Remote Ready Biology Learning Activities

Biology 103

Jessica Kiefer

Category: Grasses
-visibly made up of only blades
-blades grow in clumps
grass1
-very thin, wispy blades
-not rigid
-grows directly from ground
grass 2
-branches a little above ground
-thicker, flat blades
grass 3
-thickest, flat blades
- veins clearly visible
grass 4
-horizontal blades off of one main branch
Category: Things that grow on trees
-no roots
-no branches
-no leaves
"Moss"
moss 1
-grows on tree
-extends up tree, but gets sparser nearing the top
-dark and light green
-fuzzy
moss 2
-grows on and around roots of trees
-dark green
-fuzzy, and resilient
-2-3 inches thick/tall
"Lichen"
lichen 1
-light blue
-flat
-grows on top of moss and directly on tree
lichen 2
-white
-flaky
-grows in dots
"Fungi"
fungus 1
-black and brown
-on dead tree
-specimen probably dead itself
-had grown in chunks
fungus 2
-white
-isolated
-on one of the stumps
-porous

Total Number of Different Kinds of Plants: 19
Number of Different Categories: 3

I. Large/Trees
Criteria:
1. A definite visible trunk.
2. Ten feet or higher.
I. Mid-sized/bushes
Criteria:
1. Multiple branches low to ground base.
2. Between three and ten feet high.
I. Small/Ground coverings
Criteria:
1. Between ground level and three feet.

I.
A. Rough bark, one main truck, defined visible roots, branches sprout horizontally at relatively low on trunk. The leaves are in bunches and have five points.
B. Smooth bark, chipping , moss surrounds the roots, multiple large branches emerging from main truck vertically. Leaves are elliptically shaped with two points length-wise.
II.
A. Brown branches emerge from small bark. There are no leaves within the bush until about one foot at the end of branches. Leaves are sharp and thin, about an inch long. There are red berries with green seeds with clear slimy liquid inside. Redness indicates ripe. Berries smell bitter. Numerous pin-like leaves on each stem. Leaves do not grow on bark but outer branches.
B. Numerous branches on inside with leaves on the outside. The bush emerges from several large branches protruding from soil instead of one solid base visible above ground. Leaves branch horizontally and they are tear-drop shaped. They are a shiny dark green hue. The veins in the leaves alternated and some leaves were yellow. One of the bush of this type appeared to be dead. Only a few leaves were observed on this plant. Birds live in bush. A nest was observed.
C. Branches emerged from visible base. Leaves grow on thinner branches not on the larger ones that stem out. Three small leaves and two bigger leaves on each stem. Leaves are elliptically shaped with length-wise points.
III.

A. One stalk, leaves grow directly out of stalk, fuzzy flexible leaves, seed
pouches at top of stems. Green and brown oval pouches. The stalk was fuzzy.
B. Single stalk, leaves protruded from branches, leaf and stalk were fuzzy.
All small leaves, except one big leave coming from branch. Thin branch.

C. Thin branch, big leaves, white sprouted flowers at the tip of the stalk.
Leaves were smooth
D. Short, thin grass, brown and green, sprouting directly from base
E. Long grass, smooth, shiny texture, sprouting directly from base. Thick
grass, ridged.
F. Long, thin grass, sprouting directly from base.
G. Thin grass with small brown seeds. (new growth of seed) Light brown in
color sprouting from the top.

H. Long, thin, brown, vine, sprouting leaf bunches sporadically and far apart
on vine.
I. Fat, small, round leaves. Long vine with the leaves sprouting in pairs
along the vine.
J. Upside down heart shaped leaf, sprouting at far distances on the vine.
K. Three round leaves, sprouting in bunches of three.
L. Long, green, hairy, ridged leaves growing in clusters from base.
M. Round, green, hairy leaves growing in clusters from base
N. Moss, found at base of trees and in large patches/groups. Green at top,
brown at bottom, long, weak pieces, easy to separate.

Out side Observations

Moss and Lichen:
-three types of moss:one type on ground around root structures of tree #1 and different around #2, one around base of rock on pedestal
-moss on ground grew in mass of circular patches with brown spots, like a carpet of tufts
-moss on tree didn’t grow as tall as moss on ground
-small light patches of springy hairs on base of tree #1
-small dark patches around bark of tree #1, concentrated toward shadier side
-moss on rock: dark green textured substance, grows in various concentrations on rock’s surface, there are no leaves or visible stems, and the moss is more concentrated around more jagged and crevice surfaces on rock.
-Lichen: small mint green splotches that grow all over the bark of tree #1 and partially on tree #2.

Trees:
Tree #1:
-tall, wood
-rough exterior
-covered with thick textual bark
-bark is grayish/brown with white on exterior
-branches are small to medium and grow more thickly at middles and top of tree
-50 to 60 ft. high
-3-5 ft. in diameter
-alive
-branches branch out from trunk at almost 60 degree angle and grow up and out
-sturdy bark, doesn’t chip or flake away
-covered with moss internitently, more towards bottom
-tree grows up but leans to one side
-branches start 1/3 up trunk. About 12 ft off ground
-very leafy and bright green
-leaves: five points, serrated edge, veined (five large, many small), earthy, fresh smell, small stem, wax paper feel, medium durability

Tree #2:
-smooth, papery bark except where it has begun to peel away
-dark greenish gray bark; where peeled away yellow/orange, raw –looking
-much more peelign away towards base
-moss starts at base, no moss on actual trunk
-ht. 50-60 ft tall
-5-6 ft. diameter
-branches grow up and out
-because they grow up, leaves don’t start until halfway up trunk
-leaves: pointed, serrated edges, elongated oval shape, green, thin stems

Shrub:
#3,5,6,8
-small, oval, smooth leaves (mostly green, some yellow growing off many smooth branches originating from central point on ground, which branch off further, leaves are darker on top than below and shiny on top as well. Scattered throughout the leaves are a few light green round solid things, smaller than the leaves and with a protruding dot at one end. Specimen 6 appears similar but has sparser branches with less leaves, and some leaves are a darker green, almost brown on shrub #8 some leaves had strange bright green spots which could chip off. Based on the shape and size of the brown plant it seems to be the same type. Only on small section has branches with leaves like the others though. The rest has almost no leaves, and the leaves that are there are brown.
#2,4,7,9
-long thin branches, on the tips of which are bristly leaves very small and thin but textured.
-small red berries with greenish centers
-branches out form the center
-smaller than a tree
-ground beneath covered with deep green moss and dead leaves
-classified as a bush because it grows closer to the ground that the trees
-branches out earlier from the root
#4 has a few branches of leaves that are brown, there are various shades of green
-in terms of little round colored berries on the branches- there are some that are small and deep green not the color of the leaves
-there are some that have a hard outer red covering with green sticking out
-there are some that are completely covered by the red except for a hole in the bottom
-red outer cover soft squishes to the touch
-there are some brown leaves on the branches that are clearly not part of the plant but seem top be attached somehow
-ground underneath covered with leaves of the same type which are darker brown grows under tree
-stubby growth shorter than trees found on ground
Bush #1
-A woody shrub about six feet at the highest branch. Main trunk about 5 inches in diameter,. Branches at a height of about 7 or 8 inches. Trunk is nearly bare of outer bark until a couple of inches beyond branches. Leaves are pointed ovals from about 1/4 to 1 and 1/2 inches in length, arranged in clusters radiating from a central point. At each branching, several branches radiate from a central point; this pattern is repeated until the branches terminate in leaves. At terminal branches where leaves originate are the dessicated remains of flowers about 1/3" in diameter each with 5 petals surrounding a brushy center. Filaments about an inch long grow out of the center of the flowers.

Grasses
--Four different types
-#1 Most prevalent, grows over entire area of island, in clumps close to the ground, grew at the bases of other grasses.
-#2 Thicker, sprouts up from the ground, grows over entire area of island but not as prevalent as #1 stands taller than the first type of grass.
-#3 Thinner than #2, but not as thin as #1, more sparse than #s 1, 2.
-#4 Least prevalent, grew only behind the bushes, all brown, only grass with obvious seeds, tallest of all the grasses.

11 different types of low to the ground plants with rounded leaves
-two of them had fruit which was evident on the growth
-most prevalent was three rounded leafed plants which covered entire area of island(clovers)
-found more than one specimen of everything except one plant which had smooth, thick jagged edged leaves, and a thick spine.

--We found two types of plants that were small with woody stems which we classified in a category by themselves as bush like growths which might later grow into trees.

Conclusion--All together we found twenty three different specimens. Basically, this is how we classified them:
Plants
/ \
bark no bark-------\
/ / \ \ \ \
Trees ambig.bushes moss/lichen grasses
/ \ /\ \ / \ / \
tree#1 tree#2 1 2 3 wide stalks flowered
leaves

This was as indepth a study we could do with the information and tools provided, further research might lead to different, better summaries of observations.

Tuesday Lab #1

Ilyssa Fisher

Emi Arima

Leah Rayner

Heather Shelton

Rebekah Rosas

1. Mosses

Moss- very small, less than 1 cm high. No visible trunks or stems.

Type one




The first type is about 1 cm tall and occurs in large patches of tiny, pointy, dark green leaves of about 3mm. These leaves are found bunched together in tiny star-shaped clusters. This type tends to occur around the base and roots of a tree.

Type two




This type is a lighter green color. It also occurs in smaller patches than type 1. It contains a lot of individual leaves which are long and narrow, about 4mm. The leaves are soft. This type also is found mostly around tree trunks and roots.

Sprouts




We found six various sprout type, most of which originated from one main stem. Some of which looked as if they could have been young versions of the great trees and bushes on the island.

1.One main stem on which grew a five pointed leaf. Each section of the leaf had a separate vein.

2. Vine type plant which grew along the ground in a long stem, many small leaves attached to main stem.

3.Growing near the tree were small sprouts, resembled that of the tree with similar leaf and bark patterns.

2. Single stemmed thin plant, 1.5 mm diameter up of 5 inches tall. Single leaf which is pointy and fan-like.
3. Single stalk up to 24 inches in height. Few leaves, long pointy clusters of seed balls about 4 mm in diameter.



4. Single stem — three round leaves sprouting from stem.

Names:

Neema Saran
Rebecca Roth
Sana Dada
Deb Charamella

Lab: Wednesday, 1-4pm

While on the island, we observed various forms of plant life. In fact, eleven, we observed in total. We looked at size, texture, shape of leaves, fruits, and color among other things.
We divided the plant life into four categories. Namely, shrubs, grasses, weeds, and trees. To categorize a plant as a shrub, it had to be fairly wide in circumference (between 6 to 8 feet in height). Grass and weeds are under a foot and grow from the ground. Trees had a wide circumference and branches were growing from their trunks.

Observations
Shrubs:
#1:
Size of leaf: approximately 1" long
Thin branches
Texture: fuzzy
Height: approximately 6 feet
Small buds growing on leaves
# 2:
thin, needle-like leaves
has red berries
thin branches, pointing upwards
Height: approximately 8 feet tall
Rounded shape overall
#3:
Shiny, round leaves
Approximately 2 cm long
Size: approximately 6 feet tall
Round shape
Thin branches

Grasses:
#1:
long and stringy
yellow-green in color
grows in clusters
height: approximately 1 foot tall
#2:
Long and thin
Green stem
tanned at the bottom
delicate

Weeds
#1:
Size: approximately 8 inches high
Has a main stem
5 pointed leaves
#2:
Size: approximately 2 inches long
Ridges on leaves
Leaves are one inch wide
One leaf on each stem
#3:
heart-shaped leaf
approximately 2 inches long, and 1 inch wide.
#4:
three-leaf clover
very small
approximately 1 inch long
leaves are speckled

Trees:
#1:
4 foot circumference of trunk
thick roots
oval-shaped and pointed leaves
approximately 30 feet high
chipped bark
#2:
approximately 3.5 foot circumference
abundant roots
crevices in bark
five-pointed leaves
approximately 30 feet high
Brown, prickly acorn-like "fruit"

Conclusion:
Through this lab assignment, we gained a greater appreciation of the ecological diversity around us. Just within a 50 foot space, we observed numerous types of plant growth. Despite the many differences that we observed among plants, we were able to find similarities that helped us to characterize them into categories of classification.

Akudo Ejelonu

Joelle Webb

Savithri Ekanayake

Helena Salles



Wednesday 1-4pm

Biology 103

Lab 1 - 9/19/01

Classifying Plants

Total number of different kinds of plants: 12 total specimens*
- 2 types of trees
- 2 types of shrubs/bushes
- 4 types of grass
- 4 types of moss

Number of different categories: 3 categories

Names of categories:
- Plants that are firmly rooted in the ground
- generally trees and shrubs
- Plants that grow on top of other things (indirect contact with soil)
- moss variations
- Plants that expand outward/cover large surface area but did not extend far vertically
- grass and weeds/small independent foliage

Criteria which distinguish each category:
- The first category, plants that are firmly rooted in the ground, had roots exposed above the surface. They also demonstrated resilience when challenged by outside forces; sturdy branches and trunks.
- The second category, plants that grow with indirect contact with the soil, were found along the bark of trees in sparse clusters, with little exposure to sunlight. In addition, their growth patterns followed the contours of the tree.
- The third category, plants that expand outward/cover large surface areas but did not extend far vertically, in contrast to the first category, had pliable stems as opposed to sturdy branches and trunks.

*(Note: These 12 plants are merely the specimens we were able to observe in the time allotted).

Wednesday lab section

Total number of different kinds of plants: 12 species registered, but more found
Number of different categories: 3 categories
Names of categories: groundcovers, shrubs and trees
Criteria which distinguish each category: direction of growth

Groundcovers: plants that grow outward (spread) on the ground as opposed to growing upward.
No branches
Colors: Light Green, dark green, yellow leaves and stems
Roots underground
Stems underground and above ground

Shrubs: plants that grow up and outwards
has trunk, bark less trunk mass than trees, leaves grow closer to ground than trees
Fruit bearing
Branches
Dark green leaves, brown bark, red fruit
Roots underground
Leaves: shiny, waxy, fuzzy, needle like, jagged edge, round

Trees: grow upwards and branch out
Nut bearing
Has Bark
Light green leaves, brown, light and dark green bark
Roots above and below ground
Leaves: jagged edge, five pointed

Jessica Kiefer

Leah Rayner

Samantha Carney
Sasha Karlins

Bio Lab #2

Hypothesis: Do large multi-cellular organisms have more cells than small multi-cellular organisms?

We collected the following organisms from outside making approximations of their actual size.

Organisms: Tree (approximately 50-60 ft. in height); sample: leaf
Lichen (approximately 1 cm); sample: one clump
Grass (approximately 5 in.); sample: one blade

Using microscope, we approximated the size of the cells using the collected samples.
Tree: (at 40x) 11 * 2.5 µ = 27.5
Lichen: (at 40x) 9 * 2.5 µ = 22.5
Grass: (at 40x) 22 *2.5µ = 55.0

There seems to be no relationship at all between the size of the organism and the size of the cell. The largest organism, the tree, had neither the largest nor the smallest cell size. This indicates that there is not a direct correlation, or even an indirect one, between cell size and organism size.

Ilyssa Fisher

The purpose of this lab is to increase our knowledge of microscope usage as well as to test the following hypothesis.

