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Seed Germination: Preparing for an Experiment
Introduction
The purpose of this lab is to gain experience with the technique and process of seed germination
and to introduce you to several standard methods of scientific data analysis and summarization.
You will then use these skills and information in designing, conducting, and writing up an
experiment focusing on seed germination.
One of the keys to most successful experiments is the selection of an appropriate organism. Early
experiments in genetics, for example, relied on the fruit fly Drosophila.. In hindsight, this was an
inspired choice. We don’t have such a lofty goal of establishing the best organism for teaching
you the fundamentals of experimentation; however, seeds are useful because of their abundance,
variety, low cost, and portability. We will introduce experimentation by giving you a chance to
become familiar with a variety of seeds. Then you can select the type that you think will best help
you investigate an experimental problem.
Seed Germination
The focus of the experiment that you will conduct beginning next week will be seed
germination. Your task this week will be to try to germinate seeds from at least 3 plant species.
You need to become adept at keeping them alive through their first critical days of growth. Next
week you will choose one of these 3 plant species to test how different environmental factors
(your experimental treatments) influence normal germination and growth.
Seed germination is simply the sprouting of the seed. It is initiated when the seed begins to absorb
water. Several environmental factors, such as temperature and light, can stimulate germination.
Seed germination ends when the embryo within the seed begins to grow or elongate. You can
easily see this because a radicle, or immature plant root, begins to grow out of the seed. Soon
after the radicle appears, a shoot will begin to grow out of the opposite end of the seed. The shoot
is that part of the plant which usually grows above the ground; it is comprised of a stem and
leaves. The earliest stage of plant growth, which begins immediately after seed germination, is
called seedling growth. For your experiment, you will likely be observing and recording both
seed germination and seedling growth.
Scientific Names
Scientific names are assigned to each type of organism that scientists describe. There is only one
acceptable scientific name for any organism, no matter what language you may be using. In
contrast, common names can vary so widely that it is sometimes difficult to be sure what
organism local people are talking about. For example, in Hawai’i cinnamon is an aromatic spice
used in baking and cooking. 1
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Mr. Cogbill’s Seed Germination Prep. Lab 10/2/06
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It is the dried bark of a twig of the tree Cinnamomum zeylandicum. In the United States Virgin
Islands, however, cinnamon is the aromatic leaf of the tree Pimenta racemosa. If you go to the
market in St. Thomas and want the spicy twig that we call cinnamon, you need to ask for “spice”
because this is what they call “our” cinnamon! So, you see how confusing common names can
be. Scientific names get rid of all this confusion by assigning just one name per organism. There
are specific rules for assigning names.
1. the name must be in Latin. Latin has been accepted as the universal scientific language,
mainly because no living cultures claim it as their daily language and also because it is the
root language to many of the western language systems. (The scientific method for naming
organisms began in Europe.)
2. each name must be a binomial, i.e., it has 2 parts, the genus and the species.
Scientific names are always underlined or are written in italics. This is because Latin is a foreign
language and foreign terms are always underlined or written in italics. The first letter of the genus
is always CAPITALIZED; the species name is always written in lower case. Taken together, the
genus and species name represents one, unique organism. Several closely related species are
classified within one genus. Several closely related genera are classified under one family name.
The family name is always capitalized. Here’s an example of how scientific names are used: the
scientific name for hibiscus is Hibiscus rosa-sinensis (note the capitalized genus, the lower case
species, and the use of italics). The scientific name for the hau tree is Hibiscus tiliaceus. Hau
belongs to the same genus as hibiscus so we know that these two plants are closely related.
These two plants belong to the plant family called the Malvaceae. Another plant that belongs to
this family is the cotton plant, Gossypium tomentosum. However, from its scientific name, we
know that cotton is not as closely related to hibiscus as hau is, because they belong in different
genera. See how much information we can learn from scientific names! Once you get
accustomed to using Latin, scientific names aren’t so bad. You won’t need to worry about
memorizing scientific names, but you should understand the rules for them.
