Which Color Filters Do You Expect Will Yield The Greatest Rate Of Photosynthesis?
Rationale
Photosynthesis represented past the equation 6H2O + 6CO2 → CviH12O6 + 6Otwo is i of the nigh crucial chemical reactions on earth equally it produces Otwo molecules– a gas vital to the survival of many organisms (Vidyasagar, 2018) This process takes place during the light dependent phase of photosynthesis and is indicated by the production of bubbling and can exist used to analyse the rate of photosynthesis (Benckiser, 2016).
Light intensity refers to the strength or amount of light produced and is the measure of the wavelength-weighted power emitted by a low-cal source (Maximum Yield, 2016). The charge per unit of photosynthesis is a function of calorie-free intensity.
The aquatic plant elodea, likewise known as anacharis, provides a habitat for small-scale aquatic animals and is used frequently by fish to protect recently hatched fish (Aquatic Biologists, 2007). Elodea is very common throughout the world, particularly Oceania, and has a rapid growth charge per unit (Asta, due north.d.) It also is an first-class oxygen producer.
The rate of photosynthesis in Elodea depends on the intensity of low-cal. With increasing, water pollution levels lite that reaches aquatic plants such as Elodea significantly decreases thus leading to bottom light intensity underwater (Denchak, 2018).
Light is an of import cistron in photosynthesis, "how does a decreased light intensity affect photosynthetic charge per unit of Elodea" is an important gimmicky ecological question to be considered.
Enquiry Question
How does decreasing low-cal intensity touch on the rate of photosynthesis in an elodea plant under a fixed period of 2 minutes?
Original Experiment
The research methodology used to written report the in a higher place question was adapted from:
BBC Bitesize- Investigating the rate of photosynthesis, https://www.bbc.com/bitesize/guides/zpwmxnb/revision/4
The original experiment shined a calorie-free onto a large beaker filled with tap water with an elodea plant placed in information technology. The experiment started with placing the light 10cm away from the beaker and increased the distance by 10cm until 50cm, to decrease the light intensity at the elodea institute.
Modifications to the Methodology
To ensure that sufficient and relevant data was collected the original experiment was modified to increase the number of trials, as the original experiment only had one trial. The reliability of the data collected was improved by modifying the original methodology (see refinements). To minimize error and increment reliability, all other variables were controlled equally per the original experiment.
Refined by:
Three trials from each sample volition be taken to ensure sufficient data is available statistical analysis.
Leaves per elodea institute volition be express to ten to ensure fairness in the information.
A vacuum volition exist created using a flask and a test tube (Appendix i) on top of the water to ensure bubbling produced directly moved upwards in the test tube increasing the accuracy and confidence in the data.
All elodea samples were randomly chosen from a fish tank to reduce the sample bias.
Prophylactic and upstanding considerations
Table A – Potential risks and their solutions
| Risk | Solution |
| Use of frail glassware | Go along all glassware away from ledges and breakages were cleaned upward immediately |
| Utilize of water and electrical appliances | Wipe hands before treatment electrical appliances |
| Hazard of allergy to elodea plants | Use gloves when handling Elodea |
Processed data
Data obtained was analysed using the following statistical methods to allow appropriate interpretation of the data of the information:
The mean was chosen as the nearly appropriate mensurate of central trend.
Standard deviation was calculated every bit a measure out of central tendency and used to summate standard error.
Standard error was called equally a measure of uncertainty.
A confidence interval was called as a mensurate of validity.
Table B – Statistical Calculations for 10cm arrangement
Tabular array C – Processed data table for the outcome low-cal intensity on rate of photosynthesis.
| Trial Number | Calculations (Below represents distance from the light source) | ||||
| 10cm | 20cm | 30cm | 40cm | 50cm | |
| Trial1 (no. of bubbles produced) | 18 | xv | 10 | 6 | 3 |
| Trial two (no. of bubbling produced) | 19 | 13 | 10 | 7 | two |
| Trial 3 (no. of bubbles produced) | eighteen | 14 | 9 | 5 | ii |
| Sample Size | three | 3 | 3 | 3 | iii |
| Average number of bubbles produced | 18 | 14 | ten | 6 | 2 |
| Standard Deviation | 0.68 | 1 | 0.68 | 1 | 0.68 |
| Standard Error (SE) | 0.33 | 0.68 | 0.33 | 0.68 | 0.33 |
| Confidence Interval | ane.4 | 2.5 | 1.4 | 2.five | 1.4 |
Interpretation: The data shows that the average number of bubbling produced are in between the ranges of 18±0.33, 14±0.68, 10±0.33, 6±0.68 and 2±0.33 respectively from 10cm to 50cm. The standard error has been used as a measure of the uncertainty associated with these averages (±SE). The depression standard fault suggests that the results collected are shut to the population mean and indicates the reliability of the mean.
