4. Discussion

4. Discussion


4.1 Key findings & Analysis of results


Our experiment has shown that unwashed eggs have less bacterial growth on the egg shell as compared to washed eggs. All of the bacterial count values and RGB values were similar for eggs which were washed in the same amount of time. However, there are four anomalies.


Firstly, the eggs washed for 50 seconds, 4A and 4B had bacterial count values of 9 and 5 respectively. The difference in the results was significant. This meant that we made an error in the experiment. We felt that the method of spreading on the agar might have to do with the abnormality. As a different person had done the transfer of bacteria from the cotton swab to the agar plate for 4A and 4B, there could have been some different actions that has caused the results to turn out this way.


Two other anomalies were found in the RGB data. With regard to the RGB data, 3A and 3B had a difference in value of 65, while 1A and 1B had a greater difference of 116. The other values had a difference of less than 20. This might have been due to the method of spreading as mentioned above.


The last anomaly concerns 4A and 4B. Aforementioned ranking data, 4A and 4B had a vast bacterial count values, but the RGB results of 4A and 4B was equivalent values of 423. The ranking data might have been inaccurate because it was our own judgment.  


Thankfully, these anomalies do not affect our first hypothesis as unwashed eggs still had the least amount of bacteria.


4.2 Explanation of key findings
Our findings wash that unwashed eggs have lesser bacteria on their egg shells as compared to all other washed eggs. This finding can be connected to what we have found in our background research. Eggs generally have a protective layer, called bloom. This protective layer prevents bacteria from penetrating through and growing on the egg shell. When we wash the eggs, the bloom is washed off, hence washed eggs generally have higher bacterial count and RGB values. Unwashed eggs, on the other hand, would have lower bacterial count or RGB value because the bloom was still present, and prevented bacteria from growing on the egg shell.


4.3 Evaluation of Hypothesis


Our findings wash that unwashed eggs have lesser bacteria on their egg shells as compared to all other washed eggs. This finding can be connected to what we have found in our background research. Eggs generally have a protective layer, called bloom. This protective layer prevents bacteria from penetrating through and growing on the egg shell. When we wash the eggs, the bloom is washed off, hence washed eggs generally have higher bacterial count and RGB values. Unwashed eggs, on the other hand, would have lower bacterial count or RGB value because the bloom was still present, and prevented bacteria from growing on the egg shell.
Our first hypothesis - unwashed eggs will have a lesser amount of bacteria on the shells as compared to all the other eggs which were washed - is proven right. In both set A and B of the ranking and RGB value method of evaluation, the bacterial count on unwashed eggs is significantly lesser than all the other washed eggs, regardless of the time they were washed. While both 1A and 1B, not washed, had a bacteria count value of 3, the rest of the samples had values of above 6, except for 4B which had a value of 5. Using the RGB levels, the amount of yellow, which can also represent the amount of bacteria, have also shown the same results. 1A and 1B had 203 and 319 values respectively, while all the other samples had a value of 350 and above. Therefore, we are able to conclude that unwashed eggs will have a lesser amount of bacteria on the shells as compared to all the other eggs which were washed.


However, our second hypothesis - the longer we wash the eggs under running water, the greater the number of bacteria growing on the eggshells - is not able to be confirmed through our experiment. Both set A and B have different bacterial count and RGB values for some of the eggs with same amount of washing time. However, others did not have significant or obvious differences in number or size. For example, with regard to the ranking method, 4A and 4B were washed for the same amount of time, 50 seconds, but they had values of 9 and 5 respectively, which are very different bacterial count values. Whereas in the case of 3A and 3B, both washed for 20 seconds each, had equivalent values of 7. In the Set A of the RGB data, 3A was washed for a longer amount of time, yet had a smaller value than 2A, which was washed for a shorter amount of time. Therefore, we are not able to evaluate whether ‘the longer we wash the eggs under running water, the greater the number of bacteria growing on the eggshells’ is correct.


Hence, we assumed that as the amount of washing time increase, it does not vastly affect the increase in growth in bacteria. In any case, we can conclude that washing will increase the number of bacteria on eggs and in turn increase the chances of Salmonella Contamination.

4.4 Limitations and Areas for improvement
Throughout this experiment, one of the main difficulties we faced was in presenting our data. As we made an error in spreading, the bacteria growth was not even. Due to difficulty in presenting our data, plotting the graph was also a challenge. Despite that, we used our prior knowledge of ranking to complete one bar graph. To support our ranking, we decided to use another method which is the RGB scale. With this, we managed to present and analyse our data.


Secondly, there is a high chance that there may have been contamination. The lab and fridge where we stored the egg is shared by many people, hence there may be other bacteria. Also, the apparatus we used may not be entirely bacteria-free. Despite trying to limit the amount of bacteria on the apparatus by sterilizing the trays and keeping our gloves on throughout the duration of the experiment, contamination may still have occurred during washing or natural drying. We could have made the experiment more accurate by performing the experiment in a completely bacteria-free environment with thoroughly sterilized equipment. However, that is not possible in the school.

Thirdly, despite using the RGB scale in photoshop and ranking the bacteria ourselves, due to the lack of equipment, our results may not be entirely accurate. If we had done through online research before the experiment, we may have been able to order a bacterial counter depending on its price. A bacterial counter is able to count bacteria accurately with its own set of level indication. This may have made our results more accurate and precise.

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