Diagram of the Parts of a Seed
It is helpful to know the parts of a seed so that you will understand the process of seed
germination. Both dry and pre-soaked seeds are available for you to observe the outer and inner
structure, respectively, of seeds. You will make 2 drawings based on your observations of the
seed. Place both drawings together on a separate sheet of paper.
1) Use a dry seed to examine the external features of the seed. Draw what you see. Label the seed
coat, and the hilum. (The hilum is that part of the seed which was attached to the fruit; it’s
analogous to your belly-button). Be sure to include a scale bar on your drawing to indicate the
size of the seed.
2) Use a pre-soaked seed to examine the internal structure of the seed. Use your thumbnail to split
the seed in two longitudinally. Make a drawing of the internal structure of the seed from one of
the seed halves; label the plumule, hypocotyl, and radicle (see Figure 2-1). Include a scale bar
for this drawing, too. (The plumule will become the first pair of leaves when the seed sprouts; the
hypocotyl will elongate and pull the bean seed above ground; the radicle grows into the primary
root.)
3) Label your drawing with the common name of the seed, the plant family to which the species
belongs, and the scientific name of the seed (genus and species).
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Figure 2-1. Seed and Seedling
Reprinted by permisssion of Carolina Biological Supply Company
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Take-Home Exercise
Look at the live demonstrations in the lab of bean and corn seed germination, as well as the
online descriptions. The demonstration and descriptions will help you know what to expect, and
to better understand what you are looking at as your seeds germinate and grow.
Before leaving lab for the day, take the following with you:
1. Three plastic ziplock baggies
2. Three paper towels
3. Four seeds of each of three species or varieties (for a total of 12 seeds).
Be sure to record the names of the 3 types of seeds you took. The common and scientific names
of the nine types of seeds available for you to choose from are:
Lima beans
Black beans
Phaseolus lunatus
Phaseolus vulgaris
Kidney beans Phaseolus vulgaris.
White beans
Phaseolus vulgaris
Pinto beans
Phaseolus vulgaris
Adzuki beans
Vigna angularis
Mung beans Vigna radiata
Black-eyed peas Vigna unguiculata
Corn Zea mays
When you arrive home, do the following: Label one of the baggies with the name of one of the 3
types of seeds. (A permanent marker pen works well for this.) Thoroughly soak a paper towel
with water by holding it under a water faucet. (Do NOT unfold the towel.) Place the wetted paper
towel on a flat surface, and put all 4 seeds of that type on one half of the paper towel. Fold the
other half of the wetted paper towel over them. Now, place this “seed sandwich” inside the plastic
ziplock baggie, and be sure to completely close the baggie. Repeat this procedure for each of the
other 2 types of seeds you took.
Now find a place to put the baggies where the seeds will not be disturbed for a week. Avoid
places that would provide extreme conditions, such as a hot, sunny windowsill, or atop an air
conditioner. Germination is triggered by the seed imbibing water, but the period of time before
the emegence of the radicle and shoot will vary depending on the type of seed. You should check
your seeds three times in the following week, about every 2 days (i.e., 48-hour intervals), by
carefully taking the paper towel out of the baggie and unfolding it to examine the seeds. After
recording your observations (see the following section), carefully re-fold the seeds in the paper
towel and return them to the baggie.
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Construct an Observation Table
Use the space below to make a table in which you will record your seed germination and seedling
growth observations for each of the seeds you are sprouting. Be sure to make observations and
measurements about every 2 days (i.e., 48-hour intervals). For each of the 3 seed types you have
chosen, record the number of seeds which have germinated, and measure the length of the radicle
and shoot after germination. (Because the radicle or shoot may be curved, you might contour a
piece of thread or dental floss along its curvature and then stretch the thread (or floss) along a
ruler to determine a straight-length measurement.) Leave space in your table to note any other
changes you observe. Be sure to bring your baggies with your plants back to lab next week.
Your Teaching Assistant will review your table of observations and will look at your plants to
help you evaluate your germination technique and observation skills.