Our hypothesis was that cells of large organisms would have larger cells than cells of smaller organisms. Our tests involved three specimens:

1. A tree approximately 35ft tall.
2. A small plant approximately 10 cm tall.
3. A collection of moss approximately 2 cm in length.

After examining the specimens under a microscope, we discovered the sizes of the cells of each plant to be as follows:

1. 1 tree cell = 35um
2. 1 small plant cell = 30 um
3. 1 moss cell = 10um

Due to our test, our observations supported our hypothesis to the best of our knowledge.

Lab #2:Cell Size vs. Organism Size

Purpose: To examine the correlation between cell size and organism size in common plants.

Hypothesis: The size of multi celled organisms is directly correlated with the size of the cells that comprise the organism

We took samples of various leaves and measured their cells with the aid of a microscope. We took two different tree leaves, a cross section of a grass blade and the leaf of an evergreen bush, and compared the lengths of their respective cells.

The following is the data that we collected at 40x:

Grass: 30 µm
"Ground leaf": 20.8 µm
"Tree Leaf": 30 µm
"Bush Leaf": 52 µm

We found that the smallest leaf had the longest cells. This disproves the hypothesis that the size of the organism has any correlation with the size of the cells. Some of the difficulties we found in measuring the length. The cells in the second tree leaf had irregular edges, which made it hard to determine its length, whereas the leaves of the evergreen was comprised of long, thin rectangular cells. Therefore, one deciding factor of organism size and shape could have to do with the shape of the cells as opposed to their respective lengths.

Tuesday Lab
September 25, 2001

Microscope Lab

Purpose: To determine whether an organisms size is related to its cell sizes.
Hypothesis: Organism size is related to cell size

Data:

Tree: 15 m tall, 12 m wide
Tree cell: 52um by 26um, 46.8um by 18.2um, 39um by 39um
(avg. 45.93um by 27.73um)

Bush: 3 m tall, 2.5 m wide
Bush cell: 41.6um by 46.8um, 39um by 36.4um, 39um by 26um, 57um by 26um
(avg. 44.2um by 33.8um)

Clover: 3 cm tall, 1 cm wide
Clover cell: 39um by 20.8um, 39um by 26um, 26um by 31.2um, 15.6um by 28.6um
(avg. 29.9um by 26.65um)

Procedure:

We first took samples of each of the specimens and then measured them under a microscope. The measurements we took had to then be converted from recticle units into micrometers. Since we used 40x, we multiplied the number of recticle units by 2.6 to get the amount of micrometers.

Conclusion:

Though the clover cells were marginally smaller than the bush and tree cells, it was not significant enough to prove the hypothesis. Also, the tree and bush cell sizes did not differ much. Therefore we conclude that our observations would contradict our hypothesis.
However, due to the imprecise nature of our measurements, it is difficult to draw a strong conclusion. More trials with perhaps better measuring would be needed to make a better conclusion.

Claudia Ginanni

Hypothesis : Big Mulitcellular Organisms vs. Small Multicellular Organisms
Do big multicellular organisms have more cells in quantity than small multicellular organisms or do big multicellular organisms have bigger cells than small multicellular organisms? Is the size of organism proportionate to the cell size?

The purpose of this experiment was to determine whether cell size and organism size correlate.
Procedure: We collected three different organisms outside and approximated the size of the organisms. We then came inside and put small shavings of the organism on a slide and under a microscope. We then measured the cell size and converted the reticle units into micrometers.
Data:

Organism #1 Bush

At 400 magnitude
(40x10)

The size of the bush was approximately 8 length feet by 7 feet width.
The cell size of the sampling was 20 reticle units.
20 x 2.5 = 50 micrometers

Organism #2 Moss
At 400 magnitude
(40x10)

The size of the moss 1/4 inch.
The cell size of the sampling was 5 reticle units.

In the microscope we were able to see green globs which were choloroplast.
5 x 2.5 = 12.5 micrometers

Organism #3 Long thick grass
At 400 magnitude
(40x10)

The size of the long blade of grass was 8 inches.
The cell size of the sampling was 20 reticle units.
20 x 2.5 = 50 micrometers

Conclusion : The size of the organism does not correlate with the size of the cell. We can conclude this because the long thick grass was only 8 inches in length and the cell size was 50 micrometers, whereas the bush which was 8 feet in length also had a cell size of 50 micrometers.

How do the size of organisms relate to the size of their cells?

Purpose: To make observations of living organisms and their cells in order to come to a conclusion about our hypothesis. (Ideally proving it wrong).

Hypothesis: Larger organisms have larger cells.

Data:

Specimens

--Grass
-8 inches long
-3/4 inch wide
- Cells were 88.4 micrometers long and 3.64micrometers wide

--Tree
-35ft tall
~ 35 ft in diameter
cells were 39 micrometers long and 10 micrometers wide

--Bush
5 ft tall
5 ft in diameter
Cells were 26 micrometers long and 2.6 micrometers wide

Conclusion:

Our data shows that the size of the organism did not necessarily effect the size of the cell. Although the grass was not the largest organism we observed, its cells were the largest.
The cells of the tree, which was the largest organism we observed, were far smaller than those of the grass cells.
This contradicts the idea that larger organisms have larger cells.
Also the cells of the grass were far bigger than the cells of the bush.
The grass cells could have been irregular causing them to be larger.
The grass cells did have irregular borders but we measured the edges consistently.
The difference between the cell size of the tree and the cell size of the bush is minimal.
We think that our observations thus far refutes the hypothesis that larger organisms have larger cells.

Purpose:
The objective of this lab was to use a microscope to observe various sized plant cells of different sized organisms and to observe whether or not the cell sizes are proportional to the size of the organism.

Hypothesis:
Our hypothesis of this lab was that cell sizes are proportional to organism size. We hypothesize that for all the organisms that we will observe the cell size will be relatively proportional in size to the size of the organism.

Materials:
Microscope
Slides of different living organisms

Procedure:
Using different slides of various sized organisms, we placed each slide under a microscope and observed the cells at a magnification of 4x, 10x, and 40x. We took measurements of several cells from each specimen at 40x and then averaged them for each of the four slides we observed. We took the reticle measurements and then converted the reticle measurements to micometers.

Data:
2 inch Clover Leaf Cells :
Cell #1: 21x15 reticle units = 52.5x37.5 um

Cell #2: 23x13 reticle units = 57.5x32.5 um

Cell #3: 28x11 reticle units = 70x27.5 um

Cell #4: 22x14 reticle units = 55x35 um

Average cell size: 58.75x33.13 um

8x1/2 inch Grass Blade Cells:
Cell #1: 28x10 reticle units = 70x25 um

Cell #2: 28x12 reticle units = 70x30 um

Cell #3: 25x12 reticle units = 62.5x30 um

Cell #4: 34x13 reticle units = 85x32.5 um

Average cell size: 71.88x29.38 um

60 Foot Tree Leaf Cells:
Cell#1: 28x12 reticle units = 70x30 um

Cell #2: 21x18 reticle units = 52.5x45 um

Cell #3: 21x16 reticle units = 52.5x40 um

Cell #4: 20x18 reticle units = 50x45 um

Average cell size: 56.25x40 um

Cheek Cells:
Cell #1: 27x20 reticle units = 67.5x45 um

Cell #2: 25x13 reticle units = 62.5x52.5 um

Cell #3: 22x17 reticle units = 55x42.5 um

Cell #4: 23x20 reticle units = 57.5x50 um

Average cell size: 60.63x47.5 um

Conclusion:
We concluded from our observations that our hypothesis is incorrect. The size of the cells that we observed were not proportional to the size of the organisms themselves. We found that there was no correlation between size of cell and size of organism.

Lab Report #2:
Cell Size

Purpose – Question:
-The purpose of this lab was to determine whether or not cell size increases relatively to the size of the specimen being measured. Also we wanted to see if the quantity of cells increased as specimen size did.

Hypothesis:
-We thought that the bigger the specimen was the greater the size of the cells. We also thought that the bigger specimens would consist of a larger quantity of cells.

Data:
We collected samples of three different specimens. Our first sample is a leaf from a 30foot tree. The leaf size was 3 and a half inches by 3 and a half inches. The second specimen was leaf from a bush. The bush was 6 feet tall, its leaf was 1 inch by 1 and a half inches. The third sample was a 12 inch tall blade of grass.

We made slides and measured three cells of each sample. The tree cells ranged from 65-50ums. The bush cells ranged from 20-25um, and the grass cells ranged from 50-70um.

Agree – Disagree With Hypothesis:
Our data does not agree with our original hypothesis. The reason we don’t think that it corresponds is because our grass samples turned out to have the most number of cells even though they were the smallest specimen that we measured. As far as the bush and tree measurements go, we think that they matched our hypothesis.

Lab #2

Purpose
To determine what makes big organisms big and what makes smaller organisms smaller.
Hypothesis
Big organisms and small organisms have similarly sized cells, but the larger organisms have more cells. Leaves with a darker color have smaller cells.
Data
Clover Leaf
2inches high with stem and about .5cm by .5cm with the leaf
cell#1=6 retricle units
cell#2=3.5 retricle units
cell #3= 5retricle units
average=12.08 micrometers
Maple Leaf
Tree = 40ft
Cell #1= 2retricle units
Cell #2= 5units
Cell#3= 3 units
Average cell=8.3micrometers
Moss
Height=4mm
Cell=10 retricle units
Cell#2= 7retricle units
Cell#3= 9retricle units
Average=21.66 micrometers
The data we found agrees with the first section of the hypothesis. The cells are generally similar and size. However, the color of the leaves did not match our hypothesis

The purpose of this lab was to look at cell sizes of different sized plant life in order to see the relation (if any) between cell size and organism size.
The first hypothesis was that larger organisms have more cells than smaller organisms, and that is what led to their greater size. The second hypothesis was that all organisms have the same number of cells, and that it was the size of the individual cells that caused the organism to have a greater size.
We collected samples from three different plants.
The first cells that we looked at came from a clover leaf. We scraped part of the leaf off and looked at it under the microscope.
6x10um= 60um
6x10um=60um
5x10um=50um
Avg=56.67 um
The next cells we looked came from a saw tooth shaped leaf (smallest sample we looked at). We scraped that as well.
4x10um=40um
2x10um=20um
4x10um=40um
Avg= 33.33 um
The last cells that we observed under the microscope came from a red leaf plant (biggest sample we looked at).
16x 2.5um= 40um
17x 2.5um= 42.5 um
12 x 2.5um= 30 um
Avg. = 37.5 um
Conclusion: We agree with the hypothesis that states that larger organisms have more cells than smaller organisms as opposed to the idea that all organisms have the same number of cells but larger organisms have larger cells. Our set of observations show that no matter what the size of the plant sample was, they had roughly the same size cells.

Lab report Wednesday September 26, 2001

Question: What accounts for differences in organism size?

Hypothesis: The Size of an organism does not directly correlate with the size of the cells that make it up. In other words, an organism’s cell size does not increase as an organism’s size increases.

Data: 3 specimens

Specimen 1: tree leaf
Measurements of organism: 15 meters high and 8 meters wide
Average measurements of cells: 37 um x 17 um
Reticle Units
Width 8, Length 10
Width 16, Length 14
Width 10, Length 12
Width 6, Length 20
Width 13, Length 18
"Jigsaw puzzle" shaped cells

Specimen 2: shrub
Measurements of organism: 2 meters high and 2 meters wide
Average Measurements of cells: 55 um x 50 um
Reticle Units
Length 18, Width 26
L 11, W 24
L 33, W 21
L 18, W 22
L 16, W 25
"brick-like" rectangular shaped cells

Specimen 3: human
Measurements of organism: 1.6 meters high and 0.4 meters wide
Average Measurements of cells: 65um x 65um
Reticle Units
Length 25 ,Width 30
L 32, W 18
L 20, W 32
L 27, W 18
L 25, W 30
"Jagged diamond" shaped cells

Cl:

We found that our observations agreed with our hypothesis in that organism size does not directly increase with cell size. Rather, we found that the larger the organism, the smaller the cell size.

Our lab question is what accounts for differences among organisms and if differences in cell size are related. The purpose of this lab is to find out if the cell size corresponds to the number of cells in the organisms. The hypothesis is that if a plant is large, it will have many more cells than a small plant and it’s cells will be relatively smaller. We compared the size of the cells in three organisms: bush, leaf and grass. Our results are as follows:

TREE CELL (50 foot) length-30 micrometers, width-15 micrometers, area- 450 um
GRASS (8 inches) CELL length-36 micrometers, width-6 micrometers, area-216 um
BUSH CELL (6 feet) length-21 micrometers, width-15 micrometers, area-150 um

Upon examining the data, we found no direct correlation between the length and width of the cells and the actual size of the organism. However, when we calculated the area of the selected plant cells we found that the plant with the largest leaf, the tree, had the biggest cell area. Additionally, the smallest plant leaf in our data set had the smallest cell area. The hypothesis was not proved by our observations. Let us also mention that the leaves we used were full size, representing a mature part of the sample plant. There were several factors that might have affected the precision of our results. First of all, the cells were not rectangular and second of all the specimens were very difficult to make into slides and could have been damaged in the process.

Accounting for Differences in Sizes

We wanted to find out what accounts for differences in size of various living organisms, since as most of us observed from the previous lab session , size is generally observed to be a relatively easy form of categorization of organisms.

We started out with one hypothesis,
cells in larger organisms are comparatively bigger when compared to smaller organisms.

First of all we selected three living organisms of three different sizes.
1. A Tree of about 30ft
2. A bush of about 5ft
3. A 1.5inch clover ground plant
We decided to examine the cell sizes of these above mentions living organisms by taking as sample three leaves from these plants,since leaves were found to be a good method of observing cells and cell structure of the plants as they are 'soft and mushy'.

Our findings are as below.(these are the average cell areas of 3 cells ,given in micro meters)
Tree leaf: 35.75* 25
Bush Needle: 8.25*5.4
Clover leaf: 16.5*37.5

We found that the hypothesis did not apply to our observations, as the clover which was comparatively smaller than the bush actually had much larger cell sizes than the much larger bush. However the tree which was the biggest of all 3, had much larger cell sizes when compared to the other two,but then again there was not a huge difference between the cell sizes of the 30ft tree and the 1.5 inch clover plant. However this does not prove or disprove the hypothesis definitely,since we might have to carry out more observations,as our findings are limited to the 3 plant specimens we selected.

Question: From a structural standpoint, what accounts for difference in organismal size?

Hypothesis: 1. All organisms are made of roughly the same amount of cells, but larger organisms have larger cells.

Data:
Tree leaf cell size in um(tree approximately 45-50 feet tall):
Cell 1: length: 62.5 width: 45
2: length: 22.5 width: 15
3: length: 37.5 width: 45
4: length: 32.5 width: 57.5
5: length: 52.5 width: 47.5
average length: 41.5 average width: 42

Grass cell size in um (grass approximately 9 inches tall):
Cell 1: length: 37.5 width: 25
2: length: 57.5 width: 30
3: length: 30 width: 25
4: length: 55 width: 40
5: length: 37.5 width: 30
average length: 43.5 average width: 30

Moss cell size in um (moss approximately 1/2 inch tall)
Cell 1. length: 22.5 width: 15
2. length: 17.5 width: 20
3. length: 22.5 width: 25
4. length: 17.5 width: 25
5. length: 25 width: 20
average length: 21 average width: 21

Conclusion: Cell length in the two plants are very similar, although their widths vary. Perhaps the moths’ cell lengths different because it is not a plant. This is too small a study to conclude anything, but our limited data suggests that perhaps a combination of cell size and cell quantity determine organism size.

