essential for implementing remedial activities in dry and desert ecosystems. Bestak city, located in Hormozgan province, is home to numerous Anghuzeh plantations, which have the potential to produce gum, generate currency, and provide significant economic value for local communities. The region is characterized by elevations ranging from 1900 to 2500 meters. This species exhibits a greater geographical distribution in areas with sand, silt, and high acidity, with increased density and decreased distribution in clay-rich areas. According to the findings, it appears that this plant thrives in light soils.

In recent years, the need for L-asparaginase in different industries has increased. L-asparaginase obtained from microorganisms is cost-effective, has no harmful effects on the environment, and improves the quality of products. In the present study, L-asparaginase-producing microorganisms were isolated and optimized from different sources, and selected strain enzymes were produced.L-asparaginase-producing yeasts were randomly isolated and purified from different parts of Isfahan. Strains were screened for L-asparaginase production. Then, the superior yeast strain with the highest enzymatic activity was selected for optimization. Under suitable pH, temperature, time, carbon source, and nitrogen source, multi-factor optimization was performed using response-level statistical software to investigate the simultaneous effect of several factors on production and the highest enzyme activity.In the present study, 5S2 yeast isolate led to the formation of the highest halo of L-asparaginase. This strain was first introduced as the L-asparaginase-producing strain and was registered in the NCBI database under Diutina mesorugosa strain SBG-IAUF-2 with access number MZ901211. Yeast 5S2 with enzyme activity equivalent to 1722.8 u / ml was selected as the selected strain for optimization. The results of multivariate optimization of enzyme activity showed that at pH 7, a concentration of 2% glucose as carbon source, the attention of 10% L-asparagine, a temperature of 35°C, and a time of 120 hours, there is the highest enzyme production activity and curve RSM is located in the optimization area.In the present study, after recording 5S2 yeast isolate for the first time as an L-asparaginase-producing strain in the NCBI database, extracellular L-asparaginase produced by the 5S2 yeast strain was introduced due to its high enzymatic activity as a potent strain in the production of L-asparaginase enzyme.IntroductionL-asparaginase as a food processing aid, is capable of significantly reducing acrylamide formation in starchy foods by over 90% without altering their taste or appearance. L-asparaginase enzymes are produced by various microorganisms, including bacteria like Streptomyces goulbarjensis, Enterobacter cloacae, and Serratia marcescens, as well as fungi and yeasts. Different isoforms of L-asparaginase originating from plants, eukaryotes, and prokaryotes have been identified, with those isolated from microorganisms, especially bacteria, proving more effective. Microorganisms producing L-asparaginase are found across diverse ecological areas, showcasing desirable enzymatic activity. The most effective isoforms of L-asparaginase currently available as anticancer drugs and produced commercially are sourced from microbial origins like Escherichia coli, Erwinia carotovora, and various Bacillus strains. Reports also mention the enzyme's production by filamentous fungi and yeasts such as Saccharomyces cerevisiae and Candida. Like Saccharomyces cerevisiae, Yeast is highlighted for its single-cell nature, rapid reproduction in cultivation environments, and its significance in various ecosystems like soil, swamps, and rivers due to its cellular processes post-translation and lack of endotoxins. Saccharomyces cerevisiae intricately regulates L-asparagine metabolism through complex pathways involving unrelated citrate products. The current study focuses on isolating, purifying, and identifying yeast strains producing L-asparaginase, optimizing its production under various environmental conditions to find an optimal method for generating these enzymes with reduced side effects and increased therapeutic potential.Materials and MethodsSampling and isolation of L-asparaginase-producing yeast: Soil samples were collected randomly from various points in Isfahan, particularly from agricultural fields, and diverse yeasts were isolated from these samples. For initial enrichment of the yeasts, 1 gram of collected soil samples was mixed in 100 milliliters of L-asparagine culture medium. This mixture was placed on a shaker for 3 days at 31 degrees Celsius and a speed of 130 rotations per minute, repeated thrice. Subsequently, 1 milliliter of the culture medium was taken and transferred to YPG agar medium.Yeast screening based on L-asparagine enzyme production: A rapid assay method was employed using a minimum asparagine agar medium. Colonies were placed on this medium and incubated at 30 degrees Celsius for 24 to 72 hours. Changes in color and halo diameter were examined every 24 hours. Yeasts capable of producing the enzyme hydrolyze asparagine in the culture medium, releasing ammonia and alkalinizing the medium. As a result, a shift in pH from acidic to alkaline changed the color of the medium from yellow to pink. Yeasts producing the enzyme caused an alkalinity shift, changing the medium color to a pinkish hue. Yeasts that did not produce this pink halo were eliminated.Molecular Identification of Superior Yeast Species Producing L-Asparaginase Enzyme: For molecular identification, the selected strains were incubated in YPG culture medium for 72 hours at 37 degrees Celsius. The colony-PCR method was employed to identify the genus and species of the yeasts. The DNA of each sample was added to the respective vials, and after adding the required reaction components and the designed primers, they were placed inside the thermocycler. Consequently, a 655 base pair fragment resulting from amplifying the gene encoding 18S-rRNA (ITS4, ITS1) using the forward and reverse primer was amplified via a polymerase chain reaction.Optimization of Enzyme Production via RSM Statistical Design: Multiple factors, including pH, carbon source, nitrogen source, temperature, time, and their various concentrations of carbon and nitrogen sources were examined in enzyme production. Based on the available sources in the culture medium, enzyme activity of Sizopek's Dax was subjected to various concentrations of glucose (from 1.5% to 2.5%) as a carbon source, a pH range from 5 to 9, L-asparagine as a nitrogen source (from 6% to 14%), temperature between 25 to 45 degrees Celsius, and time from 80 to 160 hours as factors in the optimization process using the Response Surface Methodology (RSM).Research FindingsIn this study, yeast 5S2 was examined for the first time to produce the L-asparaginase enzyme. After sequencing and obtaining the relevant file, the sequence underwent evaluation and editing using the Choromas software. Sequence comparison via the BLASTN server in the NCBI database revealed that the 18S-rDNA sequence of the 5S2 yeast strain bears the highest similarity and coverage with a strain of Diutina mesorugosa. Following assessments, this isolate was registered as a new strain for L-asparaginase production under the name Diutina mesorugosa strain SBG-IAUF-2 with accession number MZ901181 in the NCBI database. The highest enzyme activity during the optimization stage was achieved in test number 6, with 2% glucose, pH at 7, a duration of 120 hours, a temperature of 35 degrees Celsius, and 10% L-asparagine. This resulted in an enzyme activity of 1722.8 U/mL, indicating the maximum level of enzyme activity. In the optimization of L-asparaginase enzyme from the 5S2 strain, the highest activity was observed at pH 7, showing sensitivity to both acidic and alkaline conditions. Additionally, the enzyme was temperature-sensitive, exhibiting the highest activity at 35 degrees Celsius but decreasing notably at 45 degrees Celsius.Discussion of Results and ConclusionsGlucose and L-asparagine levels influenced enzyme production, achieving optimal enzyme yields at their moderate levels. Time was also a significant factor affecting enzyme production. This research successfully produced L-asparaginase using the isolated yeast strain 5S2 from the soil, optimizing its activity through the response surface method. The increased enzyme activity suggests the potential application of these results in various industries, including food processing and nanotechnology. The enzyme production levels in the optimization process suggest the potential for enhanced enzyme yields through strain optimization.