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Style Guide AIET  [Name] [Institution] [Date] Research Question Does altering in the conditions like the concentration in the sucrose solution, change in the temperature and amount of oxygen directly affect the growth in population of yeast over a 192-hours of fixed period? Rationale for the experiment The yeast that is just starting to grow at the cellular, molecular, and genomic stages, S. cerevisiae is a very strong modelling system in order to understand eukaryotic biology1 and 2. Since it can be obtained worldwide in a great range of human-associated products like wine, sake, beer, and some of the other fermented beverages as well as in the wild product like plant, soil, and insect biotopes.  Saccharomyces. cerevisiae has recently also found in population genomics3, 4, and 5. The number of published Sacccharomyces. cerevisiae genome sequences has increased in recent years, revealing a greater degree of diversity in the genes and population structure is also very complex in this yeast (Peter et al., 2018). Saccharomyces cerevisiae is found in a wide range of foods, but it is rarely identified as a spoilage agent. It is primarily responsible for the fermentation of foods and beverages which are consisting of the large amount of sugar. Since Sacchacromyces. cerevisiae has an ability to tolerate ethanol concentrations up to 15%, therefore very easily can ruin alcoholic drinks such as wine and beer on occasion (Dao et al., 2018). Saccharomyces cerevisiae is also present in dairy products such as milk, cheese, and yoghurts, as well as in the fermented vegetables and in minimum amounts also in those vegetable products which are processed, though the role of this species in product spoilage is unknown (Yang et al., 2019). Reaction of sucrose with yeast to produce ethanol and carbon dioxide Yeast consumes sucrose, so it must first break it down into glucose and fructose in order to pass it through its cell wall. The enzyme Invertase is produced by yeast to break down sucrose. Now this enzymes breaks yeast into ethanol and carbon dioxide (Kawai et al., 2020). Since yeast is a fungus, it requires energy to survive and develop. This energy comes from sugar and.Yeast, like human beings, also respire in which it utilizes oxygen and produce sugar (Rodríguez Madrera, Pando Bedriñana and Suárez Valles, 2021) As a result, thje high concentration of sugar activate this microorganism to grow and rise in number, but this is also true that in very high sugar concentration the yeast cells are unable to grow like honey.. Via a process known as “respiration,” yeast, like human beings, can utilize oxygen to produce energy from sugar. As a result, it can be prove that high concentration of sugar helps the yeast cells to divide quickly and increase in number, which results in the rise of the yeast cells. The most important substance for the growth of yeast cells is water and found that it is 90% more quickly grow in the water. If the solution is concentrated osmotically then the water molecules start moving from the yeast cells to the solution because of the decrease concentration of the water in the solution and the death of the yeast cells start therefore it is necessary that water should be present in greater concentration in order to increase thje growth of yeast cells (Lange et al., 2017). The amount of sugar available for respiration and synthesis of cell materials is the limiting factor up to a certain concentration, which makes the yeast able to absorb more water contents than they are needed for the growth. This is also true that both process of the synthesis and respiration will proceed in a fastest rate if the high concentration of sugar is present in the solution, water absorption slows to the point that it becomes the limiting factor (González-Garcinuño et al., 2017). Alcohol is poisonous to both yeast and humans, so when the alcohol content is too high, the yeast is unable to expand. This is why wine has a maximum alcohol content of around 12%. Methodology The initial experiment used a 2 percent sucrose substrate and 10mL of yeast medium suspension (2 drops). This has been done by collecting the yeast cells in two intervals of time, one is at 24 hours interval and the other with 120 hours of time span. For counting purpose of the yeast cells a compound microscope is used by making a smear and covering it with the cover slip of 0.5 cm2 size. In this study dependent and independent variables are used like number of yeast cells is used as a dependent variable and sucrose solution is used as an independent variable. Modification of the methodology The approach which is used in order to find reliable and most accurate data in order to get the solid conclusion regarding the dependent and independent variables is original Therefore . As a result, the original experiment was modified by increasing the population sample size. The inclusion of several concentrations improved the validity and precision of the study, in order to maintain and establish a causal relationship. To ensure that parallax error did not invalidate the results, the same individual counted the number of yeast cells were counted at each time interval. Raw and processed data Table 1 Interpretation of the table The data of the above table 1 shows how the percent concentration of sugar disaccharide influences yeast growth over a fixed time which comprises of the 192 hours. The change in the mean of average percentage of reacting sample concentration has been found moderate, and thus could be greatly improved with additional statistical research. Table 1 is actually explaining that three types of samples are used having different concentration of the sugar(sucrose) solution in order to find that change in concentration will impact on the growth of the yeast cells. It has been found that in sample 1 the number of yeast cells after 144 hours is becoming 112, in sample 2 it reached up to 148 and in sample 3 this number increased up to 248. Therefore it can be concluded that when concentration of the sucrose in the solution increased. Then yeast cells number also increased as the microorganism when getting more favorable conditions start dividing in more number and the growth of the microorganism increases. Graph 1: explains the yeast cells growth mean yield across each sucrose concentration over the time of 192- fixed point Interpretation As seen in the graph 1 above, yeast growth on sugar substrate occurs in three stages at the same time: exponential growth, decay, and constant horizontal growth (carrying capacity). This is due to the fact that each of the concentration organisms exhibits a sudden increase in growth from 24 to 144 hours. Furthermore, three types of samples with three different concentration of the sucrose solutions are used along with different time