Names: Helena Salles, Ilana Moyer, Julie Wise

Purpose: To determine what accounts for drastic size differences between organisms.

Hypothesis: This drastic difference in size is due to larger organisms having larger cells than smaller organisms.

Data:
Organism Type: Clover
Original Size: approximately .5 inches
Magnification Level: 40X
Cell #1: 17.5 micrometers, Cell #2: 20 micrometers, Cell #3: 15 micrometers
Average Cell Size (of 3 sample cells): 17.5 micrometers

Organism Type: Evergreen Bush (cell samples taken from pine needle/leaf)
Original Size: approximately 6 feet
Magnification Level: 40X
Cell #1: 30 micrometers, Cell #2: 50 micrometers, Cell #3: 27.5 micrometers
Average Cell Size (of 3 sample cells): 35.83 micrometers

Organism Type: Tree (cell samples taken from tree leaf)
Original Size: approximately 50 feet
Magnification Level: 10 X
Cell #1: 350 micrometers, Cell #2: 390 micrometers, Cell #3: 490 micrometers
Average Cell Size (of 3 sample cells): 410 micrometers

Findings:
Our data supports our hypothesis: the difference in size among organisms is due to larger organisms having larger cells than smaller organisms. From our observations, it seems as though cells from larger organisms (such as the tree) tend to be larger in size than the cells of smaller organisms (such as the clover). The evergreen bush, situated somewhere between the clover and the tree in size, also had cells of a considerably larger size than the clover, yet significantly smaller than those of the tree.

Hypothesis: We proving that water molecules move at the molecular level.

2 mm beads: After minute one........... 4 reticule units
After minute two..........5 reticule units
After minute three........6 reticule units
After minute four.........10 reticule units
After minute five............10 reticule units

4 mm : After minute one.............0 reticule units
After minute two..............1 reticule units
After minute three.............1 reticule units
After minute four.............2 reticule units
After minute five...............2 reticule units

8 mm: After minute one...............0 reticule units
After minute two...............1 reticule units
After minute three..............1 reticule units
After minute four...............1.5 reticule units
After minute five................1.5 reticule units

When an outside substance is added, like sodium chloride, the cell walls of the onion are broken down because there is more water inside the cell walls and it needs to balance out with the ratio, so it breaks. Water will go from a high concentration to a low concentration to balance out the concentration grade.
When we took a tissue and wiped up the sodium chloride, and added a drop of water, the cells re-hydrate and the cell walls become normal again.

Biology 103
Tuesday Lab
October 9, 2001

Today's Lab focused on the movement of microbeads in water, measured in reticule units. We observed two different types of sizes: 8 and 4 reticule units. However, we had difficulty finding moving microbeads in the size 4 reticule units. We were only able to observe that size for 3 minutes. Nevertheless, using the class, as a whole's data, we find that the hypothesis holds true, since the 2 micrometer size beads moved the most. It was interesting to find that the 8 micrometer cells moved more than the 4 micrometer size, which also disproves the hypothesis.

At the 8 micrometer size, we observed the microbeads moving at:

1 minute--10 reticule units (ru)
2 minutes--9 ru
3 minutes--10 ru
4 minutes--12 ru
5 minutes--9 ru

4 micrometer size:

1 minute--25 ru
2 minutes--22 ru
3 minutes--30 ru

We feel as though our observations are incorrect because the four micrometer size moved so much. This could be due to the fact that we placed too much water on the slide, or when we pressed the cover slip down, we caused a current to occur.

Onions:

We also had the opportunity to observe onion cells. At first we looked at them in water. Next we put a solution of 20% Sodium Chloride. This caused the cell membranes to shrink. This showed us that where there was an area of many molecules of water, they would move to an area of fewer water molecules. Next we removed the NaCl and replaced it with distilled water onto the slide. This rehydrated the cell membranes by the balance of water both within and out of the cell membrane.

October 9, 2001

Microbeads

Hypothesis: Bigger microbeads will move slower and smaller microbeads will move more quickly at room temperature when suspended in water.

Methods: Prepare slides of 2µm, 4µm, and 8µm microbeads suspended in room temperature water. View the slides at 400x magnification (10x on the lens and 40x additional.)

Observations:

2µm beads
1 minute: 11 units
2 minutes: 23 units
3 minutes: 31 units
4 minutes: 39 units
5 minutes: 51 units

4µm beads
1 minute: 2 units
2 minutes: 4.5 units
3 minutes: 8 units
4 minutes: 9 units
5 minutes: 9.25 units

8µm beads
1 minute: 8 units
2 minutes: 12 units
3 minutes: 18 units
4 minutes: 18 units
5 minutes: 18 units

Discussion: All molecules are involved in random motion. It is intuitive to think that smaller beads will move more slowly than larger beads because the molecules are moving in the same random motion. However, our findings and the findings of the entire class do not support the given hypothesis. Still, this does not mean that the hypothesis is not correct. Because we are looking at random motion, a very large sample is necessary to thoroughly understand whether or not the hypothesis is supported. A possibly reason for the very large area covered by the 2µm bead is that there may have been some sort of current in the 2µm slide caused either by an air bubble or by vibrations from the table that caused the horizontal shift in the bead’s motion. The difference in area covered by the other size beads could simply be due to the randomness of motion.

After completing the experiment with microbeads we looked at what happens as onion cells are immersed in different solutions. We first viewed the onion cells immersed in water. We then observed how the onion cells changed when immersed in a sodium solution. The water from the cells distributes itself throughout the sodium solution, breaking down the cells. The reason the water moves throughout the solution is random motion and probability. The water distributes into the sodium solution because there is a greater amount of water in the onion cell than in the solution surrounding it. After viewing the onion cell immersed in a sodium solution we then looked at how it would change if we immersed it in water again. The onion cells were rehydrated again because of random motion and probability. There was a greater amount of water outside the cell so it disbursed throughout the cell.

Both experiments demonstrate the property of random motion in molecules. We were able to identify the random motion by viewing the movement in the microbeads and the onion cell walls.

Hypothesis:
In a solution, the smaller beads experience more motion than the larger beads.

Purpose:
To observe the molecular motion of water.

Procedure:
We prepared slides with 2, 4, and 8 um bead solution. We then examined them under the microscope and followed the motion of a single bead in each solution for a total of 5 minutes. We took measurements every minute.

Observatioms.
The 2 micrometer bead moved over a range of 15 reticle units.
The 4 micrometer bead moved over a range of 3 reticle units
The 8 micrometer bead moved over a range of .5 reticle units

Conclusion:
Our observations proved our hypothesis that the smaller beads would move over a larger range than the larger beads, in the 5 minutes.

Onion Experiment:

Procedure:
We prepared a slide using one layer of an onion (one layer of cells) and observed what the cells looked like. We then added a drop of NaCl solution to the slide and observed the change. Then we dried the NaCl solution from the slide and added several drops of distilled water to the slide and observed the change.

Observations:
After placing the NaCl solution on the onion slide, the cells appeared to "shrivel up". When we added the water, the cells returned to their regular state.

Conclusion:
The onion experiment shows how water moves along a concentration gradient. Molecules spread out randomly. Because they move randomly, they tend to move apart (laws of probability).

Hypothesis:
Our hypothesis was that as the size of the microbeads increased, the distance travelled by the beads would decrease.

Data:
Microbeads at 2 um
Minute 1: 10. ret. Units
Minute 2: 0.0 ret. Units
Minute 3: 0.0 ret. Units
Minute 4: 5.0 ret. Units
Minute 5: 2.0 ret. Units
Total Distance after 5 min: 17 reticle units

Microbeads at 4 um
Minute 1: 2.3 ret. Units
Minute 2: 1.5 ret. Units
Minute 3: 1.8 ret. Units
Minute 4: 0.2 ret. Units
Minute 5: 0.5 ret. Units
Total Distance after 5 min: 6.3 reticle units

Microbeads at 8 um
Minute 1: 0.0 ret. Units
Minute 2: 0.2 ret. Units
Minute 3: 1.2 ret. Units
Minute 4: 0.3 ret. Units
Minute 5: 0.2 ret. Units
Total Distance after 5 min: 1.9 reticle units

Conclusion:
Our conclusion after observing the microbeads was that our hypothesis was correct. As the size of the microbeads increased from 2 to 8 reticle units, the distance travelled by the microbeads did in fact decrease.

Part II.
For the second part of the lab we took samples of onion cells and observed them under the microscope. We then added drops of sodium chloride to the onion cells slide and viewed them a second time. It appeared that the cell membranes of the onion cells shrunk. We concluded that it was due to the replacement of water molecules with those of sodium chloride molecules. This helped to show a different type of molecular movement.

Motion
Question: Do items of a greater mass move less in water than objects with less mass?

Hypothesis: Microspheres with smaller mass cover more distance in water over time than microspheres of larger mass.

Procedure:
Microspheres of sizes 2, 4, and 8 were placed in water and observed under a microscope. One microsphere of each size was measured to determine how much distance (in one direction) it covered over 5 consecutive one-minute periods. Distances were measured in reticle units.

Observations and Data:

Microsphere of size 8 (first measurement):

Minute: Total Distance Traveled:
1 4.5
2 9
3 13.5
4 16.5
5 20.5

Microsphere of size 8 (second measurement):

Minute: Total Distance Traveled:
1 3
2 5
3 8
4 9
5 12

Microsphere of size 4:

Minute: Total Distance Traveled:
1 0.5
2 1
3 3
4 4.5
5 5.5

Microsphere of size 2:

Minute: Total Distance Traveled:
1 5
2 7
3 13
4 14
5 16

Conclusions:
The results from the 2micrometer microspheres were consistent with our hypothesis that the smallest of the objects would cover the largest distance. However, we found that in both trials for the 8 micrometer microspheres, their distances surpassed that of the 4 micrometer spheres. One notable characteristic of our results from the 8’s was that they traveled in one direction only (which implies that they may have still been affected from the movement of putting them onto the stage rather than their movement due to the water molecules). Perhaps with more trials we would find that the movement of the 4’s and the 8’s would be consistent with our previous ideas, but for now they are not.

To test why this type of motion is important we observed the affects of osmosis in an onion cell. By adding the sodium chloride solution to the exterior of the cell we created a conflicting concentration of water outside the cell as compared to inside the cell. This caused the water to move in the outward direction, and the cells began to shrivel up. Hypothetically by re-adding water we could have seen them fill back up again, but we think we may have done them in and damaged the cell membranes. We learned that thermal random motion will attempt to even out the unequal concentrations from in and outside the cell.

To test why random molecular movement is important we did a second experiment. For this experiment, we looked at a layer of onion cells under 10x with water, then water removed and sodium chloride applied, and then with sodium chloride removed and water reapplied.
In the first case, with the onion layer covered in water, we saw entire onion cells clearly, with the nucleus.
In the second case, after we removed the water and applied the salt solution, we observed the what looked like the cell walls breaking down.
In the third case, after we removed the salt solution, we observed the cells ‘fill out’ and return to their original form.
Data: The second experiment demonstrates unequal distribution and random motion.
In the first instance the water outside and within the cell was equal the molecules’ random movement resulted in the cell remaining the same.
In the second instance there were more water molecules inside the cell than outside. Water left the cell. Because more water molecules were moving randomly inside than outside the cell more water molecules left the cell than entered. The result was the shrinking of the cells.
In the third instance there were more water molecules outside the cell than inside so the opposite occurred, water molecules entered the cell more than left and the result was the ‘filling up’ of the cell.
Discussion: This second lab helped to illustrate the molecule motion we observed in the first experiment. We observed the property of unequal distribution and random motion tending towards chaos.

I. The motion of the spheres

We attempted to test the hypothesis that microscopic spheres in water are subject to constant bombardment by water molecules because of the thermal motion of the water molecules. It was predicted that because of their smaller mass, smaller microspheres would be propelled farther by such bombardment, and thus travel greater distances, than larger microspheres.

Our findings didn't conform to the prediction. A 4-micrometer sphere observed for five minutes moved a total distance of 7 reticule units during the time it was observed, while a 2-micrometer sphere moved only four units.

There could be a number of explanations for this phenomenon. Focusing the 40x lens sometimes forces the lens against the slide, which could account for some movement of the microspheres. Microspheres could become trapped against the glass cover and thus fail to move when expected to. Movement in only one dimension was measured; it is possible that there was vertical movement (that is, movement away from the lens) that was invisible to the observer.

The entire class's data was entered into a database that plotted the movement of 2-micrometer, 4-micrometer and 8-micrometer microspheres against time. On average, the class data more nearly conformed to the hypothesis than our data, although the prediction did not prove entirely correct. Although the 2-micrometer spheres were observed to move significantly farther than either the 4- or 8-micrometer spheres (which was consistent with the prediction), the average 4-micrometer sphere did not move as far as the average 8-micrometer sphere (which was not consistent with the prediction).

Thermal movement is random and therefore probabalistic, so the failure of our individual observations to conform to the prediction was probably not significant. A larger sample yielded a result that was closer to what was expected; perhaps the addition of the second lab group's data will bring it still closer to the expected result.

II. The Salted Onion

Next, we peeled a thin layer of tissue from an onion, added a drop of water, and observed it under a microscope. At 40x magnification, we were able to see the onion's cell's very clearly; the material inside the cells appeared to be moving around a bit. Then, with a Kim wipe that illustrates the fabulous adhesive property of water (not at issue in this experiment), we dried as much water as possible from the surface of the onion and replaced it with a 20-percent solution of sodium chloride. It was predicted by some observers that the onion would now be tastier, but observations to support that prediction could not be made through light microscopy.

We did observe that the motion we had formerly seen within the cells was no longer visible, and the contents of the cells appeared to have shrunk. The salt had apparently sucked most of the goo out of the cells. Why? The goo was composed primarily of water. Because the solution outside the cell membrane contained a far lower concentration of water than the contents of the cell, water molecules moved to fill the void.

The movement of the water molecules through the membrane illustrates the tendency of matter to become randomly distributed. That is to say that matter will always tend to move from a less probable (unevenly distributed) state to a more probable state of random distribution. Because the cell membrane is permeable by water, unequal distribution of water on either side of it was quickly remedied by the water molecules. When we tried to rehydrate the onion cells, the results were disappointing, which led to speculation that their dessication had been so abrupt as to puncture the membrane. The movement of water is essential to life, but there are times when organisms had best get out of its way.

The hypothesis was that in a given amount of time the smaller the bead the further a distance it would travel due to Browning motion, and the larger a bead, it would not travel as far.

Minutes 2 micrometer bead 4 micrometer bead

1 13 reticule unit (ru) 11 ru
2 20 ru 17 ru
3 25 ru 22 ru
4 30 ru 29 ru
5 35 ru 39 ru

The data at first supported the hypothesis, until the fifth minute of the 4 micrometer bead, where it picked up speed and surpassed the 2 micrometer bead. So looking at the data set as a whole, it would appear that the hypothesis is not supported. However, it may not be disproved either, due to the fact that the observations were not extensive, and the last sized bead (8 micrometers) was not even observed.

We wanted to see if the size affected the speed of the beads.We hypothesized that smaller sized beads would cover greater distance. This was a way of simulating water molecules and the distance that they travel.