The Standard deviation values obtained (0.68, 1, 0.68, i and 0.68 respectively) are close to zilch indicating that the data is close to the expected mean of the dataset (John, 2009). The low standard error and standard difference of the information may propose higher precision during data collection and therefore the sample represents the accepted values (McHugh, n.d.).
Analysis– – The standard departure of 0.68 obtained from the data for 10cm, 30cm and 50cm systems show that data is closely clustered around the mean suggesting that the data is closer to the truthful hateful. The standard deviation of i for 20cm and 40cm systems propose that the data is more dispersed away from the hateful relative to that of 10cm, 30cm and 50cm systems. This may be attributed to experimental error as well as natural variations in the samples such as size of the leaves (John, 2009).
Interpretation –The graph of boilerplate number of bubbles produced vs distance (Figure A) demonstrates a linear pattern with a very strong negative correlation as demonstrated by the R2 value of 0.9981. Figure A also shows that from 10cm to 50cm, the mean number of bubbles produced (y-variable) appears to decrease in exact decrements of 4. As light intensity decreases with the distance, these observations suggest that decreasing low-cal intensity had a negative bear on on the number of bubbles produced. According to Reckitt Benckiser (2016), every bit low-cal intensity decreases the charge per unit of photosynthesis likewise decreases in an almost linear design. As the rate of photosynthesis is indicated past the number of bubbling produced the data collected fits this literature.
Analysis – As shown in figure A, the mistake bars are less spread out and they do non overlap at all. This suggests that results collected are all statistically significant and do not fall in the aforementioned range as each other indicating that there was a negative bear on on rate of photosynthesis since the start of the experiment. Co-ordinate to Effigy A, the error bars for 20cm and 50cm systems slightly larger (0.68) relative to that of 10cm, 30cm and 50cm systems (0.33) which may suggest the variability of the plotted data may be less precise then the other measurements.
Analysis – The data indicates, with 95% confidence, that the sample means falls within the
ranges of 18±i.four, xiv±2.five, x±one.4, vi±2.5, two±1.4 from 10cm to 50cm respectively. Although very close, the fault bars (confidence intervals) do non overlap until 30cm. However, equally the overlaps in 30cm, 40cm and 50cm error bars are not all-encompassing and therefore indicates that there is a statistical difference between all the ways.
Evaluation
Limitations of Evidence
Standard mistake, error bars and confidence intervals are all examples of the uncertainty and limitations observed from analysis of the evidence. This can exist explained by a lack of reliability and validity in the experimental process besides equally the statistical sampling fault.
The standard error (Table C) indicates that how far the sample mean of the data is likely from the true population hateful. The natural variation within the population and the sample size cause this error. Moreover, the bubble counting error (not all bubbles in every sample were counted every bit some were trapped below leaves and some bubbles were too pocket-sized to be observed by the naked middle), and the resultant errors associate with the boilerplate number of bubbling produced and statistical parameters based on that information increases the standard mistake.
This, in conjunction with the high standard deviation (Table C) suggests that not all variables were fully controlled and indicates low precision in the measuring devices or high random biological variation in the samples.
The small sample size of this experiment is a major cistron in determining the length of the conviction intervals (Figure 2). Consequently, the evidence is limited in its ability to be used to extrapolate the findings of the experiment to the population of elodea.
Sources of Error
About appropriate equipment to collect information were non used which may contribute to the data beingness inaccurate i.e. the ruler used to measure the altitude betwixt the beaker and lamp was imprecise (±0.5mm).
Human and parallax errors contribute to imprecision in the experiment I.e. the distance had approximated to a certain extent when marking it on paper and when assessing distance from to a higher place (Appendix ane) and simply bubbles visible to the naked eye were counted which may touch both accuracy and precision of the experiment.