periods. Hence, 3 percent solution clearly demonstrates that more concentrated substrates promote faster development. And a higher concentration induces faster growth than a lower concentration this leads to confirm the research question of whether the change in the concentration of a sucrose solution has an effect on yeast cell development. While the 1 and 2 percent solutions showed that the change in the percentage of the yeast growth is linear while, all three solutions showed a consistent growth pattern after the 144-hour mark. Analysis According to the regular error, error bars, 3 percent was done with greater overall precision, that can be observed from table 2. Furthermore, the error bars which are overlapping between 120h and 144h mean that the outcomes for each concentration are in the range which is commonin all three solutions. This is a reason that , the error bars are not converging from 24 to 48 hours, implying that their outcomes are not in the suitable range. This may indicate that no definitive correlation is existing after the 115-hour mark, and some more research is required for further study. Graph 2: Change in mean percentage of the yeast cell population based on 192 h testing period Interpretation This data shows that species 1 and 2 have a larger average percentage shift from the mean, indicating that the error bars had a moderately low precision. As shown in table 1, the percent differential remains relatively low at 3%. Furthermore, the negative trend-line indicates that the overall shift was declining at each time interval. Analysis The most significant change occurred between hours 24 and 72, indicating exponential yeast development. Furthermore, from 92h to 144h, a steady decay is maintained, implying that 3 percent reached carrying capacity before 2 percent, and that 2 percent reached carrying capacity before 1percent. As a result, evidence suggests that yeast growth is influenced by concentration. Evaluation To obtain a better understanding of the data during the step of the process in this experiment, it is necessary that four types of evidences were used as the limitation which includes: standard error, confidence interval-(95%), standard deviation and percentage shift. As a consequence, the quality of the results may be harmed due to the precision lack apparent in between the phases of the experiment. The findings from each concentration were contradictory, as shown in table 1. Furthermore, the relatively high standard deviation and percentage indicate that internal and external variables were not adequately accounted for. In comparison to the other two, solution 3% give the lower values of the standard deviation, standard error and also the percentage. Refer to table 1 for Species, which indicates that the experimenter treated the data with accuracy and precision. In addition, the sample in smaller size limits the ability of the data to be concluded, making definitive links between relevant associations impossible. As a result, the evidence’s results are small and unreliable. Sources of error Effects on Reliability The glass stirring rod used in the experiment was not properly cleaned after each insect, which may have altered the concentrations and harmed the accuracy of the experiment. Effects on Validity The solutions were not housed in the same way in the incubator. Suggestions that certain solutions could have fallen short of the 30 degree target. As a result, the data’s accuracy is compromised. Results came along with inaccuracy and this is because of the reason of using coverslip of 0.5 cm2 size which causes an imperfect counting of the cells and thus affect the data adversely. Suggested Improvements and Suggestions Lessened random error in the experimental phase will greatly improve reliability and validity. A larger sample size, on the other hand, is essential to obtain a better understanding of yeast growth in relation to sucrose. An electronic courting system is needed to improve the precision and accuracy of this data and to reduce human error. Evaluations To demonstrate a valid correlation between concentration and growth, reroute the experiment through compare it with the control.Extend the experiment by seeing if a mono disaccharide sugar (glucose) has a longer time to affect yeast growth than a disaccharide sugar molecule. Conclusion of the Study To be conclusive, the proof, despite having moderately low precision and accuracy throughout, was conclusive. However, it cannot be assumed that the data shows a strong linear association, indicating that higher sucrose (sugar substrate) concentrations affect yeast growth faster than lower concentrations. Significant limitations have hampered the data’s ability to establish a clear connection between the degrees to which concentration affects development in relation to carrying capacity. More statically research may be needed to examine this further and conclusively support this hypothesis. References  Dao, F., Lv, H., Wang, F., Feng, C., Ding, H., Chen, W. and Lin, H., 2018. Identify origin of replication in Saccharomyces cerevisiae using two-step feature selection technique. Bioinformatics, 35(12), pp.2075-2083 González-Garcinuño, Á., Tabernero, A., Sánchez-Álvarez, J., Galán, M. and Martin del Valle, E., 2017. Effect of bacteria type and sucrose concentration on levan yield and its molecular weight. Microbial Cell Factories, 16(1). Kawai, M., Tsuchiya, A., Ishida, J., Yoda, N., Yashiki-Yamasaki, S. and Katakura, Y., 2020. Suppression of lactate production in fed-batch culture of some lactic acid bacteria with sucrose as the carbon source. Journal of Bioscience and Bioengineering, 129(5), pp.535-540.  Lange, A., Becker, J., Schulze, D., Cahoreau, E., Portais, J., Haefner, S., Schröder, H., Krawczyk, J., Zelder, O. and Wittmann, C., 2017. Bio-based succinate from sucrose: High-resolution 13C metabolic flux analysis and metabolic engineering of the rumen bacterium Basfia succiniciproducens. Metabolic Engineering, 44, pp.198- Peter, J., De Chiara, M., Friedrich, A., Yue, J., Pflieger, D., Bergström, A., Sigwalt, A., Barre, B., Freel, K., Llored, A., Cruaud, C., Labadie, K., Aury, J., Istace, B., Lebrigand, K., Barbry, P., Engelen, S., Lemainque, A., Wincker, P., Liti, G. and Schacherer, J., 2018. Genome evolution across 1,011 Saccharomyces cerevisiae isolates. Nature, 556(7701), pp.339-344. Rodríguez Madrera, R., Pando Bedriñana, R. and Suárez Valles, B., 2021. Evaluation of indigenous non-Saccharomyces cider yeasts for use in brewing. European Food Research and Technology, 247(4), pp.819-828. Yang, H., Yang, W., Dao, F., Lv, H., Ding, H., Chen, W. and Lin, H., 2019. A comparison and assessment of computational method for identifying recombination hotspots in Saccharomyces cerevisiae. Briefings in Bioinformatics, 21(5), pp.1568-1580.


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