Lab 7, exercise 3, the effect of temperature on the rate of aerobic respiration. To set up this experiment, what we're going to do is we are going to take a respiring organism and subject it to three different temperatures to see how those temperatures influence how quickly respiration happens. In this experiment, the subject that we're going to be utilizing, so the living thing undergoing respiration, are going to be germinated peas. Okay, so... Obviously these are plants and I kind of like that we're using this to illustrate that plants undergo cellular respiration too.
A lot of people have this misnomer that only animals undergo cellular respiration and that just isn't correct. Plants have to as well. So we have our peas that are going to be respiring. They're all going to be undergoing respiration.
The question is how fast? So how fast is respiration going to occur? in these different temperatures. That's what we're going to try to answer so that we can figure out how temperature influences the rate of respiration.
Now we need a way of telling how much respiration has happened at different time intervals so that we can establish respiration rate. As with the other two experiments that we've done in this lab, we are going to measure the amount of CO2 as a way of indirectly telling us the amount of respiration. As with the other experiments, the more CO2 is produced within a given time frame, that's an indication that there is an increase in respiration. And if you are taking measurements over time, that can allow you to establish rate.
The thing that's been changing from exercise to exercise, they've all utilized this concept. The thing that's changed is how do we measure this? The way that we've measured CO2 has changed from one exercise to the next.
The nice thing is that this particular exercise is probably the most straightforward in terms of carbon dioxide measurement. We're not looking at displacement, we're not changing the color of anything. We literally have a device, a monitor, that measures the concentration of CO2.
This is going to tell us the concentration of CO2 in parts per million. Parts per million is a unit when you're measuring the concentration of a gas. So we're going to take some living germinated peas. We're going to put them into an enclosed container so that gases can't go in or out.
We're going to put this monitor in with the peas so that it can measure the amount of CO2 produced by the peas. And then we're going to place the different containers at different temperatures. One of them will be placed on ice.
One of them will be left out at room temperature, so this one is literally just going to be sitting on a desk with nothing else influencing it, so that it can just be room temp, which should be about 24 degrees Celsius. And this one is going to be put on a hot plate, or an incubator rather, so I'll put some flames here. It's going to be a little bit warmer, not too incredibly warm. much warmer than the other two temperatures.
And then we're going to look at how the CO2 outputs are changing over time and we'll go ahead and graph those as a way. Alright here we have the setup for exercise 3 with the pea fermentation. So again remember kind of from our intro that what we're doing here is that we are subjecting peas which are our live organism to different temperatures and looking at how those different temperatures influence their rate of...
respiration. As with the last two exercises, the way that we are measuring how quickly cellular respiration is occurring is by looking at the CO2 output. And the idea is that if the respiration is happening faster, the CO2 output will raise quicker over time periods. Now the way that we're going to measure CO2 output in this particular experiment is more intuitive than the last two.
We're not looking at displacement and we're not looking at how long it takes to change a liquid color. Instead, we are literally using a probe that is designed to measure carbon dioxide concentration in the air. And what we're doing is we are utilizing those same monitors that we've been using all semester, those Vernier monitors. We have the probes. plugged into them and as they read the CO2 in the air, they're going to read that and it's gonna show up on the monitor here.
Now here's the setup we have for the peas. We have a jar of peas that are alive and germinated so they are respiring and giving off CO2 as they respire and we've subjected them to different temperatures and they've been sitting at these temperatures for a while so they they're acclimated to their given temperature. So these peas right here are at 45 degrees Celsius. This is a little bit warmer than your internal body temperature so we're looking at 100 some degrees Fahrenheit.
These peas are on ice so they are our zero degrees Celsius temperature and then these peas right here are at about 24 degrees Celsius which is roughly room temperature um depending on the day in this particular room as you all know it's pretty fluctuates a lot. Alright, and we have the monitor that we're going to be putting in during the duration of the experiment and the readings will show up on this screen. So here's kind of how it's ordered on the screen.
This top box which is red corresponds with the degrees Celsius, so just think red for the hottest temperature. The middle box is there to represent the coldest temperature, zero degrees, blue for cold. And then our intermediate, the 24 room temperature, is this green box right here in between blue and, well, in between temperatures.
Okay, so first things first, before we put the probe into the various beakers and start recording the CO2 change over time, we first need to establish a baseline. CO2 reading. What the baseline CO2 reading is, it's what the machine is reading when the probes are sitting on the desk not being subjected to any piece. It's essentially telling us what it's reading as its default just based on atmospheric air.