We put two to three drops of h2o solution that had beads on the depression slide for each of the three beads. We tracked the distance using the ocular reticle ruler at 40x.
After every minute we recorded the area that it travelled.

2um (smallest)
1st min= 4 reticle units
2nd min=6 reticle units
3rd min=7 reticle units
4th min=8 reticle units
5th min=14 reticle units

4um
1st min=5
2nd min= 7
3rd min=8
4th min=12
5th min=16

8um (largest)
1st min=1
2nd min=2
3rd min=2
4th min=2
5th min=2

Conclusion: The data did not support our hypothesis. However, the 2um and 4um beads moved faster than the 8um. The 4um was moving quicker than the 2um. This could be due to a few reasons. For one, there is a lot of variation in measurements. The bead that we decided to focus on may have been moving quicker than the 2um we chose to focus on.

Brownian Motion Lab

Introduction: The purpose of this lab was to observe Brownian Motion in action and to determine whether or not small latex sphere would cover a greater distance in water than larger latex spheres.

Hypothesis: The smaller the latex sphere, the greater distance it will cover in water due to its size and the constant motion of the water molecules.

Observations: In observing the 2-micrometer spheres we noted that a single sphere moved approximately 19 reticule units in 5 minutes.
A 4-micrometer sphere traveled approximately 4.5 reticule units within 5 minutes.
An 8-micrometer sphere oscillated in place but did not travel any distance.

Conclusion: From our observations, our hypothesis agrees with the data. Smaller spheres did cover a greater distance than larger spheres.

Molecular Motion

Molecules are all around us; they are made up of various numbers of atoms that are in constant motion. The purpose of this lab was to explore the properties of life at the molecular level and make predictions about the motion of the beads under the scrutiny of a microscope. The hypothesis of this lab predicted that smaller beads would cover more area than the larger beads. This theory was based on Browning Motion which states that very small items that move when there is no outside force to move it are subject to the forces that are moving around it. In our experiment, the beads are analogous to the pollen particles observed by Browning.

In order to make observations about items that can't be seen by the naked eye we used tiny lab-produced latex/rubber beads in pools of water. We used three different sizes of beads which each measured 2 micrometers, 4 micrometers and 8 micrometers. We recorded the total distance that a single bead covered while experiencing random motion over a period of 5 minutes. The bead measuring 2 micrometers moved a total of 21 reticle units in the period of time allotted. 10 reticle units were covered by the latex bead, which measured 4 micrometers. The largest bead which measured 8 micrometers only covered 2 reticle units in 5 minutes. The observations we made did not include any space that was covered more than once.

Our hypothesis was correct because the smallest beads which measured only 2 micrometers covered more area than the beads which were 8 micrometers long. This is because the smaller beads are more susceptible to the moving water particles around it. We concluded that the physical property of molecular motion is constantly at work in our world today and that the tiniest particles are moving the fastest.

Do the size of the beads affect the amount of distance covered?

Hypothesis:
We assume that the smaller beads will cover a larger area while the larger beads with cover a shorter area due to the Browning motion’s reaction to different the mass amounts of the different beads.

Procedure:
We have 2 different solutions with 2 different sizes of latex beads in them. We take a drop of each solution and drop each of them separately into a well on the slides. Placing a slipcover on each of them, we observe them under a microscope under the magnification 40x for the duration of 5 minutes, recording distance covered per minute.

Observations:

2micrometers:

1 min- 3 reticle units
2 min- 3
3 min- 3
4 min- 4
Final result of maximum area traveled: 4 reticle units

4 micrometer beads

1 min- 3 reticle units
2 min- 4
3 min- 4
4 min- 5
5 min- 5
Final result of maximum area traveled: 5 reticle units

8micrometers:

1 min- 2 reticle units
2 min- 3
3 min- 3
4 min- 3
5 min- 5
Final result of maximum area traveled: 5 reticle units

Final Observations:
Our results show that the larger beads traveled somewhat greater distances than the smaller ones. The overall difference in distance traveled was not that great, with results such as 4 and 5 reticle units.

Our results did not seem to correlate with the results of the class. The whole classes’ results show support for our hypothesis. Most had observed that the smaller 2-micrometer beads traveled a greater distance than the larger 8-micrometer beads. These results correlate mass and motion (Browning motion) to distance/area.

Onion Cell Experiment:
We took one layer of onion cells and added Sodium Chloride to them. We observed the cell membrane shrinking from the cell wall and from this we can infer that water has left the cell. This is an example of diffusion through the Browning motion and the random motion of molecules caused the solution to flow into areas without by way of probable motion.

Wednesday Lab

10/10/01

Motion in the Molecular Level

Introduction:

We were given the question that if there is something small enough to be affected by water molecules, it’s movement can be traced even with no human interference (shaking the slide, table, etc.). We decided that since water molecules move with thermal energy, the warmer the water is will make the molecules move faster. Brownian motion states that water molecules are in constant motion, and we decided to prove that. If we took different sized latex beads, we could see if water molecules really moved. We decided that the smaller the bead, the easier it would be affected by the moving molecules, and thus would move faster than the larger beads and visit a greater area.

Method:

Part One:

Taking tiny pieces of latex beads, we mixed them with water and put them onto a slide. Their sizes were of 2 micrometers, 4 micrometers, and 8 micrometers. We then looked through a 40x magnification lens, which allowed us to follow the path of the beads in radical units. We took measurements of how far a bead moved during five minutes for each size, taking measurements every minute in between. The results were as follows:

2 micrometer beads:

1 min: 3 r.u.

2 min: 5 r.u.

3 min: 6 r.u.

4 min: 8 r. u.

5 min: 10 r. u.

4 micrometer beads:

1 min: 2 r. u.

2 min: 4 r.u.

3 min: 4 r.u.

4 min: 5 r.u.

5 min: 5 r.u.

8 micrometer beads:

1 min: .5 r.u.

2 min: .5 r.u.

3 min: 1 r.u.

4 min: 1 r.u.

5 min: 1 r.u.

Part Two:

We took an onion layer and looked at the cells under a microscope. We then cleared the slide and left the onion layer, adding a drop of Sodium Chloride onto it. The results were surprising. The cell membranes shriveled up within the cell wall, although the cell wall was intact. Due to diffusion,, the high concentration of water within the cell met with the low concentration in the Sodium Chloride outside the cell wall, therefore by random thermal motion the water diffused to the outside of the cell, causing it to shrivel.

Conclusion:

We found that Brownian motion can indeed be proved and that water is in constant motion. It is a probabilistic motion, both random and thermal.

Purpose: To measure the relationship between molecular size and movement, as it occurs in the environment of water.

Hypothesis: The Brownian Motion of the bubbles within the slide of water vary based on the size of the bubbles. For instance, the 2-micrometer bubbles move faster than the 8- micrometer bubbles, as smaller objects tend to have a wider and faster range of motion.

Procedure: A slide was made for two beads in water, of sizes 2 and 8 micrometers. For each bead, the range of motion was observed under the microscope at 40X magnification, for minute-long increments over a total of 5 minutes for each size.

Following this procedure for beads in water, we then observed onion cells (on slides) in water with sodium chloride.

Observations:
Bead Size: 2 micrometers Bead Size: 8 micrometers
Min 1: 10 retinal units Min 1: 0.5 retinal units
Min 2: 12 retinal units Min 2: 0.5 retinal units
Min 3: 12 retinal units Min 3: 0.5 retinal units
Min 4: 12 retinal units Min 4: 0.5 retinal units
Min 5: 13 retinal units Min 5: 0.5 retinal units

The range of motion of each size tends to increase with time. Our observations agreed with our hypothesis in that the smaller beads in water moved more quickly and cover more space over time than the larger beads in water.

For the onion cells in a sodium solution, we observed that the cells shriveled up when the water left the interior of the cell. Since there is so much sodium chloride in the solution, the amount of water molecules in any section of the sodium solution outside the cell is less than the amount of water molecules within the cell. Therefore, water will go from an area of high concentration to an area of low concentration because of thermal motion, creating a net movement of water leaving the cell.

Conclusion: The relationship between the two sets of observations is the repeated tendency towards chaos/random motion. The beads in water exhibited random motion, and the addition of sodium chloride to the onion cell caused the process of diffusion. Diffusion is the random motion of molecules moving from higher concentration to a lower concentration area. Therefore, both diffusion and Brownian Motion depend upon random movement.

We had to look at particles at molecular level and determine their characteristics of movement.

Hypothesis:
We think that smaller particles move faster than larger particles.

Method:
We examined 2mm beads and 4mm beads under a microscope and observed their movement for 5 minutes. Here is the data that we recorded:

Size #2 Beads:
Minute: 1 2 3 4 5
Distance: 5 15 23 25 27

Size #4 Beads:
Minute: 1 2 3 4 5
Distance: 3 5 8 9 10

Conclusion:

In the end, we learned that particles move at different speeds in water because of their density. During the time we were observing the beads, we realized that the beads gradually cover a greater distance as the time intervals increase. Also, we were able to view that the particles move in a random motion. The results we obtained supported our initial hypothesis.

Second Experiment:
For our second experiment we viewed an onion cell with water on it. We saw the set up of the cells. Then we dried the water off and put Sodium Chloride on the onion cell and viewed it under the microscope. We saw that the cell membrane shrinks when there is Sodium Chloride on the cell. This is because the water inside the cell is moving outward. It leaves because of the process of osmosis, this is when water moves from a high concentration to low concentration, until a balance is achieved. The water is in constant motion and since there are more water molecules inside the cells, some water is going to leave just because there is more room outside the cell than inside the cell. Basically the water leaves because of thermal motion and for the fact that it moves from a higher concentration to a lower concentration, or from a state of order to a state of disorder and randomness. Also osmosis occurs because the probability of obtaining a balance is greater than disorder. The two labs we performed today are related because in both we observed random motion create a balanced environment

Lab 10/23/01

Experiments:

1.
4.5 mL of buffer
0 mL of enzyme
0.5 mL of H2O2

(no oxygen produced)

TEMPERATURE EXPERIMENT

2. Control
1.5 mL enzyme
0.5 mL H2O2
3.0 mL buffer

Data:
Seconds: mL of oxygen:
15 .5
30 1
45 1.1
60 1.5
75 1.7
90 2.0
105 2.1
120 2.2
135 2.3
150 2.4
165 2.4
180 2.5

3. Cold
1.5 mL enzyme
0.5 mL H2O2
3.0 mL buffer

Seconds: mL of oxygen:
15 1
30 1.6
45 1.7
60 1.9
75 2.1
90 2.2
105 2.5
120 2.6
135 2.7
150 2.8
165 2.9
180 3.0

4. Hot
1.5 mL enzyme
0.5 mL H2O2
3.0 mL buffer

Data:
Seconds: mL of oxygen:
15 1.5
30 2
45 2.2
60 2.4
75 2.5
90 2.7
105 2.7
120 2.8
135 2.8
150 2.9
165 2.9
180 3.0

Purpose:
The purpose of this lab was to test the effects how varying the amounts of enzyme concentration would affect the speed of chemical reaction and amount of oxygen produced.

Hypothesis:
Our hypothesis was that as the concentration of substrate (H2O2) increased, while our enzyme concentration remained constant, the reaction speed would increase.

Data: (recorded at 15-second intervals)
Control
1st Control (4.5cc buffer, 0.0cc enzyme, 0.5 H2O2)
0cc (for 3 min)

2nd Control
0cc (for 3 min)

Experiment #1
1st Trial of Experiment #1( 3.0cc buffer, 1.5cc enzyme, 0.5cc H2O2)
1.0cc
1.4cc
1.8cc
2.0cc
2.0cc
2.2cc
2.3cc
2.5cc
2.5cc
2.6cc
2.6cc
2.7cc
2.7cc
2.8cc
2.8cc
2.8cc

2nd Trial of Experiment #1
1.2cc
1.5cc
1.8cc
2.0cc
2.1cc
2.3cc
2.3cc
2.4cc
2.5cc
2.6cc
2.7cc
2.7cc
2.8cc
2.8cc
2.9cc
2.9cc

Experiment #2
DSubstrate (H2O2)

1st Trial (3.25cc buffer, 1.5cc enzyme, 0.25 H2O2)
0.0cc
0.2cc
0.3cc
0.4cc
0.5cc
0.5cc
0.5cc
0.6cc
0.6cc
0.7cc

2nd Trial (3.0cc buffer, 1.5cc enzyme, 0.5cc H2O2)
see above for data

3rd Trial (2.75cc buffer, 1.5cc enzyme, 0.75cc H2O2)
1.5cc
2.3cc
3.1cc
3.5cc
4.0cc
4.4cc
4.6cc
5.0cc
5.3cc
5.5cc
5.9cc
6.0cc
6.1cc
6.3cc
6.4cc
6.5cc
6.6cc
6.7cc
6.7cc
6.8cc
6.9cc
6.9cc
7.0cc

4th Trial (2.5cc buffer, 1.5cc enzyme, 1.0cc H2O2)
2.5cc
3.5cc
4.5cc
5.5cc
6.2cc
6.5cc
7.0cc
7.5cc
8.0cc
8.3cc
8.5cc
8.6cc
8.8cc
8.9cc
9.1cc
9.3cc
9.4cc
9.5cc
9.7cc

Conclusion:
Our hypothesis was correct for the experiments that we tested. As we increased the substrate concentration, the reaction speed increased as well.

Heather Shelton

Trials


Seconds  Control      1st Trial        2nd Trial        Cold         Hot


15                0                .8                   1                .5              1.2


30                0                1.2                1.5              .9              1.7


45                0                1.4                1.8              1                2.0


60                0                1.8                 2.0             1.3             2.2


75                0                 2.0                2.2             1.4             2.4


90                0                 2.1                2.4             1.5             2.6


105              0                 2.2                2.5             1.7             2.7


120              0                 2.3                2.6             1.8             2.8


135              0                 2.4                2.7              2               3.0


150              0                 2.5                2.8              2.1            3.2


165              0                 2.6                2.9              2.2            3.3


180              0                 2.65              3.0              2.3            3.4


195              0                 2.8                3.1              2.4            3.5


210              0                 2.9                3.2              2.6            3.6


225              0                 3.0                3.2              2.7            3.7


240              0                 3.1                3.2              2.8            3.75

Hypothesis
When the Ph of the solution into which the enzyme catalase and hydrogen peroxide are mixed is increased or decreased from Ph 7.4, the rate of oxygen production will slow down.

Data

Ph 4

Time Oxygen Level

15s 0.3
30s 0.3
45s 0.3
1m 0.5
1m 15s 0.9
1m 30s 1.0
1m 45s 1.1
2m 1.2
2m 15s 1.6
2m 30s 2.0
2m 45s 2.1
3m 2.2
3m 15s 2.5
3m 30s 2.8
3m 45s 3.0
4m 3.1
4m 15s 3.3
4m 30s 3.5
4m 45s 3.6
5m 3.9
5m 15s 4.0
5m 30s 4,1
5m 45s 4.5
6m 4.5
6m 15s 4.6
6m 30s 4.6
6m 45s 4.6

Ph 7.4 (control)

Time Oxygen Level

15s 1.0
30s 1.3
45s 1.5
1m 2.0
1m 15s 2.0
1m 30s 2.1
1m 45s 2.3
2m 2.4
2m 15s 2.4
2m 30s 2.4
2m 45s 2.5
3m 3.0
3m 15s 3.0
3m 30s 3.0

Ph 10

Time Oxygen Level

15s 1.0
30s 1.4
45s 1.6
1m 1.8
1m 15s 2.1
1m 30s 2.2
1m 45s 2.3
2m 2.5
2m 15s 2.6
2m 30s 2.7
2m 45s 2.9
3m 2.9
3m 15s 3.05
3m 30s 3.2
3m 45s 3.4
4m 3.5
4m 15s 3.5
Conclusion
Our initial hypothesis proved to be incorrect. We thought that the Ph the reaction normally occurred at, 7.4, would be the Ph at which the reaction occurred fastest. It seems that in fact the oxygen will be produced fastest at a higher Ph.