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Summarizing Data
Any time we take measurements in science, we need a way to summarize these data (note: this
word is plural; one single measurement value is a datum). We also notice that there is a lot of
variability caused by naturally occurring variation and our experimental treatments. We need
methods to allow us to understand this variability and to compare different sets of data. Statistics
is defined as the scientific study of numerical data based on variation in nature. Statistical
analysis allows us to summarize our data into a readily understandable form.
Biologists generally study populations of organisms; that is, all the individuals of a given species
found in a circumscribed area at a given time. It is often impossible (and impractical) to study
every organism in the population. Therefore, scientists usually make observations on some
feasible number of organisms. They use this sample of the population to provide an estimate of
what the whole population is really like. In a general sense, the larger the sample, the more
accurate the estimate becomes. This is because there is less likelihood that a few chance, deviant
measurements will bias (i.e., unduly influence) our estimate. Sampling should be done randomly
to help reduce bias in the results. The features that we measure are called variables or characters.
In a study of a population of pea seedlings, variables that we might observe include plant height,
maximum leaf width, dried plant weight, leaf color, or the number of leaves. Some variables can
be measured (for example, length and weight) and given numerical values; these are called
quantitative variables. Other variables are attributes that must be expressed qualitatively (such
as color or texture). Such variables can only be described and are termed qualitative variables.
There is always some error or inaccuracy in scientific measurements. Scientists try to identify
and quantify the sources of error. One source of error is based on the precision, or lack of it, in
our measurements. For instance, when measuring time, a watch may be fast or slow. Also if you
measure to the nearest minute, your measurements won't be as precise as measuring to the nearest
second. Bias can be a source of error in science. Scientists are humans with opinions, prejudices,
and desires for success. Much human bias is unconscious. Scientific questions, the methods used
in experiments, and the conclusions drawn from results are all subject to bias. So scientists report
procedures to others for criticism and advice, and try to improve procedures and reduce bias.
In this lab, you'll learn some basic graphing and statistical techniques for analyzing data. When
you do your seed germination experiments, you will be collecting measurements of variables.
You will need to analyze these data, too. So the techniques you will be studying here will be used
in several other situations this semester. Statistics is an important component of quantitative
research. Statistics not only allows you to quantitatively describe and compare information, but
also makes your conclusions more objective.
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Graphing
Let's assume that you have collected the following data on 10 snakehead cowries (Cypraea
caputserpentis) from some tropical islands. A cowry is a type of marine mollusk. First you make
a data table to record your observations.
Table 1. Observations on Snakehead Cowries
shell
number
1
2
3
4
5
6
7
8
9
10
length
(mm)
10.4
11.1
10.7
10.5
10.4
10.6
10.9
10.6
10.9
10.5
weight
(g)
5.2
6.2
5.7
5.5
5.4
5.5
5.7
5.4
6.0
5.4
sex
color
F
M
M
F
F
F
M
F
M
F
green-yellow
yellow
yellow
green-yellow
yellow
green
green-yellow
green-yellow
green-yellow
green
What are the quantitative variables for this data set?
What are the qualitative variables for this data set?
Long lists of data are often not very useful for identifying trends in the variables or for noting
significant points. The next step is to graph the data. Plot how the weight of a shell is related to its
length in Figure 1.
weight (g)
6.5
6
5.5
5
10
10.5
11
11.5
length (mm)
Figure 1. Length-weight relationship of snakehead cowries.
What does this graph show you about the relationship between weight and length?
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How are they correlated? (That is, is there any trend between length and weight?) Is the
relationship positive or negative?
numbe r of individua ls
Now you want to show how many shells are female and how many are male, so make a bar
graph in Figure 2. The vertical axis represents the counts or frequency (%) of a set of categories
(in this case, male or female). Note that in a bar graph, the horizontal axis is always divided into
categories which are equally represented by the width of the bar.
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7
6
5
4
3
2
1
0
male
female
sex
Figure 2. Frequency of male and female snakehead cowries.
