Yeast Eutrophication Lab

The results shown in table 1 clearly show that when the volume of yeast is increased in the milk solution, so does the rate of oxygen depletion and therefore the rate of eutrophication. It shows that when 2mL of yeast solution was added it took 32.86 minutes on average for the milk to be depleted of oxygen, while it took only 7.46 minutes on average for the 10mL of yeast to use up the oxygen present.

Figure 1 shows the minimum, maximum and average length of time it took for each solution to be depleted of oxygen. The scatter in the values suggests the presence of random errors.

This is representative of how eutrophication works in an aquatic environment. It shows that the greater the number of blue-green algae then the faster the oxygen depletion

of the water and hence faster rate of eutrophication.

DISCUSSION

Random errors are an inherent part of all experiments as measurements can never be taken perfectly.

A random error is caused by any factor which randomly affects the amount of scatter in the data. An increase in sample size allows averages to be calculated which reduces the effects of these random errors. By removing outliers in the data, the effect of random errors can be further minimised. A large amount of scatter in results indicated low precision and a large number of random errors. Some possible random errors in this experiment may have arisen when measuring the 12mL of milk solution for each test tube; some may have had slightly more and others slightly less than 12mL. Another random error could have occurred when adding 4 drops of methylene blue, some drops may have contained more liquid than others, meaning some test tubes may have contained less methylene blue indicator than

others.
Systematic errors are caused by a flaw in the equipment used and can cause a set of data results to be skewed as the instruments may be constantly reading a value lower or higher than the accurate value, and therefore affect the accuracy of experimental data. Systematic errors can be identified by repeating the experiment with different equipment at a different time. These can be minimised by ensuring equipment is correctly calibrated. Unlike random errors the effect of these errors cannot be minimised by averaging the results of multiple experiments. A possible systematic error in this experiment could be that the stopwatch was incorrectly calibrated and was consistently reading a time value lower or higher than the accurate time. Another possible systematic error could be that the 10mL measuring cylinder was not correctly calibrated and was measuring incorrect volumes of yeast solution consistently each time.
The reliability of this investigation could be increased if it was to be repeated with different materials at a later date. Because this was only one sample, the results could quite possibly be subject to a high level of random and systematic error and therefore are not particularly reliable.
A strength in this experiment was having a larger sample size than just 1.

By taking a sample size of 5, while still not particularly large it decreased the effect of random errors as an average was able to be calculated. Another strength was using the same size test tubes throughout the experiment. This made sure the surface area and exposure to oxygen in the air was kept consistent which would allow for more accurate results. A weakness of this experiment was that it was difficult to distinguish the exact point when the methylene blue had disappeared. As the top part of the test tube was exposed to oxygen in the air, the milk solution never went completely white and there was a blue ring on top of each test tube which stayed blue. It was also difficult to put the exact same amount of methylene blue into each test tube because you are not actually measuring it but rather just placing drops into the test tubes which is a little difficult to

control.
The experiment design could be improved by measuring out an exact volume of methylene blue (say 1tsp) to ensure that is kept constant across the experiment. Another improvement could be increasing the sample size by repeating the experiment with different equipment to reduce the effect of random errors and also possible identify the presence of any systematic errors.

CONCLUSION

Eutrophication is the process of the environment being enriched with nutrients and can lead to harmful algal blooms. Human activity, such as over-fertilisation has led to an increased rate of eutrophication and therefore more algal blooms. Algal blooms cause waterways to be depleted of oxygen, slow photosynthesis and can produce harmful toxins which can disrupt the working of the entire ecosystem. This investigation using yeast to represent blue-green algae shows how they affect the rate of oxygen depletion in the water. The hypothesis that if the volume of yeast is increased then the rate of oxygen depletion and eutrophication will increase was supported by the results of the experiment. This investigation shows that the greater the number of blue-green algae in waterways, the faster they will use up the oxygen and therefore the greater the effect they will have on marine life and the entire ecosystem.