Elodea samples were non genetically screened. Therefore, random biological variation might be within the sample. This could explain some of the remaining imprecision in the data.
Diminishing carbon dioxide, temperature variation and the fourth dimension elodea plant takes to acclimatise to changed intensity of low-cal can potentially impact the charge per unit of photosynthesis.
The experiment was conducted in a standard classroom with opened doors and windows while students often walked by the experiment. These could take impacted the intensity of light for the experiment.
Affecting validity
The corporeality of CO2 in water was non pre-determined. With photosynthesis standing the supply of carbon dioxide is rapidly used up. Hence at that place is the possibility that the decreased number of bubbles is a function of this.
Limiting leaves to 10 does not directly make up one's mind the number of elodea cells which may affect the rate of photosynthesis.
Suggested improvements and extensions
Suggested improvements
Reducing the random error in the experimental procedure would meliorate its reliability. In this experiment, the reliability of the data could be improved by increasing the number of trials more once to subtract standard fault due to 'regression to the mean' (Schnell, 2006).
To maintain the supply of carbon dioxide a compound such every bit sodium hydrogen carbonate can be added to the water (Benckiser, 2016).
Mensurate altitude with a ruler equipped with a precise digital LED digital display to increase accuracy.
Light sources of different intensities should be used every bit this would reduce random errors. Besides, the accurateness of data could exist improved by using a hemocytometer to straight quantify the number of Elodea cells. (Fuentes, n.d.)
Conduct the experiment in a dark room with minimal exposure to exterior factors such as open door and windows to ensure the only source of calorie-free is the lamp.
Suggested extensions
Redirect the experiment by using varying light intensities and determine the optimum light intensity for the maximum charge per unit of photosynthesis.
Extend the experiment past investigating the issue of lite intensity of diverse species of Elodea or unlike plants all together.
Conclusion
In decision, the bear witness suggests that decreasing light intensity reduces the charge per unit of photosynthesis in a 2-minute fixed growth menstruum. Therefore, more pollution levels mean aquatic plants (such every bit Elodea) are non able to photosynthesis every bit well impacting the level of oxygen underwater. All the same, there are noted limitations in the experimental procedure such as pocket-sized sample size and further statistical analysis would be required to back up this decision.
Bibliography
Aquatic Biologists. (2007, 09 24). Elodea (Canadian H2o Weed). Retrieved from Aquatic Biologists: https://world wide web.aquaticbiologists.com/elodea-canadian-water-weed/
Asta, J. (n.d.). Rate of Growth of Elodea. Retrieved from eHow: https://www.ehow.com/info_10061234_rate-growth-elodea.html
BBC Bitesize. (n.d.). Photosynthesis. Retrieved from BBC Bitesize: https://world wide web.bbc.com/bitesize/guides/zpwmxnb/revision/4
Benckiser, R. (2016). Rate of photosynthesis: limiting factors. Rate of photosynthesis: limiting factors, 2.
Denchak, M. (2018, 05 14). H2o Pollution: Everything You Need to Know. Retrieved from Natural Resources Defence Quango: https://www.nrdc.org/stories/water-pollution-everything-you-need-know
Fuentes, M. (due north.d.). Jail cell counting equipment essentials. Retrieved from hemocytometer.org: https://www.hemocytometer.org/starter-kit/
John, T. S. (Director). (2009). Interpreting the standard deviation [Motion Film].
Lumen. (north.d.). Describing Variability. Retrieved from Lumen: https://courses.lumenlearning.com/boundless-statistics/chapter/describing-variability/
Maximum Yield. (2016, 04 15). Lite Intensity . Retrieved from Maximum Yield: https://www.maximumyield.com/definition/2036/low-cal-intensity
McHugh, M. Fifty. (n.d.). Standard mistake: significant and estimation. Retrieved from Biochemia Medica: https://www.biochemia-medica.com/en/periodical/18/1/10.11613/BM.2008.002
Schnell, A. (2006, April 23). What Is Regression to the Mean? Retrieved from Analysis Factor: https://www.theanalysisfactor.com/what-is-regression-to-the-mean/
Vidyasagar, A. (2018, October fifteen). What Is Photosynthesis? Retrieved from Live Science : https://www.livescience.com/51720-photosynthesis.html
Which Color Filters Do You Expect Will Yield The Greatest Rate Of Photosynthesis?,
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