how to increase light intensity in photosynthesis experiment

The Biology Corner

Biology Teaching Resources

Photosynthesis Virtual Lab

This lab was created to replace the popular waterweed simulator which no longer functions because it is flash-based. In this virtual photosynthesis lab , students can manipulate the light intensity, light color, and distance from the light source.

A plant is shown in a beaker and test tube which bubbles to indicate the rate of photosynthesis. Students can measure the rate over time. There is an included data table for students to type into the simulator, but I prefer to give them their own handout ,

The handout is a paper version for students to write on as the work with the simulator. The document is made with google docs so that it can be shared with remote students.

There are several experiments that can be done in the lab that would complement this virtual experiment. For example, students can use elodea and measure the number of bubbles released when the plant is under a bright light. Algae beads can also be used to measure changes in pH as the plants consume carbon dioxide.

In experiment 2, students specifically look at light color to determine which wavelength of light increases the rate of photosynthesis. Students should discover that green light has a very slow rate. Their collected data is then compared to a graph of the absorption spectrum of light.

Shannan Muskopf

Practical Biology

A collection of experiments that demonstrate biological concepts and processes.

Observing earthworm locomotion

Practical Work for Learning

Published experiments

Investigating factors affecting the rate of photosynthesis, class practical.

In this experiment the rate of photosynthesis is measured by counting the number of bubbles rising from the cut end of a piece of Elodea or Cabomba .

Lesson organisation

The work could be carried out individually or in groups of up to 3 students (counter, timekeeper and scribe).

Apparatus and Chemicals

Students may choose to use:.

Thermometer, –10 °C –110°C

Coloured filters or light bulbs

Push-button counter

Potassium hydrogencarbonate powder or solution (Hazcard 95C describes this as low hazard)

For each group of students:

Student sheets, 1 per student

Beaker, 600 cm 3 , 1

Metre ruler, 1

Elodea ( Note 1 ) or other oxygenating pond plant ( Note 2 )

Electric lamp

Clamp stand with boss and clamp

Health & Safety and Technical notes

Normal laboratory safety procedures should be followed. There is a slight risk of infection from pond water, so take sensible hygiene precautions, cover cuts and wash hands thoroughly after the work is complete.

Read our standard health & safety guidance

1 Elodea can be stored in a fish tank on a windowsill, in the laboratory or prep room. However it is probably a good idea to replace it every so often with a fresh supply from an aquarist centre or a pond. (It’s worth finding out if any colleague has a pond.) On the day of the experiment, cut 10 cm lengths of Elodea , put a paper-clip on one end to weigh them down and place in a boiling tube of water in a boiling tube rack, near a high intensity lamp, such as a halogen lamp or a fluorescent striplight. Check the Elodea to see if it is bubbling. Sometimes cutting 2–3 mm off the end of the Elodea will induce bubbling from the cut end or change the size of the bubbles being produced.

2 Cabomba (available from pet shops or suppliers of aquaria – used as an oxygenator in tropical fish tanks) can be used as an alternative to Elodea , and some people find it produces more bubbles. It does, though tend to break apart very easily, and fish may eat it very quickly.

3 If possible, provide cardboard to allow students to shield their experiment from other lights in the room.

Ethical issues

Look out for small aquatic invertebrates attached to the pond weed used, and remove them to a pond or aquarium.

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Lab Answers: How Does Light Intensity Affect the Rate of Photosynthesis

• Lab Answers: How Does Light…

Photosynthesis represented by the equation 6H 2 O + 6CO 2 → C 6 H 12 O 6 + 6O 2 is one of the most crucial chemical reactions on earth as it produces O 2 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 bubbles and can be 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 light source (Maximum Yield, 2016). The rate of photosynthesis is a function of light intensity.

The aquatic plant elodea, also known as anacharis, provides a habitat for small 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 rate (Asta, n.d.) It also is an excellent oxygen producer.

The rate of photosynthesis in Elodea depends on the intensity of light. With increasing, water pollution levels light that reaches aquatic plants such as Elodea significantly decreases thus leading to lesser light intensity underwater (Denchak, 2018).

Light is an important factor in photosynthesis, “how does a decreased light intensity impact photosynthetic rate of Elodea” is an important contemporary ecological question to be considered. 

Research Question

How does decreasing light intensity affect the rate of photosynthesis in an elodea plant under a fixed period of 2 minutes?

Original Experiment 

The research methodology used to study the above 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 light onto a large beaker filled with tap water with an elodea plant placed in it. 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 plant.

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 increase reliability, all other variables were controlled as per the original experiment.

Refined by:

Three trials from each sample will be taken to ensure sufficient data is available statistical analysis.

Leaves per elodea plant will be limited to 10 to ensure fairness in the data.

A vacuum will be created using a flask and a test tube (Appendix 1) on top of the water to ensure bubbles 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.

  Safety and ethical considerations

Processed data.

Data obtained was analysed using the following statistical methods to allow appropriate interpretation of the data of the data:

The mean was chosen as the most appropriate measure of central tendency.

Standard deviation was calculated as a measure of central tendency and used to calculate standard error.

Standard error was chosen as a measure of uncertainty.

A confidence interval was chosen as a measure of validity.

Interpretation : The data shows that the average number of bubbles 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 low standard error suggests that the results collected are close to the population mean and indicates the reliability of the mean.

