Hello and welcome to this lesson from the unit Photosynthesis Factors Affecting the Rate.

I'm Mr. Jarvis, and I'm gonna be taking you through this lesson, which is evaluating our investigation into the effect of light intensity on the rate of photosynthesis in algae.

By the end of today's lesson, you should be able to evaluate and explain data from the investigation into the effect of light intensity on the rate of photosynthesis in algae.

There are five key words to today's lesson.

They're on the screen now.

They're accuracy, error, precision, repeatability and reproducibility.

The definitions are there for you to read, and you can pause the video at this point if you want some extra time to read through those definitions, rather than listening for them as we go through today's lesson.

Today's lesson is broken down into two parts.

First, we're going to interpret the data from the experiment, and then, in the second part of the lesson, we're going to evaluate the experiment.

So if you're ready, let's get started.

Photosynthesis happens in the cells of some algae and other producers when there's light.

And we can see in the diagram that light falls onto algae, and it's absorbed by chlorophyll within the green algal cells.

Light transfers the energy that's needed for the chemical reactions of photosynthesis to take place.

The reactants and products of photosynthesis are water and carbon dioxide, the reactants, the molecules that go into the reaction, and glucose, the food that's produced, and oxygen, which are the products of reaction.

The rate of a reaction is a measure of how much change occurs, for example, the pH change due to reactants being used, per unit of time.

The rate of photosynthesis depends on a number of limiting factors.

And a limiting factor is a condition that when in short supply slows down or limits the rate of a reaction.

Light intensity, the amount of light reaching a given surface in a period of time, is one of the main limiting factors of photosynthesis.

So bright light allows algae to photosynthesize at the fastest rate.

In low light conditions, when the light intensity is lower, such as in the evening, in the early morning or even at night, means that photosynthesis occurs much slower or even not at all.

Here's a check.

Which statement is an example of the rate of a reaction? A, how long a chemical reaction takes.

B, how much reactant is converted into product.

Or C, how much the pH changes per unit of time.

I'll pause for a few seconds, and then we'll check the answer.

The correct answer is C.

An example of the rate of a reaction is how much pH changes per unit of time.

Well done if you got that correct.

We used an indicator to measure the rate of photosynthesis in algae, and the indicator that we used was hydrogen carbonate indicator.

Hydrogen carbonate indicator at atmospheric concentrations of carbon oxide is cherry red.

That's pH 8.

4.

As photosynthesis takes place, carbon dioxide from the jar containing the indicator is used by the algae, and that makes the pH more alkaline, and the indicator turns purple.

When photosynthesis is slow, carbon dioxide increases, and this is because of cellular respiration in the algae.

So the amount of carbon dioxide increases in the bottle, and that makes the pH more acidic, and the indicator turns yellow.

As light intensity increases, the rate of photosynthesis increases too until the rate is limited by limiting factors.

And you can see on the graph, the point where other limiting factors slow down the rate of photosynthesis.

At night, there is no light, and photosynthesis doesn't take place.

So at zero light intensity, there is zero rate of photosynthesis, and that's indicated by the arrow on the graph at the moment.

So when there's no light, photosynthesis does not take place, but cellular respiration does.

And that means that carbon dioxide is being produced by the algae, and this means that the conditions within the bottle become more acidic because there's more carbon dioxide, and the indicator turns yellow.

As the rate of photosynthesis increases, then the carbon dioxide is used.

And so towards the top end of the graph, the indicator should have turned purple.

Reactions, including photosynthesis, take place more quickly at warmer temperatures.

Here's a check.

When is the rate of photosynthesis likely to be fastest? A, on a warm, bright, sunny day.

B, in the middle of the night.

C, on a cool day with lots of cloud cover.

Or D, on a bright but snowy day in winter.

I'll pause for a few seconds, and then we'll check your answer.

The correct answer is that the rate of photosynthesis is likely to be fastest on, A, a warm, bright, sunny day because the light intensity will be highest and it's warmer, and we know that reactions, including photosynthesis, take place more quickly when the temperature is higher.

Well done if you got that right.

Before carrying out the experiment, you made a hypothesis.

A hypothesis is an idea, for example, an idea about the outcome of an experiment that's based on observations and scientific understanding.

It should also suggest why the outcome will happen using your scientific understanding.

For example, as the light intensity increases, the rate of photosynthesis in algae will increase, as the light provides the energy needed for the chemical reactions of photosynthesis to take place.

We're going to analyse the data from the experiment and decide whether it increases or decreases our confidence in the hypothesis.