Hypothesis: The enzyme catalase serves as a catalyst that stimulates a reaction between molecules of hydrogen dioxide, increasing the rate of reaction within the solution.
Since oxygen is one of the byproducts of the chemical reaction, we measured the amount of reaction between the peroxide molecules by measuring the amount of oxygen in mls yielded in each trial.
Data
Controlled Experiment:
No enzyme
4.5 mls Buffer PH7.4,
.5 ml H2O2
Amt of oxygen measured in Intervals of 15 s
15s 0.0
30 0.0
45 0.0
60 0.0
75 0.0
90 0.0

1.5 ml Enzyme, 3.0 ml buffer, .5 ml H2O2
Trial 1;
15s 0.8
30 1.2
45 1.6
60 1.8
75 1.8
90 2.0
105 2.2

Trial 2
15 0.8
30 1.0
45 1.2
60 1.6
75 1.8
90 2.1
105 2.2
We observed a drastic change in the rate of reaction when the enzyme was added to the solution. Without the addition of the enzyme, there appeared to be no oxygen byproduct at all.
For the second part of the experiment, we examined the effect changing the pH of the environment in which the reaction takes place would have on the rate of reaction. We changed the pH of the buffer to a pH of 4 and then to a pH of 10, and observed the new reaction rates, again in intervals of 15 seconds.

PH 4
0.5 ml H2O2, 3.0 ml PH4, 1.5 ml Enzyme
15. 0.0
30. 0.0
45. 0.1
60. 0.2
75. 0.2
90. 0.3
105. 0.4
120. 0.6
135. 0.8
150. 1.0
165. 1.4
180. 1.5
195. 1.6
205. 2.0
220. 2.2
235. 2.4
250. 2.4

PH 10
0.5 ml H2O2, 3.0 ml PH10, 1.5 ml Enzyme
15. 0.8
30. 1.3
45. 1.6
60. 1.6
75. 2.0
90. 2.1
105. 2.2
135. 2.3
150. 2.4
165. 2.4
180. 2.6
195. 2.6

The PH4 had a lower rate of reaction, however it eventually began to ‘take off’. As some enzymes work better in different PH environments, the catalyse does not do very well in a PH4, however catalyse works just dandy at PH10 suggesting that catalyse has a structure that is conductive from PH7.5 to PH10.

Hypothesis: The greater the concentration of enzyme in the reaction, the faster the oxygen will accumulate. However, ultimately the amount of oxygen created will be the same.

Purpose: To determine the role enzymes play in chemical reactions.

Procedure: Keeping the total volume and the amount of hydrogen peroxide constant, we varied the amount of enzyme (and therefore the amount of buffer). We first used 1 ml of enzyme with 3.5 ml of a buffer and added it to the hydrogen peroxide. We then measured the amount of oxygen produced during the reaction for every fifteen seconds until the reaction appeared to stop. We then attempted to do the same thing using 2.0 ml of the enzyme, but we ran into difficulties and were unable to complete the experiment.

Data:
For 1.0 ml of enzyme, .5 ml of hydrogen peroxide, and 3.5 ml of bufferý
Minutes Amount of Oxygen
.25 .9
.5 1.2
.75 1.5
1 1.8
1.25 1.9
1.5 2.0
1.75 2.2
2.0 2.3
2.25 2.4
2.5 2.5
2.75 2.6
3.0 2.7
3.25 2.8
3.5 2.95
3.75 3.0
4.0 3.05
4.25 3.1
4.5 3.2
4.75 3.3
5.0 3.4
5.25 3.45
5.5 3.5
5.75 3.55
6.0 3.6
6.25 3.65
6.5 3.65
6.75 3.7
7.0 3.75
7.25 3.8
7.5 3.9
7.75 4.0
8.0 4.1
8.25 4.18
8.5 4.2
8.75 4.3
9.0 4.35
9.25 4.4
9.5 4.4
9.75 4.4

Conclusion: Our data was not extensive enough in itself to yield any conclusive result. However, looking at the data from the other group that did the same experiment, one can see a vague relationship between the concentration of enzyme and the rate at which oxygen was produced: the higher concentrations of enzyme yielded a faster rate of oxygen production. The amount of oxygen produced at each trial was not exactly the same. This discrepancy, however, could be attributed to the imprecision of the tools being used in the experiment.

Lab 4

Change in Enzyme

Objective: To see the effect of increasing the enzyme solution while keeping the hydrogen peroxide constant on the reaction’s rate. The solution with more enzymes should have a faster reaction because the molecules are more prone to bump into each other.

Therefore our hypothesis is that by increasing the amount of enzyme solution in the solution will result a faster reaction rate.

Procedure:
By keeping the H202 solution constant and increasing the amount of enzyme, we measured the volume of the pressure resulting from the reaction.
Data:

Enzyme 0.0
H202 .5
Buffer 4.5

There was no reaction so no oxygen was emitted.

Enzyme 1.0
H202 0.5
Buffer 3.5

.6
.8
1.0
1.2
1.4
1.5

Enzyme 1.5
H202 .5
Buffer 3.0

.8
1.6
1.8
2.2
2.3
2.4
2.5
2.6
2.7

Enzyme 2.0
H202 .5
Buffer 2.5

1.4
1.8
2.0
2.3
2.4
2.5
2.6
2.7
2.75
2.8

Enzyme 2.5
H202 .5
Buffer 2.0

1.4
1.8
2.0
2.1
2.2
2.3
2.35
2.4
2.5
2.5

Conclusion:

Overall the volume increases but gradually increased at a slower (decreasing) rate. For example, in our experiments the pressure jumped from .6 to .8. and then to 1.4 but then remained at 1.4. The last three trials with 1.5, 2, and 2.5 enzyme solution quantity tapered off to roughly the same rate towards the end of the reaction. After the enzyme amount was 2.0, the pressure stayed the same. In general our hypothesis was correct but we should have taken how it increases, into consideration i.e. increasing at a decreasing rate as opposed to a steady rate as our hypothesis implies. The inaccuracy in our enzyme of 1.0 could be from us not following through with the entire reaction

Hypothesis:
1. Given a certain amount of substrate (in our case 2H2O2) increasing the concentration of enzyme in the solution will result in a greater rate of oxygen release, but all cases should result in the same amount of oxygen released because the amount of substrate to use is not changing.
2. Given a certain amount of enzyme (catalase), increasing the concentration of 2H2O2 substrate in the solution will result in a greater rate of oxygen release and there will also be greater amounts of oxygen produced.
3. Increasing the temperature of the solutions in the experiment will increase the rate of reaction, and decreasing the temperature will in turn decrease the rate of reaction as compared to normal room temperature.
4. Any change in pH (be it increasingly acidic or increasing basic) will have a changing effect on the enzyme and hence decrease its effectiveness. Therefore the rate of reaction will decrease with increased acidity or increased basicity of the buffer in the enzym/substrate solution.

We specifically tested the varying amounts of substrate with the consistent 1.5 mL of enzyme (this corresponds to hypothesis #2).

We ran the experiment 4 times (not including the control in which we tested the reactions without the presence of enzyme—in which we saw no notable production of oxygen). We kept the enzyme concentration the same in the solutions and varied the amounts of peroxide and buffer (pH 7.4) maintaining a constant volume of 5 mL of solution in all runs of the experiment.

Time Intervals 0.25 mL 0.5 mL 0.75 mL 1.0 mL
15 0.4 1.2 2.2 3.0
30 0.5 1.4 3.0 4.0
45 0.6 1.8 3.4 4.7
1 MINUTE 0.7 2.0 3.7 5.4
15 0.8 2.2 3.8 5.8
30 0.85 2.4 4.1 6.2
45 0.9 2.5 4.3 6.6
2 MINUTE 0.95 2.6 4.5 6.9
15 1.0 2.7 4.7 7.1
30 1.02 2.8 4.8 7.3
45 1.03 3.0 5.0 7.5
3 MINUTE 1.03 3.0 5.1 7.7
15 1.03 3.0 5.1 7.7
30 1.05 3.1 5.3 8.0
45 1.05 3.1 5.4 8.2
4 MINUTE 1.07 3.2 5.5 8.3
15 - - 5.6 8.4
30 - - 5.65 8.5
45 - - 5.7 8.5
5 MINUTE - - 5.8 8.6
15 - - 5.9 8.6
30 - - 6.0 8.65
45 - - 6.0 8.65
6 MINUTE - - 6.0 8.65

According to our data, the rate of oxygen production in the first 15 seconds increases with the increased amounts of peroxide in the solution. The difference in the total amount of oxygen released is apparent in the different cases with the 0.25 mL of substrate producing an amount of oxygen significantly less than that of the solution with 1.0 mL of substrate. It is also noteworthy to look at the rate at which oxygen is released in the 4 cases. In the first case (with the least amount of peroxide) the amount increases by about 0.05-1.0 mL per interval, whereas the case with the 1.0 mL of peroxide increased with about 0.2-0.4 mL. Therefore, the data seems to support our initial hypothesis.

Experiments:

#1: We added 0.5ML of H2O2 and 4.5ML of buffer. We measured the amount of oxygen released when no enzymes reacted on the chemical process.

#2: We added 3ML of buffer, 0.5ML of H2O2 and 1.5ML of the enzyme. We measured the amount of oxygen released.

#3& #4: We added 3ML of buffer with a PH of 4 and 10, the rest of the quantities of the chemicals added remained the same. We measured the amount of oxygen released.

Hypotheses:

In the first part of the experiment we had to determine how an enzyme reacts on the chemical process. We thought that an increase in the amount of the enzyme would speed up the reaction rate. In the second part of the experiment we had to determine how PH effects the release of oxygen in this chemical process.

Data:

Experiment #1:

Time (s) Oxygen (ML)
15 0.8
30 0.8
45 0.8
60 0.8

Experiment #2:

Time (s) Oxygen (ML)
15 0.8
30 1.0
45 1.2
60 1.5
75 1.7
90 1.9
105 1.9
120 2.0

Experiment #3: (PH of 4)

Time (s) Oxygen (ML)
15 0.1
30 0.1
45 0.1
60 0.2
75 0.2
90 0.3
105 0.4
120 0.6
135 1.0
150 1.2
165 1.4
180 1.8
195 2.0
210 2.1
225 2.2
240 2.4
255 2.7
270 2.9
285 3.0

Experiment #4: (PH of 10)

Time (s) Oxygen (ML)
15 0.8
30 1.0
45 1.3
60 1.4
75 1.6
90 1.7
105 1.8
120 2.0
135 2.0

Conclusion:

In this lab we learned the effects of PH and the amount of enzyme added to chemical reactions. An enzyme acts as a catalyst, which means that it speeds up a chemical reaction without permanently changing itself. From our data we also determined that the more acidic the buffer is the longer it takes for the reaction to take place.

Varying Enzyme Amount

Hypothesis: As we add more enzyme, the reaction will occur more quickly but more oxygen will not be produced. In the experiments when we added less enzymes, we would have eventually gotten the same amount of oxygen, but we would have had to wait much longer than five minutes.

Experiment 1: 0.5 ml Hydrogen Peroxide, 4.5 ml buffer, 0.0 enzyme

There was no reaction.

Experiment 2: 0.5 ml Hydrogen Peroxide, 3.5 buffer, 1.0 enzyme

Time Volume
.15 .4
.30 .8
.45 1.0
1.0 1.2
1.15 1.4
1.3 1.6
1.45 1.8
2.0 2.0
2.15 2.2
2.3 2.4
2.45 2.4
3.0 2.6
3.15 2.8
3.3 2.8
3.45 2.8
4.0 2.8
4.15 2.8
4.30 2.8
4.45 2.8
5.0 2.8

Experiment 3: 0.5 ml Hydrogen Peroxide, 2.5 ml buffer, 2 ml enzyme

Time Volume
.15 1.6
.30 2.2
.45 2.4
1.0 2.6
1.15 2.8
1.30 3.2
1.45 3.4
2.0 3.4
2.15 3.4
2.30 3.6
2.45 3.6
3.0 3.6
3.15 3.6
3.30 3.6
3.45 3.6
4.0 3.6
4.15 3.6
4.30 3.6
4.45 3.6
5.0 3.6

Experiment 4: 0.5 ml hydrogen peroxide, 2 ml buffer, 2.5 ml enzyme

Time Volume
.15 1.8
.30 2.4
.45 2.8
1.0 3.2
1.15 3.4
1.3 3.8
1.45 4.0
2.0 4.0
2.15 4.2
2.3 4.4
2.45 4.6
3.0 4.8
3.15 5.0
3.3 5.2
3.45 5.4
4.0 5.6
4.15 5.8
4.3 5.8
4.45 6.0
5.0 6.0

Conclusion: Our data supports our hypothesis, but doesn't completely prove it. There could be other conditions that we weren't exploring.

The enzyme binds and helps get a faster rate of reaction. If you add more enzymes you get a faster reaction rate. The buffer solution was held constant. We wanted to find out if it is true that enzymes increase reaction rate. We hypothesized that if we increase the enzymes it would lead to a faster chemical reaction.

For the control group: No enzyme 1/2 mL of H2O2. 4 1/2 mL buffer solution. There was no reaction (0) for a total of 3 minutes.

For the first experiment .5mL H2O2, 3.0 mL buffer solution and 1.5mL enzyme.Our data was as follows:
15 sec 1.6 mL enzyme
30 sec 2.0
45 sec 2.4
60 sec 3.0
75 sec 3.6
90 sec 3.6
105 sec 3.6
120 sec 3.6
135 sec 3.6

This showed that as we add enzymes we get a clear, measurable reaction. The enzymes speeded up the reaction at the beginning.

For our next reaction, we varied the Ph. Before we used a 7.5 pH solution. Now we are going to use a pH4 and a pH 10.

The lower the pH, the higher the hydrogen concentration. The pH has an effect on the enzyme structure. The enzyme 3 dimensional structure is dependent on the different chemical environment. Everything was a control. but the pH.

pH4 1.5 enzyme .5 H2O2
15 sec 0
30 sec 0
45 sec .2
60 sec .2
75 sec .2
90 sec .2
105 sec .3
120 sec .4
135 sec .5
150 sec .7
165 sec .7
180 sec 1.0
195 sec 1.0
210 sec 1.2
225 sec 1.3

With a pH of 10 1.5 enzyme .5H202
15 sec .6
30 sec .8
45 sec 1.2
60 sec 1.4
75 sec 1.4
90 sec 1.6
105 sec 1.6
120 sec 1.6
135 sec 2.2
150 sec 2.2
165 sec 2.2
180 sec 2.4
195 sec 2.6
210 sec 2.6

The reaction rate for the pH4 was slower than the reaction rate for pH 10. It was also slower than a pH 7.5 The neutral pH works the best. The pH content has an effect on the speed of the reaction which is effected by the enzymes. A higher pH generates a faster rate of reaction than a lower pH.

