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Natal Bean Discrimination by Bean Beetles

  • Page ID
    7698
  • Adapted from C. Beck and L. Blumer by Staci Forgey, TCC Biology Faculty

    Objective

    Design and perform a set of experiments to evaluate whether female bean beetles (Callosobruchus maculatus) discriminate between suitable species of beans.

    Introduction

    Bean beetles, Callosobruchus maculatus, are herbivorous pest insects that are found in Africa and Asia. Females lay their eggs on the surface of beans. Eggs are layed singly, and hatch into larvae (maggots) several days later. The larva then burrows into the bean and will form a pupa 21–30 days after the egg was deposited. They mature 24–36 hours after emergence from the pupa and do not need to feed.

    Adults typically live for 1–2 weeks. Mating and oviposition occur during this time period. Females will choose the best substrate (bean) to lay their offspring on, since the larvae cannot move. By choosing a substrate for oviposition, the female chooses the food resource available to her offspring (Brown and Downhower 1988). This is a critical choice for the female, as it influences the growth, survival and future reproductive success of her offspring (Mitchell, 1975, Wasserman and Futuyma, 1981). Females can lay eggs on a wide range of bean species, but very few bean species will result in normal development and the successful emergence of adults. Some species of beans are toxic to larvae (Janzen 1977).

    Materials

    In class, you will be provided with live cultures of bean beetles containing adults that have been raised on mung beans (Vigna radiata).

    Female beetles are easily identified in the live cultures because they have two dark stripes on the posterior of the abdomen, whereas the posterior abdomen of males is uniformly light in color.

    You will also have access to petri dishes and several types of beans.

    Experimental Design

    Since the oviposition choices of females influences the survival and future success of their offspring, females may be very sensitive to the species and condition of the beans on which they are depositing eggs.

    Each group should design a set of experiments to address whether female bean beetles discriminate between suitable species of beans. We will re-visit the experiment next week and collect our data set. We will choose one experiment to perform as a class.

    As a group, list several ways we might examine female bean choice for oviposition. We will pick one experiment from the class to perform. Write your ideas below.

    **Stop here. We will go over ideas for our experiment as a class and choose one to perform**

    Outline the agreed on experiment using the criteria below.

    1. Formulate a hypothesis for this week’s experiment. Be specific!
    2. We will re-visit the experiment in a week to collect data on the number of eggs laid. Formulate a hypothesis for this experiment.
    3. Identify the independent variable(s).
    4. Identify the dependent variable(s).
    5. What variables will you keep standard?
    6. What is your control?
    7. Design data collection tables for both of your experiments on a separate sheet of paper.

    For this data, it is most useful to perform a Chi Square analysis. Chi Square statistical test evaluate whether this is a significant difference between groups of data. The null hypothesis (H0) is the hypothesis that states that there is no difference between the groups of data. The alternative hypothesis, (Ha) is the hypothesis you outlined above.

    1. Restate your H0 hypothesis.
    2. Ha hypothesis.
    3. If the null hypothesis is correct, what would we expect to see?
    4. If our alternative hypothesis is correct, what would we expect to see?

    To do this statistical test, we need to calculate observed and expected values for the bean species and for our control. Our expected values are based on our null hypothesis (that there is no difference).

    For example, if we had 40 eggs and four different treatment groups, we would expect there to be 10 eggs on each group.

    Treatment Observed number of eggs Expected number of eggs
    Mung beans 5 10
    Pinto beans 25 10
    Chick peas 10 10
    Control 0 10

    Fill in the data table below with our observed (what we actually found) and expected values.

    Treatment Observed number of eggs Expected number of eggs

    To calculate the chi-square value, or \(\chi ^{2}\), we simply add the square differences, divided by the expected, of all the observed and expected. In mathematical terms:

    \(\chi ^{2} = \Sigma\frac{(O-E)^{2}}{E}\)

    So for our example from the previous sample table, the first \(\frac{(O-E)^{2}}{E}\)​​​​ would be \(\frac{(5-10)^{2}}{10}=2.5\)

    We would then add to this value all of the other \(\frac{(O-E)^{2}}{E}\)​​​​ in the table and then add to get the \(\chi ^{2}\) value.

    Treatment Observed number of eggs Expected number of eggs Observed-Expected (Observed-Expected)2 (Observed-Expected)2/Expected

    Compute the χ2 value for your data by adding all of the (Observed-Expected)2/Expected values.

    In order to find something to compare this number with, we need to calculate the degrees of freedom, or the number of different comparisons that can be made within the table. The degrees of freedom are the number of columns (M) minus one times the number of rows (N) minus one.

    Degrees of freedom = (M − 1)(N − 1)

    A B
    C D

    How many ways can this two by two table be broken into individual comparisons? Hint: Use the formula above.

    Calculate the degrees of freedom in your experiment.