We've got a table of our results that have the start and the end pHs, the change in pH for each of the distances from the light source, and also those values for the control, which was the bijou bottle that we covered in kitchen foil so that no light could enter.

I've also added the class results to my table, and you can see that I've now got three repeats at each distance from the line source.

What are the results telling you that are in the pink box? You might want to pause the video at this point so that you can just have a look at the data and work out what the results are telling you.

So I've squashed my results table to just include those results that we highlighted on the previous slide.

And at 60 centimetres from the light source and the control, the pH of the indicator became more acidic.

That's indicated by the fact that there are negative numbers.

So it's gone from 8.

4 and it's dropped and become more acidic.

And this was because carbon dioxide must have been increasing in these samples.

So here was our starting pH, 8.

4, a cherry red colour, and it turned to a yellow colour.

The rate of photosynthesis in the control was zero due to being no light.

And the rate of photosynthesis at 60 centimetres was very slow indeed.

Carbon dioxide was produced by respiration more quickly than it was used by any photosynthesis that was occurring.

If we look at the results, we can calculate the mean change in pH.

To calculate the mean, we need to sum our samples and divide by the number of samples.

Let's do one as an example.

Let's choose the 20 centimetre distance.

We've got 0.

8 plus 0.

8 plus 0.

6, and that gives us a total of 2.

2.

There are three samples that we've got in our results table, so 2.

2 divided by three gives us the mean change in pH, and that's 0.

733.

We're going to add that to our table.

We can do this for the 30 centimetre reading, the 40 centimetre reading, the 50 centimetre reading and the 60 centimetre reading.

And we can also do it for the no light, which was the control.

The rate of reaction is equal to the change in pH per unit of time, and we can calculate this using the equation rate is equal to the change in pH divided by the time in hours.

The experiment that I undertook was 1.

5 hours or 90 minutes.

So here's our mean change in pH, which we calculated on the previous slide.

We're now going to calculate the rate, so let's use our 20 centimetre from the light source example.

We've got 0.

73 as our mean change in pH.

And we divide it by the time in hours, which is 1.

5.

So 0.

73 divided by 1.

5 gives us a rate, which is a pH change per hour of 0.

487.

We can again do the same calculation for our 30 centimetre, 40 centimetre, 50 centimetre and 60 and control readings.

The negative rate means that photosynthesis is very slow or not taking place, and they're indicated within the pink box in our results table.

We can plot the results on a graph.

I've got a summary table on the screen, which shows the distance from the light in centimetres and the rate of photosynthesis.

My graph needs to be plotted carefully.

The x-axis, the axis along the bottom of the graph, is the distance from the light source.

That's our independent variable.

It's the thing that we changed.

And you can see I've gone up in units of 10.

The y-axis, the axis along the side of the graph, is our dependent variable, the thing that we measured, and that was the rate of photosynthesis.

And again, you can see that I've gone up in equal steps along the axis.

We can then start to plot the data.

So 20 centimetres from the light source was a rate of 0.

49.

At 30, 0.

27.

40, 0.

09.

And 50, 0.

05.

We can then draw a line of best fit, and here is my best fit for my graph.

Here's a check.

Which graph is drawn correctly, and what's incorrect about the other graph? I'll pause for a few seconds, and then we'll check your answer.

The correct graph is B.

The incorrect graph is A, and here are the errors that you might have spotted.

I've got my independent variable, the distance from the light, along the y-axis, and that's wrong.

I've also got the dependent variable, the thing that I measured, the rate of photosynthesis, along the x-axis.

And again, that's wrong.

It should be on the y-axis.

And you can see on the scale on the x-axis, I've also not gone up in equal units.

And so I've got 0.

1, 0.

2, 0.

3, 0.

5, 0.

6.

Well done if you spotted those errors.

So that brings us to our first task of the lesson.

Using your data or the data provided, calculate the mean change in pH and the rate of photosynthesis in each algal bead sample.

Add these values to your results table.

Secondly, I'd like you to plot a graph of rate of photosynthesis in algae against the distance from the light.

Draw a line of best fit.

And your graph success criteria is that your axes are correctly plotted and labelled, your points are plotted accurately, there's a smooth line of best fit drawn and you've given the graph a title.

And finally, consider your hypothesis or use the exemplar hypothesis that was provided.

Do your results increase or decrease your confidence in that hypothesis? You'll need to pause the video to answer those questions and to plot your graph.

And then when you're ready, press play, and you can check to see how well you did.

First of all, I asked you to use the data to calculate the mean change in pH and the rate of photosynthesis for each algal bead sample, and to add that to your results table.