Wednesday Lab – 10/24/01

Enzymes Lab

Hypothesis: To expect an increase in reaction rate when you increase the amount of enzymes and when the substrate amount is increased a faster reaction rate will occur.

Method:
We used all room temperature substances and kept the substrate (H2O2 – hydrogen peroxide) constant. We varied the amount of enzymes to test the reaction, and kept the amount of liquid in the experiment constant with a buffer liquid. At all times there was 5 ml of liquid in the system. We measured the amount of oxygen produced by the reaction of the enzyme with the hydrogen peroxide with a syringe and took readings every 15 seconds.

The table we used was the following:
(numbers measured in ml)
Enzymes H2O2 Buffer
1 0.0 0.5 4.5
2 1.0 0.5 3.5
3 1.5 0.5 3.0
4 2.0 0.5 2.5
5 2.5 0.5 2.0

Observation:
(cc of oxygen released in each trial)
Time 1 2 3 4 5
15 sec 0 1.8 1.2 1 1
30 sec 0 2.1 1.6 1.2 1.5
45 sec 0 2.2 2.0 1.6 1.7
1 min 0 2.4 2.2 1.8 2.0
1m 15s 0 2.4 2.4 1.9 2.0
1m 30s 0 2.6 2.4 2.0 2.2
1m 45s 0 2.7 2.6 2.1 2.2
2 min 0 2.8 2.6 2.2 2.3
2m 15s 0 2.8 2.8 2.3 2.4
2m 30s 0 2.9 2.8 2.4 2.5
2m 45s 0 3.0 2.8 2.4 2.6
3 min 0 3.1 3.0 2.4 2.6

Conclusion:
While our results showed the opposite of our hypothesis, we conclude that because we only did one trial, human error, and enzyme concentration differences, our observations were possibly skewed. Logic suggests that the reaction rate (oxygen production) should increase as more enzymes are added to the solution.

Purpose: To observe the reaction rates and quantify the amount of oxygen produced when mixing varying levels of enzymes with hydrogen peroxide.

Hypothesis:
For variation in the amount of enzyme: The more enzyme in the solution, the faster the reaction will be. We do not expect an increase in the amount of oxygen produced by the reaction, only an increase in the speed of the reaction itself.
For variation in the amount of hydrogen peroxide: The more hydrogen peroxide, the faster the rate of reaction, but it takes longer for completion, so the amount of oxygen is not constant.

Observations:

Variation in amount of enzyme:
Control Group
0.5 mL Hydrogen Peroxide
4.5 mL Buffer
0.0 mL Enzyme

Findings
:15 0.0 mL oxygen produced
:30 0.0
:45 0.0
1:00 0.0

Experimental Group
0.5 mL Hydrogen Peroxide
3.0 mL Buffer
1.5 mL Enzyme

Findings
:15 .8 mL oxygen produced
:30 1.2
:45 1.4
1:00 1.6
1:15 1.8
1:30 2.0
1:45 2.0
2:00 2.0
2:15 2.2
2:30 2.2
2:45 2.3
3:00 2.4
3:15 2.4
3:30 2.4

Variation in amount of substrate (Hydrogen Peroxide)
Experimental Group #1
0.25 mL Hydrogen Peroxide
3.25 mL Buffer
1.50 mL Enzyme

Findings
:15 0.6 mL oxygen produced
:30 0.8
:45 1.0
1:00 1.2
1:15 1.2
1:30 1.2
1:45 1.2
2:00 1.2

Experimental Group #2
1.0 mL Hydrogen Peroxide
2.5 mL Buffer
1.5 mL Enzyme

Findings
:15 4.5 mL oxygen produced
:30 5.0
:45 5.4
1:00 6.0
1:15 6.2
1:30 6.5
1:45 6.8
2:00 7.0
2:15 7.2
2:30 7.4
2:45 7.6
3:00 7.8
3:15 8.0
3:30 8.0
3:45 8.0
4:00 8.2
4:15 8.4
4:30 8.6
4:45 8.6

Conclusion:
Our hypotheses appear to have been correct. Through the experiment, we found that the more hydrogen peroxide we added to a constant level of enzyme, the faster the reaction and the more oxygen was produced. Similarly, we found that the more enzyme we added to a constant level of hydrogen peroxide had an increased reaction rate but the level of oxygen produced was constant.

Purpose: to observe the effects of changing the amount of enzyme concentration on the speed of a chemical reaction and the amount of oxygen that is consequently produced.

Hypothesis: The reaction rate will increase along with an increase in concentration substrate (H2O2), while keeping the enzyme level constant.

Data:
Control: Enzyme: 0 ml Buffer: 4.5 ml H2O2: .5 ml
The measurement of oxygen given off every 15 seconds was not a measurable reaction and remained constant at 0 cc.

Experiment #1 Enzyme: 1.5 ml Buffer: 3.0 ml H2O2: .5 ml

Time Elapsed Oxygen Meas.(Trial 1) Oxygen Meas.(Trial 2)
15 sec .6 cc .6 cc
30 sec .8 cc 1.0 cc
45 sec 1.2 cc 1.0 cc
60 sec 1.4 cc 1.3 cc
75 sec 1.6 cc 1.5 cc
90 sec 1.8 cc 1.6 cc
105 sec 1.8 cc 1.8 cc
120 sec 1.8 cc 1.8 cc

We found that adding the enzyme creates a measurable oxygen reaction with a higher reaction rate in the beginning, which eventually dies down and remains at a constant level.

Experiment #2: Variation in Room Temperature

The same measurements of enzyme, buffer, and H202 were used (as in Experiment #1), however with one trial using cold samples and the other using hot samples.

Hypothesis: There is a proportionate relation between the temperature and the reaction rate.

Time Elapsed Oxygen Meas.(cold) Oxygen Meas. (hot)
15 sec .5 cc .7 cc
30 sec .7 cc 1.0 cc
45 sec 1.0 cc 1.3 cc
60 sec 1.2 cc 1.5 cc
75 sec 1.2 cc 1.6 cc
90 sec 1.4 cc 1.8 cc
105 sec 1.5 cc 1.9 cc
120 sec 1.6 cc 2.0 cc
135 sec 1.7 cc 2.1 cc
150 sec 1.8 cc 2.2 cc
165 sec 1.9 cc 2.2 cc
180 sec 1.9 cc 2.3 cc
195 sec 1.9 cc 2.4 cc

Conclusion: Based on our first experiment, we observed that more enzyme leads to a higher reaction rate, producing more oxygen. Based on our second experiment, we found that the substances used at a higher temperature resulted in higher reaction rates than the substances used at both room temperature and cold temperatures. In addition, compared to our results from the experiment conducted at room temperature, the reaction rates using the cold substances were lower. Therefore, our observations support our hypothesis that the reaction rate is proportionate to the temperature.

Problem:
Measuring the reaction rate as hydrogen peroxide is increased in a 5 mL solution

Hypothesis:
We think that an increase in the amount of enzyme with cause the rate to decrease. Since we think that an increase of hydrogen peroxide will lead to an increase in rate, we think that in turn, adding enzymes will slow down the process.

Procedure:
For the experiments, combining varying amounts of hydrogen peroxide, enzyme and buffer, we measured the rate of the reaction by equalizing the pressure (as seen through interpreting the movement of the blue Broaden solution) by pulling on a syringe which is attached to the closed system of the experiment. We measured the data that we got from the syringe readings in15 second intervals. The increase or decrease in rate was acquired from these results.

Control
0.5 mL hydrogen peroxide
4.5 mL buffer
0.0 mL enzyme

Results: 0

Experimental
0.5 mL hydrogen peroxide
3.0 mL buffer
1.5 mL enzyme
Resulting Measurements: 0.5, 0.9, 1.2, 1.4, 1.6, 1.8, 2.0, 2.1, 2.2, 2.3, 2.4, 2.6, 2.7, 2.75, 2.8, 2.8, 2.825

Change in Enzyme:

1.0 mL enzyme
0.5 mL hydrogen peroxide
4.5 mL buffer
Resulting Measurements: 0.3, 0.5, 0.7, 0.8, 1.05, 1.25, 1.4, 1.6, 1.75, 1.9, 1.95, 2.1, 2.2, 2.4, 2.6, 2.7, 2.8, 3.0, 3.1, 3.2

2.0 mL enzyme
0.5 mL hydrogen peroxide
2.5 mL buffer
Resulting Measurements: 0.25, 0.4, 0.2625, 0.8, 1.0, 1.2, 1.4, 1.4, 1.55, 1.6, 1.7, 1.8, 1.85, 1.925, 2.0, 2.05

2.5 mL enzyme
0.5 mL hydrogen peroxide
2.0 mL buffer
Resulting Measurements: 0.4, 0.6, 0.8, 1.0, 1.1, 1.25, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.1, 2.175, 2.25, 2.3, 2.4, 2.5, 2.6

Final Observations:
We looked at the last measurement from each experiment
1.0 mL enzyme final result: 3.2
1.5 mL enzyme final result: 2.85
2.0 mL enzyme final result: 2.05
2.5 mL enzyme final result: 2.6
and we see that for the most part our hypothesis was correct. As the amount of enzyme is increased, the final results show a decrease in measurement, which we assume is a decrease in overall average rate. The only exception is the last result (the measurement shows an increase in measurement, which counters the 4 previous measurements, which show a decrease in measurement) which we assume is due to possible human error. Human error can be caused by a false measurement of solution, errors in reading the data from the searing, erroneous timing, problems with keeping the experiment in a closed system (the plugging up after adding the solutions) or problems in assuming the equilibrium in pressure (by placement of the blue Broaden solution).

Enzymes

Purpose of Experiment:
To observe the effects of enzymes as catalysts by testing the reaction of hydrogen peroxide and a buffer solution when they are catalyzed by enzymes. Enzymes are proteins, which are an important part of life. They are complex molecules, which we break down and receive energy from. When chemical reactions cause enzymes to work too quickly, it can be very dangerous, and even lethal to humans.

Procedure:
We observed varying substrates by changing the proportions of hydrogen peroxide and buffer solution. The enzyme level remained constant at 1.5 mL.

Hypothesis:
As the hydrogen peroxide increases in relation to the buffer solution, the amount of oxygen produced and the rate at which it is produced will increase as well.

Control:
Solution: 4.5 mL of buffer (saline solution) + 0.5 mL of hydrogen peroxide

Time in minutes: Oxygen produced in milliliters:
0:15 0
0:30 0
0:45 0
1:00 0
1:15 0
1:30 0
1:45 0
2:00 0

Experiment A:
Solution: 3.25 mL of buffer + 1.5 mL of enzyme + 0.25 mL of hydrogen peroxide

Time in minutes: Oxygen produced in milliliters:
:15 0.4
:30 0.6
:45 0.7
1:00 0.8
1:15 0.8
1:30 0.9
1:45 0.9
2:00 1.0

Experiment B:
Solution: 3.0 mL of buffer + 1.5 mL of enzyme + 0.5 mL of hydrogen peroxide

Time in minutes: Oxygen produced in milliliters:
:15 0.6
:30 1.0
:45 1.2
1:00 1.4
1:15 1.6
1:30 1.8
1:45 2.0
2:00 2.2
2:15 2.4
2:30 2.4
2:45 2.6
3:00 2.6

Experiment C:
Solution: 2.75 mL of buffer + 1.5 mL of enzyme + 0.75 mL of hydrogen peroxide

Time in minutes: Oxygen produced in milliliters
:30 2.4
:45 3.2
1:00 3.8
1:15 ----
1:30 4.4
1:45 4.8
2:00 5.0
2:15 5.2
2:30 5.5
2:45 5.7
3:00 6.0

Experiment D:
Solution: 2.5 mL of buffer + 1.5 mL of enzyme + 1.0 mL of hydrogen peroxide

Time in minutes: Oxygen produced in milliliters:
:15 2.4
:30 3.4
:45 4.2
1:00 4.8
1:15 5.4
1:30 6.0
1:45 6.4
2:00 6.8
2:15 7.1
2:30 7.6
2:45 7.8
3:00 8.2
3:15 8.4
3:30 8.6
3:45 8.7
4:00 8.8

Conclusion:
Our data supported our hypothesis very well. Higher percentages of hydrogen peroxide (and smaller percentages of buffer solution) caused both the amount of oxygen produced and the rate at which it was produced to increase.

.We discussed enzymes.
We observed that when Hydrogen Peroxide, or H2O2, was added to an unknown substance, a chemical reaction occurred, producing H2O, O2, and heat. Because the unknown substance was not used up in the reaction, no matter how much H2O2 was added, we concluded that it must be an enzyme. In fact, it did indeed turn out to be an enzyme called catalase.
We tried to predict what would happen if differing amounts of the substrate, H2O2, were added to a constant amount of the enzyme catalase. We would measure the amount of oxygen released each time, using a respirometer.
First we performed the control. We observed that when no enzyme was present, no reaction occurred when .5mL enzyme was mixed with 4.5mL of buffer.
We then performed the first experiment. We added .5 mL of H2O2 to a mixture of 1.5 mL of enzyme and 3 mL buffer (the buffer was used to make sure that the pressure remained constant). We observed the amount of oxygen displaced in the reaction every 15 seconds.
15 secs .5 mL O2
30 secs 1.2 mL
45 secs 1.5 mL
60 secs 1.8 mL
75 secs 2 mL
90 secs 2.2 mL
105 secs 2.8 mL
120 secs 2.8 mL

Deciding to keep the amount of enzyme at a constant of 1.5 mL, we tried to see what would happen when .25, .75, and 1.0 mL of H2O2 were added, always adjusting the buffer amount to keep a constant volume of 5 mL.
When .25 mL of the substrate were added, no significant of O2 was released.
We repeated the experiment in which .5 mL of H2O2 was present, and we found:
15 secs 1 mL O2
30 1.4 mL
45 1.6 mL
60 1.8 mL
75 2 mL
90 2.2 mL
105 2.2 mL
120 2.4 mL
135 2.6 mL
150 2.6 mL
When we added .75 mL of H2O2 the results were the most dramatic. Every fifteen seconds, these amounts of O2 were released: 2.6, 3, 3.4, 3.6, 3.8, 4.2, 4.4, 4.4, 4.6, 4.8, 4.8, 5.2, 5.2, 5.4, 5.6, 5.8, 6, 6, 6, 6.2, 6.2, 6.2, 6.4, 6.5, 6.6, 6.8, 6.8, 6.8, 7, 7, 7.2, 7.2, 7.2, 7.2, and 7.2 mL. When 1 mL H2O2 was added, no observable amount of oxygen was observed to have been released.

Thus, we observed that, generally, the more substrate was added, the longer the entire reaction seemed to take. Also, with more substrate, the reactions tended to go at a quicker rate, at least at first. This is probably because the enzyme itself is not used up in a chemical reaction; it only speeds things up. Since the enzyme is not used up, the reaction will last until the substrate is used up. However, this doesn’t explain the results of our last experiment, in which the most substrate was used.

Ilyssa Fisher

Fly Lab

Purpose:
The purpose of this experiment was to try to come to a greater understanding of the way genes are passed on from one generation to another.