    Now we can compare against the Chi distribution for the likelihood that our data is generated by chance. Remember, we are looking at the column labeled 0.05 for our p value. This means that at this level, we are 95% sure our results are real. The Chi distribution table gives us a critical value to compare our test value to.

    • If test > critical value @ p level, reject null hypothesis
    • If test < critical value @ alpha level, fail to reject null hypothesis

    Compare to the Chi-distribution table. Did your results come about by chance?

    DF/P 0.995 .990 0.975 .950 .900 .750 .500 .250 .100 .050 .025 .010 .005
    1 0.00004 .00016 0.001 0.004 0.016 0.102 0.455 1.323 2.706 3.841 5.024 6.635 7.879
    2 0.010 0.020 0.0506 0.103 0.211 0.575 1.386 2.773 4.605 5.991 7.378 9.210 10.597
    3 0.072 0.115 0.216 0.351 0.584 1.213 2.366 4.108 6.251 7.815 9.348 11.345 12.838
    4 0.207 0.297 0.484 0.711 1.064 1.923 3.357 5.385 7.779 9.488 11.143 13.277 14.860
    5 0.412 0.554 0.831 1.145 1.610 2.675 4.351 6.626 9.236 11.070 12.833 15.086 16.750
    6 0.676 0.872 1.237 1.635 2.204 3.455 5.348 7.841 10.645 12.592 14.449 16.812 18.548
    7 0.989 1.239 1.690 2.167 2.833 4.255 6.346 9.037 12.017 14.067 16.013 18.475 20.278
    8 1.344 1.647 2.180 2.733 3.490 5.071 7.344 10.219 13.362 15.507 17.535 20.090 21.955
    9 1.735 2.088 2.700 3.325 4.168 5.899 8.343 11.389 14.684 16.919 19.023 21.666 23.589
    10 2.156 2.558 3.247 3.940 4.865 6.737 9.342 12.549 15.987 18.307 20.483 23.209 25.188
    11 2.603 3.053 3.816 4.575 5.578 7.584 10.341 13.701 17.275 19.675 21.920 24.725 26.757
    12 3.074 3.571 4.404 5.226 6.304 8.438 11.340 14.845 18.549 21.026 23.337 26.217 28.300
    13 3.565 4.107 5.009 5.892 7.042 9.299 12.340 15.984 19.812 22.362 24.736 27.688 29.819
    14 4.075 4.660 5.629 6.571 7.790 10.165 13.339 14.114 21.064 23.685 26.119 29.141 31.319
    15 4.601 5.229 6.262 7.261 8.547 11.037 14.339 18.245 22.307 24.996 27.488 30.578 32.801
    16 5.142 5.812 6.908 7.962 9.312 11.912 15.339 19.369 23.542 26.296 28.845 32.000 34.267
    17 5.697 6.408 7.564 8.672 10.085 12.792 16.338 20.489 24.769 27.587 30.191 33.409 35.718
    18 6.265 7.015 8.231 9.390 10.865 13.675 17.338 21.605 25.989 28.869 31.526 34.805 37.156
    19 6.844 7.633 8.907 10.117 11.657 14.562 18.338 22.18 27.204 30.144 32.852 36.191 38.582
    20 7.434 8.260 9.591 10.851 12.443 15.452 19.337 23.848 28.412 31.410 34.170 37.566 39.997
    21 8.034 8.897 10.283 11.591 13.240 16.344 20.337 24.935 29.615 32.671 35.479 38.932 41.401
    22 8.643 9.542 10.982 12.338 14.041 17.240 21.337 26.039 30.813 33.924 36.781 40.289 42.796
    23 9.260 10.196 11.689 13.091 14.848 18.137 22.337 27.141 32.007 35.172 38.076 41.638 44.181
    24 9.886 10.856 12.401 13.848 15.659 19.037 23.337 28.241 33.196 36.415 39.364 42.980 45.559
    25 10.520 11.524 13.120 14.611 16.473 19.939 24.337 29.339 34.382 37.652 40.646 44.314 46.928
    26 11.160 12.198 13.844 15.379 17.292 20.843 25.336 30.435 35.563 38.885 41.923 45.642 48.290
    27 11.808 12.879 14.573 16.151 18.114 21.749 26.336 31.528 36.741 40.113 43.195 46.963 49.645
    28 12.461 13.565 15.308 16.928 18.939 22.657 27.336 32.620 37.916 41.337 44.461 48.278 50.993
    29 13.121 14.256 16.047 17.708 19.768 23.567 28.336 33.711 39.087 42.557 45.722 49.588 52.336
    30 13.787 14.953 16.791 18.493 20.599 24.478 29.336 34.800 40.256 43.773 46.979 50.892 53.672

    We will now use this data and information to do a lab write up.

    Lab Report Template

    The report should be typed and single spaced. See grading rubric for clarity on formatting.