All three probes for the temperatures that we're going to use right now are just sitting on the desk. They're not doing anything else, they're not in any different environment, they're all exposed to the same air. and in theory should be exposed to the exact same concentration of CO2.
There's no reason why the concentration of CO2 is any different on this portion of the table than it is less than a foot away on the table. So if these machines were perfectly calibrated and precise, they would all be reading the exact same CO2 concentration in the atmosphere. The problem is they're not. The machines are not all perfectly calibrated. and they do not have a high precision level between each other.
Each reading from each meter is precise, but the reading between machines is not. For instance, just to give you an idea, look at the monitor. They're all exposed to the exact same concentration of CO2 in the air, but they are not all reading the same numbers.
This shows the inaccuracy from one machine to the next, and this is why we need to take the baseline readings. If you look, the cold temperature already has a high... higher CO2 output at the same concentration as the others. Over time, as it increases because of cellular respiration, it's going to have sort of an arbitrarily higher value than it should relative to the others because it started out higher. And at the end, it might make it appear that those peas are undergoing more respiration when in fact it's just because they were already higher to start off with due to the machine they were assigned.
By taking a baseline reading, we can look at the difference in the CO2. outputs from where it started to where it's at after the five minute time periods and by looking at the difference we can sort of eliminate any of the machine error. Now with that explanation in mind here is your fourth in-class participation question. Why is it important for us to take baseline readings when comparing results between the different temperatures? Your fourth in-class participation question is this.
Why is it important for us to take and consider baseline readings? when looking at results across different temperatures. The very first thing we're going to do is record these baseline readings in your book in your lab manual. So 118, about 401, and about 269. So we're going to go ahead and we are going to go to the table that you have in your book and write down those recordings. So the baseline reading was about 218, sorry 218 for the warmest temperature.
It is about 398 for the coldest temperature and about 268 for the intermediate temperature. And the units for these readings are parts per million. Parts per million is a way of expressing the concentration of a gas. Now if you notice, the tables give us a space for the CO2 reading at time zero for each one of the temperatures in the table off to the right. we're going to assume that the reading at time zero is the same as the baseline reading.
So for instance, it's going to be 398 for this cold temperature and the difference is going to be zero. They haven't been subjected to their temperatures yet, so we're assuming that they haven't changed from baseline. And the same will be true for the other temperatures as well.
Every time we take a recording, we are going to record it in the CO2 level column. And then we are going to calculate how much it's changed from baseline. Ultimately, we will be graphing and considering the differences from baseline when we are looking at our results.
What we're going to do now is we are going to start a five-minute timer, and we will come back together in five minutes to look at where the CO2 levels are for each one of the peas. But before we start that timer, let's go ahead and make sure that the meters are in their respective treatments. So we're going to put this probe into the room temperature. We're going to put this probe into the zero degree temperature.
And we're going to put this probe into the 45 degree temperature. Dr. Reed, go ahead and start the timer. And we will come back in five minutes to look at how the results have changed and record it in our table. Folks, we are now at the five minute time period.
So we're going to go ahead and write down the results. Here's what they look like on the screen. I am going to toggle off to our tables so that we can write them down and calculate the differences.
All right, so for the zero degrees after. five minutes, the reading was 1069. So we need to take 1069 minus baseline of 398, and the difference is 671. So that's how much it's increased in the last five minutes from where it started. For the 24 degrees after five minutes, the reading is 1170. So we need to take 1170 and subtract 268, and the answer is 902. So it's increased 902 parts per million.
And then finally, the 40 degrees Celsius is currently at 1312 on the meter. So we need to take 1312 minus 218, and it has increased by 1094 parts per million. All right. We'll see you back in five more minutes for the 10-minute reading. All right, folks, we are back with our 10-minute reading.
So that's what the screen looks like. I'm going to go ahead and toggle to our table and start writing down results. As you can notice, they are going up.
So we're going to start with the zero degree temperature first. It is currently at 1138. So we're going to take 1138 and subtract 398. So it has now gone up 740 parts per million. Our 24 degree temperature is currently at 1590. So we'll take 1590 minus 268. It has gone up 1,322 parts per million since we started the experiment in the last 10 minutes. And then for the 40 degree temperature, it is currently at 22. 9.3.