Hypothesis:
We hypothesized that the fruit flys of the wild type will pass their dominant genes onto the F1 generation to all the offspring. However, when breeding the F1 generation offspring together, the result will be a 3:1 ratio of wild type to the second type.

Data:
We experimented with several traits on the Flylab Program in order to test our hypothesis.

Conclusion:
In some case types, the wild type was not the dominant gene, therefore disproving our hypothesis.

We investigated the properties of genes. We learned that alleles are different forms of the same gene. We began with Mendell's hypothesis that there are dominant and recessive traits. We wanted to discover whether or not inheritance follows a consistent pattern or ratio.
When observing the fly lab program, we selected wing angle as the variant trait. Our results were not in agreement with Mendell's three to one ratio. During our discussion later we found out that the specific trait is part of a certain group known as lethal traits.

Fly Genetics Lab

For this lab, we examined the occurrence of traits as they appeared through two generations of breeding. We bred fruit flies, isolating at first one trait. We were testing Mendel's hypothesis that at the F2 level, there would be a 3:1 ratio of dominant trait to recessive trait.

First we tested Wing size of fruit flies. We had the female set as a wild type and the male as wingless. After the first breeding, we had only wild type of individuals present. After we bred the F1 individuals together, we had the 3:1 ratio of dominant to recessive trait.

Eye color with a wild type female and a purple-eyed male also followed this pattern.

However, when we tested a female wild type antennae and a male type aristopedia antennae we found that at the F1 stage we had a ratio of 1:1 , with both types present. This was described to us as an example of a dominant lethal gene.

Next we examined dihybrid crosses. We discovered that in breeding two traits, the dominant and recessive traits could be independently assorted, leaving a ratio of 9:3:3:1 of genotypes.

Hypothesis: All inheritance is governed by Mendel's model, which says that the first generation would have characteristics of the dominant gene while the second generation would show a 3:1 ration of the dominant gene to the recessive gene.

Observations: Although some students did find some traits that did not follow Mendel's model, we didn't find any. We tested for: purple eye color, apterus wings, dumpy wings, lobe eye, and black body. The lobe eye was interesting because it turned out that the lobe eye gene is dominant over the wild type gene.

Reasons why Mendel's model doesn't always work:
1. sex-linked genes
2. dominant-lethal genes

Mendel has another model called the Law of Independent Assortment, which only works for genes that are not linked to chromosomes. In this case, the second generation has a ratio of 9:3:3:1.

Conclusions: In most cases Mendel's hypothesis works. However, his model is oversimplified. It does not take into account genes that are on the same chromosome, which limits the possible outcomes of reproduction.

Hypothesis: The F1 generation will show only dominant traits, and in the F2 generation, there will be a 3:1 ratio of dominant to recessive traits.

Purpose: To determine the pattern by which traits are passed from one generation to the next.

Procedure: We used the Fly Lab program to "breed" fruit flies of various traits. We first bred wild females with males having one differing characteristic.

Data:
Trial 1: Eyecolor
Red female x Purple male ‡ f1: all red; f2: 3:1 ratio of red to purple
Red female x White male ‡ f1: all red; f2: 3:1 ratio of red to white
Red female x Sepia male ‡ f1: all red; f2: 3:1 ratio of red to sepia
White female x Red male ‡ f1: 1:1 ratio; f2 1:1 ratio

Trial 2: Antennae
Wild female x Aristopedia male ‡ f1: 1:1; f2: 1:1, but not as many actually survived

Trial 3: Wing Vein
Wild female x Crossveinless male ‡ 1:1; 3:1

Conclusion: Not every trait followed our hypothesis. Some traits appeared to be linked to sex chromosomes.

Biodiversity as shown in the breeding of fruit flies

Hypothesis: one can follow a genetic mutation through generations of fruit flies.

I used the Java application known as "FlyLab" to track the gene coded for white eyes in fruit flies. I mated a wild [normal, red-eyed] female with a white-eyed male. The offspring has red eyes. I mated two of the offspring and two of their offspring had red eyes, and the other two had whited. I mated a whit-eyed female with a red-eyed male and ended up with one red and one white. I mated the red-eyed female with the white-eyed male and ended up with two reds and two whites.

The gene for white eyes is recessive.

We hypothesize that our F1 and F2 generations of fruit flies will follow Mendel's model for the breeding of peas. The F1 generation would be 1:1 and the F2 generation would be 3:1.

Data:

Wild Female x Purple eyed Male
F1 1:1
F2 3:1

Wild Female x Dichaete Male (wing angle)
F1 1:1
F2 1:1

Wild Female x Eyeless Male
F1 1:1
F2 3:1

Wild Female x Dumpy Male (wing shape)
F1 1:1
F2 3:1

Wild Female x Aristapedia Male (antannae)
F1 1:1
F2 1:1

Aristapedia Male x Wild Female
F1 1:1
F2 1:1

Discussion:
Our observations show that for the most part, mating wild fruit flies with flies of different characteristics for two generations yielded the same 3:1 ratio as Mendell observed in pea plants. The two instances which stood out were wild female x diachaete and wild female x aristapedia male. we are not sure why the ratio was 1:1 in these cases since some of the variants might not be true varients.

After the first experiment we crossed
Black Body/Shaven Bristle Male with Wild Female. We recieved a 9:3:3:1 ratio. This result complies with Mendells second law of independent assortment. Allele pairs are free to break up and recombine. Color and Hair genes are on a different set of chromosomes. They are independent of eachother.

The purpose of this lab was to observe how various genetic characteristics of the fruit flies effect their offspring. We used a computer program to simulate the breeding of fruit flies with different genotypes to see how it would effect the phenotype. We looked at the way dominant and recessive genes played a role in the flies’ generations.

We observed six characteristics: curly wings, purple eyes, lobe eyes, antennae, yellow body color, and forked bristles. We bred flies with one of these characteristics with the corresponding "wild type" genes. Wild is the first number in the ratio.

Curly wings
Female (wild) F1 1:1 F2 1:0
Male (wild) F1 1:1 F2 1:0

Purple eyes
Female (wild) F1 1:0 F2 3:1
Male (wild) F1 1:0 F2 3:1

Lobe eye
Female (wild) F1 1:0 F2 1:3
Male (wild) F1 0:1 F2 1:3

Antennae
Female (wild) F1 1:1 F2 1:0
Male (wild) F1 1:1 F2 1:0

Yellow Body
Female (wild) F1 1:0 F2 3:1
Male (wild) F1 1:1 F2 1:1

Forked Bristle
Female (wild) F1 1:1 F2 1:1
Male (wild) F1 1:0 F2 2:1

Hypothesis: That body color and bristle type in fruit flies will follow the same patterns that Mendel observed in pea color and shape.

Procedure: We used Fly Lab to test the results of mixing genes in fruit flies. In our first experiments, the female carried all Wild Type traits, or those that are most prominent in the wild. We then altered the male to create, in this case, bristle variations. We subsequently reversed the traits of the male and female. Finally, we analyzed the effects of a dihybrid cross between a Wild Type female and a male with two other traits.

Data:

When we crossed a Wild Type (WT) female with a Spineless Bristled (SS) male, in the first generation (F1), all of the 1000 the offspring had the WT phenotype. In generation F2, 748 offspring had the wild type bristle and 267 had the spineless bristle, creating a ratio of 2.8:1.

We repeated this experiment changing only the number of offspring from 1000 to 100. Once again, in F1, all offspring were the WT phenotype. In F2, the ratio was 2.65:1.

We then did the experiment a third time, changing again the number of offspring to 10,000. F1 remained the same, and the ratio in F2 was 2.95:1

In the dyhybrid experiment, we mated a Wild Type female with a male with a Black body and Shaven bristles. In the first generation, F1, all 10,054 were WT phenotypes with regard to both body color and bristle type.

The chart below shows the results of generation F2:

Phenotype number Ratio

Wild, wild 5625 8.777
Wild, shaven 1922 2.998
Black, wild 1882 2.936
Black, shaven 641 1.000

Conclusions:
In the first experiments, we reached nearly the same conclusions. The F1 generation always produced the Wild Type phenotype. In the F2 generation, the ratio of Wild Type bristle phenotypes to Spineless bristle phenotypes was approximately 3:1, and the more flies that were tested, the more exact the ratio was.

In the dihybrid cross, the results conformed very closely to the 9:3:3:1 ratio predicted by Mendel’s law of independent assortment; consequently, we concluded that genes controlling these characteristics are probably located on different chromosomes.

Hypothesis: by mating two fruit flies, one with the dominant wild traits, and the other with a variant recessive trait, the first generation of offspring will all have wild traits. In breeding their offspring, the second generation will have a 3:1 ratio of dominant to recessive traits. This is so according to Mendel's law of segregation. All traits will follow this law.

Observations: Some of traits that were tested follow along with Mendel's law, such as eyeless, purple eye, dumpy wing, and sepia eye. However, there were several traits that resulted in different ratios, such as 1:1, and those include curly wing, bar eye, aristopedia antennae, and incomplete wing vein.

Conclusion: While Mendel's theory does account for the majority of traits found in fruit flies and other organisms, Mendel's law does not account for other conditions that can affect genetic heritage, such as sex-linked inheritance, dominant lethal mutation, and when two or more characteristics occur on one chromosome.

Hypothesis: When mated, fruit flies will always yield the 1:0 ratio in the F1 and a3:1 ratio in the F2 as discovered by Mendel.

Procedure: Using the FlyLab program we simulated the mating of a wild type female fruit fly and a curly winged male fruit fly. We then mated the offspring. We tested both genders of the flies to insure that gender was not a determinant factor.

Results: The F1 of the mating pair gave a 1:1 ratio.

The F2 showed a 2:1 ratio with more curly winged flies

Conclusion: These results did not agree with our hypothesis. We account for the discrepancy by noting that the curly winged flies are not pure

For this lab we used the fly lab program to test out Gregor Mendel’s 3:1 ratio of inheritance in monohybrids. According to this, any one trait when crossed with a pure (wild) type, the offspring will show a 3:1 ratio of wild types to a traited type. The hypothesis was that we would find this ratio in any monohybrid.
In the fly lab when a purple eyed female was crossed with a wild male, the second generation would show the 3:1 ratio. This is not a sex-linked trait; when the male is purple eyed and the female wild, the same ratio is still found in the second generation. This example upheld the hypothesis.
However, other traits such as curly wings or dichaete wings did not follow the pattern. They had 1:1 ratios in the first generation and 1:2 ratios in the second generation( mating curly with curly or dichaete with dichaete). This sort of mating yields a dominant lethal mutation; when the two dominant traits appear at the same time, the fly dies.
While we didn’t find any sex-linked traits, in lab we discussed traits that are linked to the fly’s sex, such as yellow bodies. A yellow female and a wild male yields a 1:1 ratio of wild to yellow but a yellow male with a wild female yields all wild offspring (both in first generation). The hypothesis works for certain traits, but does not cover instances such as sex-linked traits, or dominant lethal traits.

We tested Mendel's hypothesis which stated that you take fruit flies with two different variants, the progeny of one F1 would be all one variant. You would take that progeny and get a 3 to 1 ratio (F2). We tested this out using the fruit fly website.
We wanted to see if the different fruit fly traits follow Mendel's theory. If they do not could we come up with a new pattern of inheritance?
Our results were as follows :

Female +(wildtype) Male (purple eyes)
F1 + F2 3 to 1 ratio
Female (purple eyes) Male +
F1 + F2 3 to 1 ratio
This supports Mendel's hypothesis.

The following do not:
Female (aristapedia) Male +
F1 483 + 482 A F2 1 to 1 ratio

Female (curly wing) Male +
F1 498 + 481C F2 1 to 1

This did not work out because two curly winged genes produce a dominant lethal mutuation therfore the ratio is 2 to 1 as opposed to 3 to 1.

Female + Male (incomplete wing vein)
F1 + F2 1 TO 1

Female + Male (bar eye shape)
F1 473 B 509 + F2 1 TO 1

Female + Male (yellow body)
F1 + F2 3 to 1 --this supports Mendel's hypothesis, however :

Female (yellow) Male +
F1 M-> Y F-> + F2 1 to 1

The variance in this case switches gender. sex linked inheritance. Therefore it was important to do reciprocal crosses.

In class we discussed the law of segregation which is Mendel's first law. The second law is of independent assortment. This does not always hold because there are some factors located on the same chromosome. Holds for genes on different chromosomes 9:3:3:1.

Purpose:
The purpose of this lab was to test Mendel 's hypothesis that when you breed two parents, each will donate one factor to their offspring, and then to determine which characteristic was recessive and which characteristic was dominant.

Hypothesis:
If you take two fruit flies, giving one of the pair a variant (allowing one to remain in the wild type), the result will be offspring with a 3:1 ratio of characteristics.

Observations:
First, we cross-bread a wild female (the control) with an eyeless male, which resulted in all wild offspring in F1. Crossbreeding these offspring resulted in three wild and one eyeless offspring, giving a 3:1 ratio. Then, we cross-bread an eyeless female and a wild male, the results for F1 and F2 offspring were the same as the first experiment, agreeing with Mendel's pattern of inheritance.
Then we cross-bread a wild female with an aristapedia male (AR) and resulting in two wild and two AR F1 offspring. We had expected to get all wild or all wild aristapedia offspring. We cross-bread all of the F1 offspring with one another (a total of 4 breedings), and we found that when we mixed one AR with on wild, we got a 1:1 ratio of offspring. When we bread two wilds, it produced all wild offspring. When we mixed two AR flies, we got offspring in a 2:1 ratio, with AR being dominant.
Finally, in breeding a female AR with a male AR, our results showed a 2:1 ratio, AR being dominant.

Conclusions:
As our original hypothesis expected a result of 3:1, and our actual findings resulted in a 2:1 ratio instead, we needed to account for the discrepancy.
We concluded, through class discussion, that when two AR are bred, it becomes a "lethal dominant trait," meaning that any fly which inherits two AR factors, that offspring will die, resulting in a 2:1 ratio rather than a 3:1 ratio.

Lab #5:
Fruit Fly Lab

Hypothesis: Our experiment was to test Mendell’s hypotheis of inheritance, which is that in monohybrid experiments, the first generation would have a ratio of 1:0 and the second generation would have a 3:1 ratio.

For our first experiment we mated a female fly with all wild traits, with a male fly with all wild traits with the exception of one variant trait.

We found our hypothesis to be correct in certain cases, when the variant trait was purple eye color, dumpy wings and eyeless. Our hypothesis was proven wrong when the variant trait was aristapedia antenna.

In this case, F1(first generation of offspring) was a 1:1 of this trait. When 2 F1’s with wild characteristics were mated the result was a1:0. The result for all the following generations was a 1:0. When 2 F1’s with a variant trait were mated the result was a 1:2. When one F1, with wild traits, was mated with one F1 with the variant trait, the result was 2:1.

Purpose: To observe the problem of inheritance (the passing of genetic information from parents to progeny) through simulating the breeding of fruit flies, as compared to the findings of Mendel's research regarding genetic inheritance.

This raises two questions:
1 - Do all traits follow the inheritance findings of Mendel?
2 - If they don't, can we devise a new hypothesis for these new observed patterns of inheritance that explain the results?

Hypothesis: While most simulations of breeding fruit flies will follow Mendel's inheritance pattern findings in pea plants, there will also be exceptions in the fruit fly phenotypes.

