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Aim:To investigate the effect of glucose concentration on anaerobic
respiration in yeast.
2* conical flask
Delivery tube with bung
Method:I am going to do 5 tests & each test will be performed 3 times
to get an average result. In one conical flask, I will mix together
25ml of yeast & 25ml of a glucose solution, with a delivery tube with
a bung in the top of it and leave it for 5 min so it gets
acclimatised; in the other conical flask I will put enough water to
cover the end of the delivery tube.
On the first test I will use a 10% concentration of glucose.
On the second test I will use a 15% concentration of glucose.
On the third test I will use a 20% concentration of glucose.
On the fourth test I will use a 25% concentration of glucose.
On the fifth test I will use a 30% concentration of glucose.
I will then put the yeast & glucose mixture in a warm water bath and
count how many bubbles of CO2 are produced within 5 min.
Fair Test:to make it a fair test, I am going to keep the water
temperature, volume of yeast and glucose, concentration of yeast and
the timings constant and the one thing I will change is the
concentration of the glucose so we can tell how the concentration of
glucose effects the respiration of yeast.
Prediction: I predict that the conical flask with the yeast and the
most glucose concentration will respire quickest.
[IMAGE]The conical flask with the yeast and the least glucose
concentration will respire slowest. This is because of the Lock and
Key Theory. Enzymes basically work due to the 'lock and key' theory,
where the substrate (the 'key') fits into the active site on the
enzyme and they bind together, the reaction takes place and the
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enzyme ready to perform the binding again. An enzyme can only bind
with a substrate that fits the shape of the active site unique to that
kind of enzyme. When some substrate substances induce a fit with the
enzyme, the enzyme may not be able to 'accept' some other substrates.
10% Glucose concentration
20% Glucose concentration
25% Glucose concentration
30% Glucose concentration
28 bubbles in 5 min
33 bubbles in 5 min
54 bubbles in 5 min
61 bubbles in 5 min
107 bubbles in 5 min
26 bubbles in 5 min
40 bubbles in 5 min
44 bubbles in 5 min
50 bubbles in 5 min
103 bubbles in 5 min
27 bubbles in 5 min
45 bubbles in 5 min
56 bubbles in 5 min
65 bubbles in 5 min
100 bubbles in 5 min
27 bubbles in 5 min
39 bubbles in 5 min
51 bubbles in 5 min
59 bubbles in 5 min
104 bubbles in 5 min
1. Make sure all glassware is away from edge of table.
2. Put all Coats, Bags & Stools away.
3. Make sure water bath doesn't get too hot.
4. Always wash hands when finish.
5. Take care of all the glassware.
From my final results table, I can use the average results to plot a
graph of results.
From my results I can identify a line of best fit. My graph shows that
as the concentration of glucose solution is increased, the amount of
carbon dioxide produced also increases. The fact that carbon dioxide
is being produced, proves that respiration is taking place. The
continual increase of carbon dioxide means that the rate of
respiration increases as the concentration becomes less dilute and
stronger. I can see that the rate of respiration is at its slowest
when there is little glucose solution present. When the concentration
was of 10%, the amount of bubbles produced isn't very high at an
average of 27 in 5 min. There is a big difference between the rates of
reaction of 10% compared with the 30% concentrations. This definitely
suggests that concentration has a large impacting affect on the rate
of respiration. The concentration of a solution can speed up or slow
down the rate of respiration depending on how concentrated the
solution is. In the case of my experiment, the strongest concentration
speeded up the rate of respiration while the weakest concentration was
very slow in producing carbon dioxide thus, showing that the rate of
respiration was much slower.
I thought the results obtained were quite accurate. They seem to be in
the same sort of shape on my graph. However, on my repeats there are
some noticeable differences between test 2 and the others. On test 2
for 20%, the result is 10 and 12 bubbles less than test 1 & 3 and this
happens again for 25%, it is 11 and 15 bubbles less than test 1 & 3.
The explanation I can offer for this is that there must have been a
mistake I have made or I might have not let it rest for the allotted
time. I thought all of my other results generally fitted the overall
trend well. I thought the experiment allowed the prediction to be
tested very well as it proved the points that I wanted it to, and very
conclusively as well. I thought my method was pretty foolproof too
which would help anyone who wanted to do this experiment and only had
my piece of coursework. I think my results were reliable enough to
support the prediction especially due to the fact that there are no
obvious abnormalities. If I was to do the experiment again, I would
use a different means of counting the bubbles as the human eye could