So we're going to take 2,293 minus 2,18. It has gone up 2,075 parts per million in the last 10 minutes. We will tune back in at the 15 minute time period. All right folks, we are back with the 15 time minute readings. This is what the screen currently looks like.
Let's go to our table and record the results. For the zero degree temperature, the reading is currently 1210. So we'll take 1210 minus 398, giving us an increase of 812 parts per million. The 24 degree temperature treatment is at 1,964.
So we're going to take 1,964 and subtract 268 to give us an increase of 1,696. Finally, the current reading for the highest temperature is at 3,044. So we're going to take 3,044 and subtract 218. which is going to give us a current increase of 2,826 parts per million. See you in five more minutes for the 20-minute reading.
Hi, folks. We are back with the Time 20 reading. Here's what the screen currently looks like. Let's toggle over to our table to record our results.
For the zero degree temperature, the reading is currently at 1, 2, 8, 4. So we're going to take 1, 2, 8, 4 and subtract 398, which is going to give us an increase of 886 parts per million. The 24 degree temperature is currently at 2, 3, 7, 0. So we're going to take 2, 3, 7, 0 and subtract 268 to give us an increase of 2,102 parts per million. at 3917 so we'll take 3917 and subtract 218 to give us an overall increase of 3699 parts per million.
Now let's talk about what we're going to do with this data and how we're going to portray it into a graph. We have all of our results recorded from the monitor over the 20 minute time period. And to kind of make sense of the data, we're going to probably want to illustrate it in some sort of graph. So looking at what we have here, it depends on what we want to display, the type of graph that we make. One thing that we're interested in looking at is how the CO2 levels change over the 20 minute time period at the different temperatures.
We want to see the rate of CO2 increase between one temperature to the next because that's going to tell us the rate of respiration. If we want to show that rate in change of the CO2 over time, that's going to be best illustrated in a line graph. So let's kind of walk through how we might set that up and I'll sort of draw the trends, but I'm not going to graph every individual number exactly from the previous page. So if we were going to set up a line graph with the information on the previous slide, The first thing we'd want to do is put time on the x-axis and include the units of time, so minutes.
Okay, this is our x-axis. Then on the y-axis, we put the thing that we were measuring throughout the experiment, which was the increase in CO2 level. And we have to also include units here.
The units were read as parts per million. Alright. It's always important to include a title on your graph, so we might say something to the effect of the effect or the influence maybe of What was the thing that we were manipulating in this experiment? The thing that changed was temperature.
So we're looking at the effect of temperature on the Technically speaking, we are measuring CO2, but we're only measuring CO2 because it tells us about respiration, which is what we're really interested in this experiment. So rather than list what was directly measured, I'm going to list what the indirect indication was of that. On the rate of cellular respiration, And it's always good to include what your subjects were that were being tested on the rate of cellular respiration in P's. And it can also be helpful to include the time frame. So I'll say over 20 minutes.
All right. That's a pretty descriptive title. I think that someone who read that would understand what we did, even if they didn't get to read all of the background of the experiment. Okay.
So then what I would do is I would put graduations along one axis that would show my different time frames. So it was every five minutes. So I would go ahead and put those down here and then along this axis I would put my graduations for the parts per million.
It's got to go all the way up to like 3,600 something. Okay again I'm not going to graph the numbers perfectly. I'm going to graph the trends.
If you want, in your book, you guys can go and look at all of those numbers and pick each point individually. Now we have three different temperatures, right? We have 0, 24, and 40. To indicate which line goes with which temperature, we're going to need a key so that our reader knows what they're looking at. So let's use blue for 0 degrees, since blue often indicates cold. And over the time frame, it increased the slowest, right?
So I'm just going to kind of draw a gradual slope. because it did go up as the plants were, the pea plants were respiring, but it didn't go up as quickly as the other temperatures. Basically what we saw is that as temperature increased, there was an increased rate in CO2 output over the 20 minute time period.
So we might expect something that looks like this. Continued to go up. if we want to extend the lines. Okay, so based on this information, our conclusion would be that an increase in temperature results in an increased CO2 output rate, which is indirectly telling us the rate of respiration.
So we would say then that is indicating that there is an increased rate of cellular respiration. in the peas. And if we think about what we learned in previous labs, this should make sense.
When we talked about the motion of molecules, we said that if you increase the temperature of a system, everything in that, molecularly speaking, goes faster. Temperature is telling you how much kinetic energy something possesses, which is what influences how fast the molecules in that substance move. So if we're increasing the temperature, things are moving quicker, which means the reactants can reach each other faster, and the whole reaction can happen faster as a whole. This isn't just true of cellular respiration, this is true of other types of reactions as well. For instance, if you increase temperature, the rate of photosynthesis would happen faster as well.