    Title Page

    • Should include Title (a brief, concise, yet descriptive title), your name, lab instructor’s name, and lab section.
      • Note: this is a separate sheet

    Body of Report

    Identify the different sections of the body of the report with headings.

    The report should begin with a brief paragraph (complete sentences) that includes a statement of the problem and your hypothesis. This should be under the heading of Introduction.

    • Statement of the problem:
      • What question are you trying to answer?
      • Include any preliminary observations or background information about the subject (in this case the bean beetles) such as reproductive cycle, life span etc. Be sure to cite any sources.
    • Hypothesis:
      • Write a possible explanation/prediction for the problem/question you are asking.
      • Make sure this possible explanation/prediction is a complete sentence and not a question.
      • Make sure the statement is testable. In other words, can you perform an experiment that will either support or refute your prediction. If you cannot not think of a way to test your prediction, then it is not testable.

    Next heading should be Materials:

    • Make a list (this does not need to be in paragraph form) of ALL items used in the experiment and their quantities. Of the materials used, identify which are dependent and independent variables, constants (standardized variable) and control group (you will lose points if you do not identify ALL dependent and independent variables, constants and controls).

    Next heading should be Procedure:

    • Write a paragraph (complete sentences) which explains what you did in the experiment.
    • Your procedure should be written so that anyone else could repeat the experiment. For instance, what beetle did you use? How was your petri dish set up? What beans did you use? That means that even some of the most obvious steps need to be stated so there is no ambiguity.
    • When designing the procedure, be sure to include replicating the experiment to ensure data is reproducible and valid.

    Next heading should be Results:

    • Write a paragraph (complete sentences) describing the results and observations of your experiment. Here you will compare results for controls and variables and not simply list the numbers.
    • This section also includes data tables, graphs or charts to illustrate the results of you experiment. Be sure to include calculated averages of t.
    • All tables, graphs and charts should be labeled appropriately (a title, labels for x & y axis, legend etc.) so the reader will be able to understand.

    Next heading should be Conclusions:

    • Write a paragraph restating your hypothesis and whether you accept or reject your hypothesis
    • In this paragraph, explain why you accepted or rejected your hypothesis using data from the experiment. Include a brief summary of the data—averages, highest, lowest, etc., to help the reader understand your results and why you have come to particular conclusions.
    • Discuss your thoughts about the possible reasons for your results (for example, if you chose salt water as a variable, give a possible reason why salt water, in particular, may have generated your results).
    • Discuss possible errors that could have occurred in the collection of the data (experimental errors) and describe how these errors may have impacted the data.

    External Helps

    These websites have helpful hints related to scientific writing that will help you with your lab report:

    How to write citations:

    The following rubric will be used to grade these reports:

    Excellent
    5 points
    Satisfactory
    2.5 points
    Unsatisfactory
    0 points
    Title Page Contains title, student name, instructor name and section Missing either instructor name or section No title page
    Formatting: typed, spacing Typed and single spaced Typed, but not single spaced Not typed
    Grammar and Spelling No errors; contains complete sentences and no misspellings A few minor errors in grammar and spelling Several major errors in grammar and spelling
    Formatting: headings Each section has a heading as described in template Some sections lack headings No headings
    Hypothesis Predictions are clearly stated and written as a testable statement Predictions/expected outcomes are not clearly stated Not written as a testable statement
    Materials All equipment and materials described; identify variables, controls and constants Materials incompletely described No identification of variables, controls and constants
    Procedure Clear step-by step description Description missing details making it difficult for another scientist to repeat experiment Description missing so much detail it would be impossible to repeat
    Results Clearly written description of results comparing controls and variables Results are presented but no comparison between controls and variables are made No written description of results
    Data tables, graphs or charts Easy to interpret, clear labels, all data, including calculated averages, included Disorganized (not easy to understand, missing labels) but all data included Disorganized and or data clearly missing
    Conclusion Clearly explains acceptance or rejection of hypothesis using data to support conclusion; identifies sources of error Accepts or rejects hypothesis but does not use data to explain why; or does not identify sources of error Does not explain conclusion and does not identify sources of error
    Total ______out of 50 points

    Literature Cited

    Brown, L. and J.F. Downhower. 1988. Analyses in Behavioral Ecology: A Manual for Lab and Field. Sinauer Associates, 194 pages.

    Janzen, D.H. 1977. How southern cowpea weevil larvae (Bruchidae Callosobruchus maculatus) die on non-host seeds. Ecology 58:921–927.

    Mitchell, R. 1975. The evolution of oviposition tactics in the bean weevil, Callosobruchus maculatus F. Ecology 56:696–702.

    Wasserman, S.S. and D.J. Futuyma. 1981. Evolution of host plant utilization in laboratory populations of the southern cowpea weevil, Callosobruchus maculatus Fabricius (Coleoptera: Bruchidae). Evolution 35:605–617.


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