So your results should look something like this.

So we've got the mean change in pH and the rate added to the results table.

Then, I asked you to plot a graph of the rate of photosynthesis in algae against distance from the light, and then to draw a line of best fit.

And remember, your success criteria were that the axes were correctly plotted and labelled.

So I've got my independent variable along the x-axis.

That's the distance from the light.

I've got my dependent variable, the rate of photosynthesis, along the y-axis.

And I've gone up in equal steps along each of those scales.

I then plotted my points accurately.

I've drawn a line of best fit.

And then I've given the graph a title, How Light Intensity Affects the Rate of Photosynthesis in Algae.

Well done if you got that.

And finally, I asked you to consider your hypothesis.

Do your results increase or decrease your confidence in it? So your answer might have included that your results supported your hypothesis, and they increased your confidence in your hypothesis because the rate of photosynthesis increases as the algae are placed closer to the light source.

The closer to the light source, the higher the light intensity, that's the amount of light, that's reaching the algae in a given time.

As the algae are placed further away from the light source, the light intensity decreases and the rate of photosynthesis decreases too, and that's shown by the change in pH.

And light is needed to provide the energy required for the reactions of photosynthesis to take place.

When light intensity is higher, there's more energy provided and the reactions take place more quickly.

Well done if you included any of those points in your own answer.

That brings us to the second part of the lesson today, and now we're going to start looking at evaluating the experiment.

So if you're ready, let's move on.

Light intensity is the amount light reaching a given surface area in a period of time.

The closer the algae samples are to the light source, the higher the light intensity.

And as the distance increases, the light spreads out over a larger area.

So here's a graphic to illustrate this.

If we put our algal beads close to the light source, then the light intensity is high.

The light hasn't spread out over a very big area, and so it's more concentrated.

And we can see this in the diagram.

As we move the algal beads further away, the light has more chance to spread out, and so less of the light is being absorbed by the algae within the bijou bottle.

And then finally, as we move it further away, the light spreads out even further, which means that there's less light reaching a given surface in that period of time.

The graph shows that as the light intensity decreased, the rate of photosynthesis decreased too.

At high light intensity, there's a high rate.

At low light intensity, there's a much lower rate.

We know that light is needed to transfer energy for the reactions of photosynthesis to take place.

Here's a check.

Whose explanation of the effect of light intensity on the rate of photosynthesis is correct, and who is incorrect? Laura says, "As the light intensity increases, "the rate of photosynthesis increases.

"Light transfers the energy needed "for the reactions to take place." And Izzy says, "As light intensity increases, "the rate of photosynthesis increases.

"This is demonstrated by the indicator turning yellow." I'll pause while you think about which of the girls are correct in their explanations and which of the girls are incorrect.

Laura said, "As the light intensity increases, "the rate of photosynthesis increases.

"Light transfers the energy needed "for reactions to take place." That's correct, well done if you got that.

Izzy said, "As light intensity increases, "the rate of photosynthesis increases, "and this is demonstrated by the indicator turning yellow." That's incorrect.

She's right in that as light intensity increases, the rate of photosynthesis increases.

But she said that it's demonstrated by the indicator turning yellow.

As the algae are photosynthesizing, they're going to use up carbon dioxide, and that's going to increase the pH of the solution, and that's gonna turn the indicator purple, not yellow.

Well done if you spotted that error.

We can conclude that the rate of photosynthesis has increased as the light intensity increases, and we know this because the indicator turned more alkaline, more purple, the closer the algal beads were placed to the light source.

And we've got this within our diagram on the screen.

We measured the rate of photosynthesis by comparing the colour of each sample with an indicator chart.

The indicator chart helps us to measure the rate of photosynthesis using the change in pH with accuracy.

Accuracy is when measurements are close to the true value, and here we can see that we have some accuracy in our bijou bottle comparing to the chart because it matches the pH 8.

4.

All experiments have the potential to have errors.

An error is when a measurement is different to what it would otherwise be.

That's the true value.

Errors can be random, which is when the size of the error is different for each measurement.

So for example, not correctly matching the sample with the indicator chart, or placing the sample bottles in the shadow of other sample bottles during the experiment.

Measurements can be systematic errors.

This is when measurements differ from the true value by the same amount each time.

So for example, if the indicator started at a pH higher than 8.

4 for all of the samples at the start of the experiment.

An error is when a measurement is different to what it would otherwise be, the true value.

Here are my results from my experiment.

Do any of the results make you think that there'd been an error in this experiment? Can you spot any? What might have caused these results? I'll give you a few seconds to think about that.