Now here's a question that I kind of want to talk about. Would this continue... indefinitely for different temperatures.
Like for instance, if we put something in 100 degrees Celsius, that's really hot. 40 degrees is like 100 degrees Fahrenheit, so 100 degrees Celsius would be pretty toasty. Would we see something like this? The answer is no.
The question is, why? Okay, why wouldn't we see an increase over the entire time frame as we increase temperature? There's got to be a reason why, and there is a reason, and it has to do with something that we've already talked about.
in class so far. What happens to enzymes when they get really, really hot? Well, when enzymes get really, really hot, they denature and they stop functioning. Right.
So if you get to a certain temperature, you denature the enzymes and they no longer work the way that they're supposed to. Okay, so in fact for this particular reaction, if we took something all the way up to a hundred, it would not do very well at all, wouldn't increase a lot because although the reaction might happen to a small degree, if the enzymes are denatured then they're not helping speed up the chemical reaction. Sort of the rule of thumb is that for most reactions the rate and temperature looks something like this.
An increase, an increase, an increase, and then at some point, a vast drop-off. And that drop-off indicates the point at which enzymes denature. All right, so this is actually your final in-class participation question. Question number five.
Would an increase in temperature result in a continuous increase in a rate of reaction? Why or why not? Question number five. Would increasing the temperature always result in an increase in the rate of a reaction indefinitely?
Why or why not? Now you'll also notice that your lab manual has given you two graph spaces, right? So this is one way that the information can be illustrated, if you want to show the changes over time.
But what if you're only interested in comparing the results at one time point? For instance, what if I only want to see what the end result was after 20 minutes? Maybe I want to compare how much it increased at 20 minutes between 0, between 24, and between 40 degrees. That information could also be illustrated, but it would be done so in a different type of graph.
Instead of using a line graph, a bar graph would be more appropriate because now you're comparing data at one point in time between temperatures rather than comparing changes in data over time. Let's look at what that setup might look like. So you have another table in your book that gives you a spot to record just the increases at the 20-minute time period. for the three temperatures.
If you wanted to create a bar graph for this, here's kind of how you would set that up. We got our x-axis, we got our y-axis. The nice thing is, what goes on our y-axis is exactly the same as what went on our y-axis in the line graph, the increase in CO2 level. And again, that's in parts per million.
What goes on your x-axis changes though. Now what's going to go on our x-axis are the things that we manipulated, the treatments, which in this case are the temperatures. So we would say temperature and we would need to include units degrees Celsius, and then we would have a bar for each temperature, right?
So we'd have a zero degrees Celsius bar, we would have a 24 degrees Celsius bar, and we would have a 40 degrees Celsius bar. They should be equally spaced and each bar should be equal in width. The top of the bar would indicate the average increase in CO2.
So we would see something like this with the 40 degree bar being the highest corresponding to this 3,699 here. If we had replicates, we could also add standard. We only ran the experiment once by ourselves, but if we ran this as a class and had two people doing the 0 degrees and two people doing the 24 and two people doing the 40, we would have different numbers, right? Like, so for instance, maybe if we did it, another group would get 900, and this group maybe would get 2200, and maybe this group would get 4000. The standard deviation bar would tell us how much variation there was between the replicates. the smaller the variation, the smaller the bar, the greater the variation, as is more variation in this 40 degree example, the bigger the bar.
And then we could use that to help us determine if these differences were significant or not. Now we'd also need to change our title a little bit as well, not significantly. I'm going to write, titles are supposed to go below the graph, but I'm going to write it off to the right here.
Your teacher might refer to this as a caption title, caption, tomato, tomato, you all need one. regardless of what you call it. So we would still have something to the effect of the effect the influence or the effect of temperature on the rate of cellular respiration. That didn't change. And maybe we just say after 20 minutes.
So it's a pretty small change. The after 20 minutes suggests that we're just looking at one time period, whereas in the other one we said over 20 minutes, which suggests that we're looking at multiple data points. It's just a slight modification.
The big thing is your titles should indicate what the independent variable is, the thing that's being changed. It should indicate the dependent variable, what you're measuring, and it needs to indicate what your subject is, the thing that's being tested. You're given a little bit of lean way, but