Descriptive Statistics
There are two basic groups of descriptive statistics: statistics of location and statistics of
dispersion. Statistics of location tell us about the central tendency of the data. A familiar statistic
of location is the mean or average, symbolized as x̄ (read as x-bar). The mean of a data set is
calculated by summing up all of the measurements and dividing that sum by the number of
observations. Note that the mean is not necessarily the true average of the population. Remember
that you only measure a sample from the population. If the sample is large and is representative
of the population, however, then the sample mean should be a good estimate of the true
population mean. Another measure of the central tendency of a variable is the median or middle
measurement in a ranked listing of the data. Equal numbers of measurements are larger and
smaller than the median.
Statistics of dispersion tell us how tightly clustered the individual values are around the mean,
which gives an indication about the variability of the data. One simple statistic of dispersion is the
range which is the difference between the maximum (largest) value and the minimum (smallest)
value. Note that the range is highly influenced by sample size. A more commonly used statistic
that expresses the variability in a sample is the standard deviation. The standard deviation (SD)
is not biased by sample size. A small SD indicates the individual values tend to be closely
clustered about the mean; there is low variability in the data. In contrast, a large SD indicates the
individual values are widely dispersed about the mean; there is high variability in the data.
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Calculating the Mean & Standard Deviation
The mean of a set of numbers is calculated simply by adding up all the numbers, then dividing by
the number in the set. You can do this with a simple calculator (or even with a pencil and paper if
you have a simple problem). Computations for standard deviation are more arithmatically
complex.
These days, we generally use a spreadsheet program on a computer to do the arithmetic for us. It
is not only easier, but a spreadsheet provides a good way to neatly store and print data tables.
Our lab computers run Microsoft Word and have Excel as their spreadsheet.
Each computer has a list of values placed beside it. Use Excel to determine the number of values
in the list, their mean, and the standard deviation. First, double click the Excel icon to get the
spreadsheet started. Next, type your values in a column, with one value in each “cell”. At the
bottom of the column, type the format to carry out the appropriate function. Be sure to place
different functions in different cells. Labels (e.g., mean, SD) can be typed in adjacent cells.
Function
Format
Example
number of items in a list
=count(start:end)
=count(A1:A10)
mean of a list
=average(start:end)
=average(B2:B11)
standard deviation of a list
=stdev(start:end)
=stdev(C3:C8)
Note that the start and end values are given in “column and row” format; the letter of the column
is followed by the number of the row. The start and end refer to the top and bottom cells of the
list of values. There can be no blank spaces in the formula.
Once the data and formulas have been entered, it is possible to change the data. When you do,
the values calculated by the formulas change automatically.
Record your results below:
Computer #
Number of items in the
list
Mean
Standard deviation
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Presenting Tables
Statistical information about your data can be presented in a table, a list of values arranged in
columns and rows. A table should be able to stand alone for anyone to interpret without having to
refer to other written material, nor having to ask the researcher to explain it. Thus, every table
should have its own descriptive title, column headings and row headings. The units for a
particular variable should be indicated (usually in the headings). Any other information pertinent
to the table may be placed in a legend below the table. Look at the example below of an
information-packed table.
Table 1. The Effects of High and Low Fat Diets on the Weights and Lengths of a Group of Rats.
(Mean weight ± standard deviation)
----------------------------------------------------------------------------------------Diet Type
Mean Weight
Mean Length
(g)
(cm)
----------------------------------------------------------------------------------------High fat
545.5 ± 6.2
55.3 ± 1.2
Low fat
346.7 ± 4.3
53.2 ± 0.9
----------------------------------------------------------------------------------------The high fat diet consisted of 50% fat, while the low fat diet
consisted of 5% fat. The values are the means for 100 rats.
In summary, the main parts of a table are:
1) Table #
2) Title (specific and descriptive); the table title belongs at the TOP of the table
3) Column headings
4) Row headings
5) List(s) of data
6) Units of measurements
7) Legend to explain some aspect of your table
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