The 30 centimetre reading, for example, might have had a random error.

It might be that the people measuring the rate of photosynthesis haven't actually matched the colour of the indicator closely or accurately enough to the indicator chart.

The control reading, which is minus 0.

2, is probably explained by the fact that the kitchen foil perhaps didn't cover the bijou bottle fully, and some light actually was able to enter into the indicator bottle, and the algae were able to photosynthesize a small amount.

What errors might have taken place in your experiment? Here's a check.

A pupil investigated light intensity in the photosynthesis in algae.

They measured the pH after one hour.

The change in pH at 10 centimetres from the light was 0.

8.

It was 0.

2 in the second experiment.

What might explain these results? Is it A, the pupil moved the algae closer to the light source in the second experiment.

Is it B, there was a systematic error caused by the pupil leaving the sample in front of the light for two hours in the second experiment.

Or is it C, there was a random error caused by mismatching the sample with the indicator chart.

I'll pause for a few seconds, and then we'll check your answer.

The lightly explanation of this scenario is C, that there was a random error caused by the mismatching of the sample with the indicator chart.

Well done if you got that right.

We can look at the precision of our results.

Precision is the spread of the results around the mean value.

If we look at our 30 centimetre results, we've got precise results.

They're very close, in fact, they match the mean value.

We've got a larger spread of results around the mean value when we look at our control results.

How precise were your results? When measurements are similar when using the same equipment and method, the experiment has what we call repeatability.

When the change in pH was measured, most results were similar or repeatable.

Although not the same, these results highlighted in pink were carried out using the same method, and they were repeatable.

They showed the same pattern in the results.

How repeatable were your results? Here's a check.

What's meant by the term repeatability? Is it A, using the same method to do an experiment over and over again? B, getting similar results each time you do an experiment using the same method.

Or C, repeating an experiment until you get the results that are the same.

I'll pause for a few seconds, and then we'll check the answer.

The correct answer is B, repeatability is getting similar results each time you do an experiment using the same method.

Well done if you got that.

By evaluating data, we can suggest ways that the experiment could be changed to improve the quality of data.

When an investigation is repeated by another person, or a different method or equipment is used and the same results are obtained, the experiment has what we call reproducibility.

How reproducible are your class results? The most reliable data comes from experiments that have repeatability and reproducibility.

Remember, repeatability is when you carry out the experiment using the same method, getting similar results each time.

And reproducibility is when someone else carries out the experiment using the same or a different method, and they get similar or the same results.

Here's a final check for today.

Lots of scientists carry out investigations into the rate of photosynthesis in plants.

The data from all of the experiments are similar.

This is an example of, A, accuracy, B, precision, C, repeatability, D, reproducibility.

I'll pause for a few seconds, and then we'll check the right answer.

The correct answer here is D, reproducibility.

They're using lots of different methods, but they're getting similar results, so results are reproducible.

Well done if you got that right.

You've investigate the effect of light intensity on the rate of photosynthesis in algae, and I'm now going to give you a task to do.

I'd like you to suggest how you might change the experiment to improve the accuracy, precision, reliability or reproducibility of the results.

You need to think about the equipment and the method that you used, and explain how each change will improve your results.

Pause the video, complete your answers.

And then when you're ready, press play and we'll check them.

So I asked you to suggest how you might change your experiment to improve the accuracy, precision, reliability or reproducibility of the results, and to explain how each change would improve your results.

So some suggestions that you might have included are use a colorimeter to measure the colour of each sample or use a pH probe to measure pH, which will improve the accuracy of the pH reading, and therefore the accuracy of the rate of photosynthesis.

You could place a temperature probe or a thermometer into each algal bead sample at the start and end of the experiment.

That will allow you to monitor the changes in temperature that would affect the rate of photosynthesis.

Or you could carry out the experiment in a dark room, with only the light source illuminating the samples.

That would ensure that the results have more accuracy as the algae will only be able to use the light to photosynthesize from the light source itself.

That brings us to the summary of today's lesson.

We've seen that the results show that the rate of photosynthesis is faster at higher light intensity.

This is because light is needed for chemical reactions of photosynthesis to take place.

We've considered the accuracy of the experiment through our analysis of the data that we produced.

Most results showed precision around the mean value.

Errors within the data can be identified.

They can be random errors, which are different each time, or systematic errors, when the measurements differ from the true value by the same amount each time.

And the results demonstrate repeatability, and the experiment has reproducibility.

I hope that you've enjoyed looking at your data and working out what it all means.

It's been great learning with you, and I look forward to seeing you sometime soon, bye-bye.