The Standard deviation values obtained (0.68, 1, 0.68, 1 and 0.68 respectively) are close to zero indicating that the data is close to the expected mean of the dataset (John, 2009). The low standard error and standard deviation of the data may suggest higher precision during data collection and therefore the sample represents the accepted values (McHugh, n.d.).

Analysis – – The standard deviation 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 true mean. The standard deviation of 1 for 20cm and 40cm systems suggest that the data is more dispersed away from the mean 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 average number of bubbles produced vs distance (Figure A) demonstrates a linear pattern with a very strong negative correlation as demonstrated by the R 2 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 light intensity had a negative impact on the number of bubbles produced. According to Reckitt Benckiser (2016), as light intensity decreases the rate of photosynthesis also decreases in an almost linear pattern. As the rate of photosynthesis is indicated by the number of bubbles produced the data collected fits this literature.

Analysis – As shown in figure A, the error bars are less spread out and they do not overlap at all. This suggests that results collected are all statistically significant and do not fall in the same range as each other indicating that there was a negative impact on rate of photosynthesis since the start of the experiment. According to Figure 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±1.4, 14±2.5, 10±1.4, 6±2.5, 2±1.4 from 10cm to 50cm respectively. Although very close, the error bars (confidence intervals) do not overlap until 30cm. However, as the overlaps in 30cm, 40cm and 50cm error bars are not extensive and therefore indicates that there is a statistical difference between all the means.

Limitations of Evidence

Standard error, error bars and confidence intervals are all examples of the uncertainty and limitations observed from analysis of the evidence. This can be explained by a lack of reliability and validity in the experimental process as well as the statistical sampling error. 

The standard error (Table C) indicates that how far the sample mean of the data is likely from the true population mean. 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 as some were trapped beneath leaves and some bubbles were too small to be observed by the naked eye), and the resultant errors associate with the average number of bubbles produced and statistical parameters based on that data increases the standard error.

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 factor in determining the length of the confidence 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

Most appropriate equipment to collect data were not used which may contribute to the data being inaccurate i.e. the ruler used to measure the distance between 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 above (Appendix 1) and only bubbles visible to the naked eye were counted which may affect both accuracy and precision of the experiment.

Elodea samples were not genetically screened. Therefore, random biological variation might exist within the sample. This could explain some of the remaining imprecision in the data.

Diminishing carbon dioxide, temperature variation and the time elodea plant takes to acclimatise to changed intensity of light can potentially affect the rate of photosynthesis.

The experiment was conducted in a standard classroom with opened doors and windows while students often walked past the experiment. These could have impacted the intensity of light for the experiment.

Affecting validity

The amount of CO 2 in water was not pre-determined. With photosynthesis continuing the supply of carbon dioxide is rapidly used up. Hence there is the possibility that the decreased number of bubbles is a function of this.

Limiting leaves to 10 does not directly determine 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 process would improve its reliability. In this experiment, the reliability of the data could be improved by increasing the number of trials more than once to decrease standard error due to ‘regression to the mean’ (Schnell, 2006).

To maintain the supply of carbon dioxide a compound such as sodium hydrogen carbonate can be added to the water (Benckiser, 2016).

Measure distance with a ruler equipped with a precise digital LED digital display to increase accuracy.

Light sources of different intensities should be used as this would reduce random errors. Also, the accuracy of data could be improved by using a hemocytometer to directly quantify the number of Elodea cells. (Fuentes, n.d.)

Conduct the experiment in a dark room with minimal exposure to outside factors such as open door and windows to ensure the only source of light is the lamp. 

Suggested extensions 

Redirect the experiment by using varying light intensities and determine the optimum light intensity for the maximum rate of photosynthesis.

Extend the experiment by investigating the effect of light intensity of various species of Elodea or different plants all together.

In conclusion, the evidence suggests that decreasing light intensity reduces the rate of photosynthesis in a 2-minute fixed growth period. Therefore, more pollution levels mean aquatic plants (such as Elodea) are not able to photosynthesis as well impacting the level of oxygen underwater. However, there are noted limitations in the experimental procedure such as small sample size and further statistical analysis would be required to support this conclusion.  

Bibliography

Aquatic Biologists. (2007, 09 24). Elodea (Canadian Water Weed) . Retrieved from Aquatic Biologists: https://www.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://www.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). Water Pollution: Everything You Need to Know. Retrieved from Natural Resources Defense Council: https://www.nrdc.org/stories/water-pollution-everything-you-need-know

Fuentes, M. (n.d.). Cell counting equipment essentials . Retrieved from hemocytometer.org: https://www.hemocytometer.org/starter-kit/

John, T. S. (Director). (2009). Interpreting the standard deviation [Motion Picture].

Lumen. (n.d.). Describing Variability . Retrieved from Lumen: https://courses.lumenlearning.com/boundless-statistics/chapter/describing-variability/

Maximum Yield. (2016, 04 15). Light Intensity . Retrieved from Maximum Yield: https://www.maximumyield.com/definition/2036/light-intensity

McHugh, M. L. (n.d.). Standard error: meaning and interpretation . Retrieved from Biochemia Medica: https://www.biochemia-medica.com/en/journal/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 15). What Is Photosynthesis? Retrieved from Live Science : https://www.livescience.com/51720-photosynthesis.html

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