5 Prelab Reading Dilutions and Standard Curve

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Feb 20, 2024

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Pre-Lab Reading: Dilutions Objectives: This reading should help you, by the end of this experiment, to be able to: 1. Correctly measure fluids using a pipette 2. Carry out a serial dilution 3. Use data from a spectrophotometer to create a standard curve showing algal concentration 4. Identify morally relevant facts in ethics issues in conducting research, critically evaluate those facts in order to develop a resolution The purpose of this laboratory exercise relates directly to the experiments you will be conducting throughout the semester. In today’s lab, you will learn how to determine the concentration of algae in a solution of saltwater. This is critical for working with plankton, as the algae are the food source that they need in order to survive. If your algae are not concentrated enough, the plankton will starve and will die in large numbers. If your algae are too concentrated, this can affect the swimming and breathing ability of the plankton. Therefore, it is important to know just how many algal cells are in the solution that you are using to feed the plankton. In order to know how much to feed your copepods each week, you will need to use a standard curve to determine the concentration of the algae. Today we are going to practice making a standard curve and learning how to use one to determine concentrations. We will do this in five steps: 1. Make a serial dilution 2. Use a spectrophotometer to find the absorbance of our solutions 3. Enter data points in Excel 4. Graph a standard curve 5. Find the concentration of an unknown using the standard curve Dilutions Orange juice is a great example of dilution – when you make orange juice from a can, the stuff in the can is called “concentrate”. You then dilute it with water. Serial dilutions are made with the same general idea, but a slightly different process. To make a serial dilution, you begin with a stock solution. A stock solution is the concentrated solution which is being diluted. Next, you need to know your dilution factor , which is a number that describes the strength of the dilution . For example, a dilution factor of 10 means a 1:10 dilution of the stock solution. To

1 ml of stock solution 9 ml of water calculate the dilution factor, you take the volume of the stock solution that you are going to use and divide this by the total volume of the entire solution. volume of stock solution youare using total volume ∈ your dilution For example, if you are doing a 1:10 dilution, you would take 1ml of your stock solution and add 9ml of water for a total volume of 10ml. 1:10 dilution In many cases, a dilution factor of 10 or 2 is used to dilute a stock solution and create a series of less concentrated solutions. This process is referred to as making serial dilutions. A serial dilution is a sequential set of dilutions, where each solution acts as the stock for the next solution. Essentially, it is just the process of making dilutions with the same dilution factor over and over. To carry out a 1:10 serial dilution, assume that you start with 11 ml of your stock solution. To make a 1:10 dilution, take 1ml of your stock and add 9ml of water. This will give you a new stock solution that has been diluted by a dilution factor of 10. You now take 1ml of this new stock solution and add 9ml of water. This gives you yet another new stock solution that has been diluted by a dilution factor of 10. This process is repeated until you reach the total dilution you were looking for. The image below may help understand the process of serial dilutions.

Standard Curve Once you have made your dilutions, it is useful to create a standard curve to help you keep track of the amount of a particular substance in a solution. A standard curve is a graph with the concentration of the solution on the X-axis and a different measurement on the Y-axis. This different measurement is one that is more easily measured than the concentration. For example, assume you have a sample of algae, and you want to know how much algae is in the sample. It would be impossible to count the number of algal cells in the entire sample, and difficult and time consuming to count all of the cells in even a drop. If, instead, you have a standard curve, you can use the graph to determine the algal concentration. See the graph below for an example. For this semester, the measurement that we will use on our standard curve is the amount of light that is absorbed by the solution, referred to as the absorbance. The more algae that are in the solution, the more light that will be absorbed . An easy way to measure absorbance is to use a machine known as a spectrophotometer . This machine shines a light on the sample, measuring the amount of light that is absorbed and the amount that is transmitted through the sample to the other side . The advantage of using the spectrophotometer is that we can place a sample in the machine, record the absorbance, and then use the standard curve to determine the actual algal concentration of our sample. This is much easier than actually counting the individual algal cells. However, it is important to remember that if your absorbance is beyond the scale of the graph (for example in the graph below if your absorbance is 150), you cannot then use that to determine your concentration. A standard curve is only accurate for those data that fall within it. 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Tetraselmis Standard Curve Cell concentration (cell/mL) Absorbance

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Topics in Ethical Conduct in Research: Data Management This week we are going to look at Data Management in research. Maintaining accurate and organized records is necessary for transparency and reproducibility of experiments. Our research should stand up to critical review. Part of this review is being able to show how the raw data was used to generate the reported results. This is true of both experimental and observational studies. While raw data is not generally included in a scientific paper, it is often included in appendices to the paper or by request. This can help settle any uncertainties about the validity of the results. If conducting an experimental study, as we are doing in this lab, the experiment should be reproducible. The results of the experiment should be due to the design of the experiment; anyone using that same design should get the same results. If the results of an experiment cannot be replicated, we should not accept the original results. That is, we would not accept that the independent variable caused the reported change in the dependent variable. We might still accept that the original researchers are telling the truth, and look for variables or steps in the procedure not addressed in the paper, that could account for the difference in results. For example, perhaps the researchers record that they used “table salt”, but it turns out that the brand used makes a difference. One example of how good record keeping led to big advances in science involves the discovery of noble gasses. In the late 1800s, Lord Rayleigh had the means to become a renaissance man of science and the time on his hands to devote himself to experiment after experiment. He wasn’t a trained chemist (his formal training was physics and mathematics), but he enjoyed it, so he set about isolating Nitrogen from the air, using the methods published in the literature. It may sound a bit boring, but it was a new discovery and all the rage in chemistry at that time. Experiment after experiment, his experimental yield was1/5000 of an ounce off the predicted value. It happened again and again, always 1/5000 of an ounce off. He wrote to professional chemists, who told him that it was likely due to experimental error. He didn’t give up. He kept trying new ways to isolate Nitrogen. Each method gave a consistent “error.” Eventually his efforts convinced professional chemist William Ramsey to join the effort (although Rayleigh might have felt more like he was butting in). After more time, experiments, and detailed record keeping, the pair was able to show that the “error” was actually the presence of an unknown gas - they had discovered the element Argon. Book Chapter: “Into the Blue”, Caesar’s Last Breath , by Sam Kean Journal Article: Spanos, A. (2010). The Discovery of Argon: A Case for Learning from Data?*. Philosophy of Science , 77 (3), 359–380. https://doi.org/10.1086/652961 University Website: https://www.chem.ucl.ac.uk/resources/history/chemhistucl/hist14.html (this site contains links to the original letters between Ramsay and Rayleigh)