Procedure: To simulate the breeding of fruit flies, we used a computer software program called Fly Lab. For each pairing of flies to be bred, there was a female fly with all characteristics of the wild type (generally dominant) that was crossed with a male fly with one variant feature. The first and second generations of offspring were analyzed in terms of the ratio of each variant feature (whether wild type or chosen variant).

Our predictions are that the F1 generation will have a 1:1 ratio while the F2 generation will have a 3:1 ratio.

Data:
Female Wild Type x Male Vestigial (variant: wing size)
F1: 1:1
F2: 3:1

Female Wild Type x Male Forked (variant: bristle)
F1: 1:1
F2: 3:1

Female Wild Type x Male Dichaete (variant: wing angle)
F1: 1:1
F2: 1:1 .......(exception to rule)

Conclusion: There were exceptions to Mendel's theories of genetic inheritance but most crosses followed the pattern of 1:1 and 3:1.

Inheritance/Genetics Lab

We used a Fly Lab program in order to simulate the genetic results of different factors and traits of the fruit flies in order to test Mendel’s Law of segregation. We took two parent flies, one having a different, non-wild trait and mated them in order to find out genetic results. We did this F1 test twice- once with the female as the wild type (having the common trait) and the male having the different non-wild trait, and then switching it around and having the male as the wild type (having the common trait) and the female having the non-wild trait. From each of these F1 tests, we took an F2 test, in which we mated the offspring in order to find the genetic results.

First Test: Wild Type x Purple Eye

Wild type female x Purple eye male
F1: all wild type
F2: 3:1 wild type
Purple eye female x Wild type male
F1: all wild type
F2: 3:1 wild type
Conclusion: Mendel’s Law is valid in this experiment

Second Test: Wild type x Curly Wing

Wild Type female x Curly Wing male
F1: 1:1
F2: 2:1 curly wing
Curly Wing female x Wild Type male
F1: 1:1
F2: 2:1 curly wing
Conclusion: Mendel’s Law does not apply in this experiment. The Hypothesis under Mendel’s Law did not prove true so we offer an adjusted hypothesis that the curly wing flies were not true breeders. We test this new hypothesis by mating two curly wings. These are the results:
F1: 2:1 curly wing
Mendel’s Law does not apply due to the dominant lethal mutation when a curly curly progeny do not survive.

Third Test: Wild type x Yellow Body

Wild Body female x Yellow Body Male
F1: all wild type
Yellow Body female x Wild Type male
F1: 1:1
Conclusion: All the females got wild bodies while all the males got yellow bodies due to sex link inheritance traits

Time to Think?

Purpose: To determine whether thinking can be measured by time.

Hypothesis: Acting will take the least amount of time. Thinking, reading, negating and acting will take the most amount of time.

Procedure: We used the Serendip computer program to measure reaction time in various cases: first just acting, then thinking and acting, then reading, thinking, and acting, and finally reading, thinking, negating, and acting.

Data:
In general, each case took progressively more time.

Conclusion: Our data supported our hypothesis.

TIME TO THINK LAB
For this lab we examined questions of the brain vs. the mind and the nature of thinking. One question is if thinking is a material or immaterial action. Our hypothesis was that a material action is measurable. We tested the measuability of thinking by testing the amount of time that was required for us to think and do certain tasks. We used the online Serendip program, which first tested reaction time. Then we tested how long it took to think, then react by having to click when black box was present. Then we tested the amount of time it took for us to read instructions, then perform the action they required. Finally, we tested how long it took us to read instructions then do the opposite of what was asked. We each did each trial 10 times and compiled the data.

OUR RESULTS

JESSICA
Trial Time standard deviation # of trials
A 254 42 10
TA 289 42 10
RTA 444 57 10
RNTA 515 77 10

JENNIFER
Trial Time standard deviation # of trials
A 250 36 10
TA 302 55 10
RTA 581 189 10
RNTA 528 116 10

LYDIA
Trial Time Standard deviation # of trials
A 337 37 10
TA 411 79 10
RTA 616 101 10
RNTA 760 167 10

CONCLUSION
Clearly, thinking requires time. As the dificulty of the requests increased, performing the tasks took a longer period of time. Similarities in the 3rd and 4th trials turned up some discrepancies. Some people were able to do the 4th trial more quickly because they looked for just one word, NOT. If not was resent they knew to click, and did not have to read the whole sentence. Many variables can affect speed, such as age, ability to concentrate in a noisy classroom, cafeine consuption etc.

Lab #6-- Time to think.

Purpose:
The purpose of this lab was to observe reaction times and to discover whether or not thinking takes time: if it is non-material or material.

Hypothesis:
Our hypothesis was that thinking doesn't take any time.

Data:
S's averages:
case 1: 326ms 23sd
case 2: 479ms 71sd
case 3: 743ms 176sd
case 4: 841ms 330sd

C's averages:
case 1: 336ms 55sd
case 2: 424ms 68sd
case 3: 632ms 112sd
case 4: 672ms 94sd

S's time to:
Act: 326ms 23sd
Think: 153ms 75sd
Read: 264ms 190sd
Negate: 98ms 374sd

C's time to:
Act: 336ms 55sd
Think: 88ms 88sd
Read: 208ms 132sd
Negate: 40ms 147sd

Conclusion:
From our data we have concluded that indeed it does take time to think. In each of our trials as our brain functions increased, so did the time it took to think. Therefore, our hypothesis is incorrect for this trial.

Hypothesis: Thinking takes no time.

Objective: We want to determine whether thinking is a material or immaterial process. Knowing that material process take times, we set out to make observations based on this assertion.

Data:

Vivian

A = 341 +/- 30

TA = 414 +/- 40

RTA = 636 +/- 131

RNTA = 686 +/- 130

Monica

A= 362 +/- 33

TA = 522 +/- 85

RTA = 637 +/- 158

RNTA = 1316 +/- 888

Discussion: According to our data and compiled data from class, our hypothesis was prove false. Our observations show that the more one has to think, the more time it takes. This raises many questions of possibly factors that influence thinking time such as amount of sleep, age, gender, computer, past experience with the program etc.

Hypothesis: It takes time to think. Negating, thinking, reading time are longer than acting time.

Samantha
1. 307 69
2. 401 59
3. 502 71
4. 501 156

Tua
1. 284 16
2. 361 69
3. 516 63
4. 474 67

We believe that it takes time to think. It's interesting to note, that with our data, it takes us less time to act on negatation than to follow directions. It would be interesting to try various stimulants to see how they effect thinking and reaction time. Also,we should see how age and reading level, or native language effects reading time. There are many factors that can change many of these times. Although the data is interesting we don't think that we could use it to support any major claims about the time it takes people to think, act, etc.

INTRODUCTION

Our experiment today used a measuring tool on the Serendip Web site to determine whether thought takes time. A finding that thought takes time was thought by 19th-century students of the mind and its processes to support the notion that thought is a physical, rather than an ethereal or spiritual, process.

METHOD

The experiment, based on a model by the Dutch physiologist Franciscus Cornelis Donders, first measured the time it took subjects to react to a stimulus. In the second case, the subjects were asked to react after distinguishing one stimulus from another. In the third case, subjects were required to read instructions before reacting, and in the fourth case, they were asked to read instructions and do the opposite of what they were instructed. Thus the first case measured the time it took to act, the second case the time it took to think and act, the third the time it took to read, think and act, and the fourth the time it took to read, think, negate and act. We hypothesized that each additional mental process would take time, and thus that response times for case four would be longer than for case three, for case three longer than for case two, and for case two longer than for case one.

OBSERVATIONS:

Subject 1:
Average "act" time: 398; standard deviation: 50
Average "think, act" time: 468, S.D.: 50
Average "read, think, act" time: 658, S.D.: 53
Average "Read, think, negate, act" time: 852, S.D.: 211

Subject 2:
Average "act" time: 312; standard deviation: 31
Average "think, act" time: 452, S.D.: 60
Average "read, think, act" time: 699, S.D.: 164
Average "Read, think, negate, act" time: 863, S.D.: 677

Subject 3:
Average "act" time: 292; standard deviation: 23
Average "think, act" time: 385, S.D.: 66
Average "read, think, act" time: 482, S.D.: 46
Average "Read, think, negate, act" time: 528, S.D.: 49

CONCLUSION:

Our data support the conclusion that thinking takes time.

We attempted to determine the correlation between reaction times and thought processes of various involvements to see if there was a noticeable difference between them.
The first trials we conducted tested the reaction time between seeing something and responding to it. The next trials we conducted tested the time it takes to think about a problem and then react to it. The next set of trials required reading directions and then acting, and the final trial tested the amount of time it takes to negate the trial.

Then we had to respond to
subj_name trial_type avg sd num_trials
Sasha A 320 30 10
Sasha TA 415 69 10
Sasha RTA 566 69 10
Sasha RNTA 579 67 10
Samantha A 315 122 10
Samantha TA 445 57 10
Samantha RTA 614 88 10
Samantha RNTA 598 111 10

subj_name type avg_diff sd
Sasha A 320 30
Sasha T 95 76
Sasha R 151 98
Sasha N 13 97
Samantha A 315 122
Samantha T 130 135
Samantha R 169 105
Samantha N -16 142

We found that on average, it takes more time when you have to process more than one action at a time. It took longer to read the directions, negate the directions and then act then it did to simply act, and click the button when the black box appeared. Therefore the hypothesis is negated. Since each separate process takes time to execute, the thought processes are not an empirical act, and are grounded in our physiology.

The purpose of this lab was to determine whether or not thinking takes time and therefore to determine whether or not thinking is ethereal or material. Because material change takes time, if thinking takes time as well, it should be material. If thinking does not take time, it can be classified as ethereal rather than material.

Hypothesis: Thinking takes time. As a subject progresses through the different steps of the experiment, the time it takes to complete each step will increase from case one to case four (case one: act; case two: think/act; case three: read/think/act; case four: read/think-negate/act).

Observations:

Subject 1 Data
Case 1: Act
Average: 323 milliseconds
Standard Deviation: 79 milliseconds
Case 2: Think/Act
Average: 412 milliseconds
Standard Deviation: 53 milliseconds
Case 3: Read/Think/Act
Average: 540 milliseconds
Standard Deviation: 60 milliseconds
Case 4: Read/Think-Negate/Act
Average: 606 milliseconds
Standard Deviation: 184 milliseconds

Subject 2 Data
Case 1: Act
Average: 295 milliseconds
Standard Deviation: 22 milliseconds
Case 2: Think/Act
Average: 438 milliseconds
Standard Deviation: 71 milliseconds
Case 3: Read/Think/Act
Average: 491 milliseconds
Standard Deviation: 126 milliseconds
Case 4: Read/Think-Negate/Act
Average: 586 milliseconds
Standard Deviation: 182 milliseconds

Conclusions: Thinking does, indeed, take time. If we are going by the idea that things which take time are material, then we can conclude from our findings that thinking is material rather than ethereal.

Hypothesis:
We wanted to determine if it does take time to think. Our experiment involved four actions which progressively became complex. Case 1 involved acting, Case 2 involved thinking and acting, Case 3 involved reading, thinking, and acting, and Case 4 involved reading, thinking-negating, and acting. We hypothesized that, due to the increasing complexity of each case, it would take a greater amount of time to complete a trial.

Method:
We went to serendip.brynmawr.edu/bb/reaction and performed a series of experiments, 10 trials for each case. There were 4 cases.

Observations:

Subject 1 (Rebecca)
Time to act: 350 +/- 67 milliseconds
Time to think+act: 436 +/- 110 milliseconds
Time to read+think+act: 541 +/- 113 ms
Time to read+think+negate-act: 805 +/- 224 ms

Subject 2 (Neema):
Time to act: 394 +/- 168 milliseconds
Time to think+act: 423 +/- 198 milliseconds
Time to read+think+act: 635 +/- 139 ms
Time to read+think+negate-act: 967 +/- 292 ms

Conclusion:
We found that our evidence was consistent with out hypothesis. The greater the number of tasks, the longer was the time of completion. Hence, thinking does take time. :)

The purpose of this lab was to repeat Donders’ experiments using a computer program that measured reaction times in milliseconds. The question being explored was: Is thinking material or ethereal? If thinking is material, then it involves change in matter, which takes time. If it is ethereal, then no time should elapse between the stimulus and the reaction. The trials measured (in order) the time it took to: act; think and then act, read, think and then act; and lastly read, think-negate, act. If thinking is material, then there would be a time difference between the trial one’s average time and trials 2,3,and 4’s average times.

Emily’s
Trial 1 average: 368, SD +- 62 (in milliseconds)
Trial 2 average: 443, SD +- 75
Trial 3 average: 530, SD +- 49
Trial 4 average: 515 SD +- 66

Rianna’s
Trial 1 average: 301, SD +- 39
Trial 2 average: 385; SD +- 112
Trial 3 average: 550; SD +- 124
Trial 4 average: 584; SD +- 105

In Rianna’s data, the more complicated the commands became, the longer it took. Thus, after doing the math, there is "thinking time", which would uphold the idea that thinking is material. In Emily’s data, in comparison to the rest of the class, the first two trials were some of the slowest, yet the second two trials were some of the fastest. This particularly reflected slower reaction time. Also, the average of the fourth trial was shorter than that of the third.

Introduction:
In today’s lab we examined the concept of thought and whether it is a material or ethereal process.

Prodcedure:
Following Donders’ model, we used the computer to gather data measuring the time it took an individual to 1. act, 2. think and act, 3. read, think and act, and 4. Read, think, negate, and act.

Hypothesis:
We predicted that the more thought required to complete a given task, the longer the thought process would take.

Data:

Julie:
Act: average: 359, standard deviation: 22
Think/Act: average: 399, standard deviation: 26
Read/Think/Act: average: 597, standard deviation: 70
Read/Think/Negate/Act: average:838, standard deviation: 346

Millie:
Act Average: 432, Standard Deviation: 232
Think/Act: Average 472, Standard Deviation 66
Read/Think/Act: Average:984, Standard Deviation: 387
Read/Think/Negate/Act Average:752, Standard Deviation: 113

Rachel:
Act Average: 392, Standard Deviation: 35
Think/ Act Average: 456, Standard Deviation: 49
Read/Think /Act Average: 644, Standard Deviation: 98
Read/Think/Negate/Act: 682, Standard Deviation: 62

Conclusion:
Generally, our data supported our original hypothesis. Trials 3 and 4, in Millie’s case, deviated from our hypothesis.

Introduction

The purpose of this lab was to test whether thinking was material or ethereal. In the late 1800s, a scientist named Donders came up with a REVOLUTIONARY contraption which tested thinking/reading/acting and negation times. Thanks to modern technology, we have been able to recreate Donder’s incredibly complex and cumbersome machine using the light-weight microchips of a computer program.

Donder’s hypothesis was that if it was more time-consuming to perform more complex thinking and reacting, then thinking was material and not ethereal. More matter in the brain had to interact to form more complex thoughts. Donder’s contraption, and our computer program test whether thinking takes time.

Hypothesis: More complex thinking will take more time.

Results:

Our data supported his theory: tests which involved more complex mental processes were more time-consuming.

Time to Think

In this lab, we had to determine if thinking was a material or ethereal process. When matter (material) is changed it takes time, so if thinking took time, then we could say that it was a material process. To prove this we analyzed our results from four different experiments.

In the first experiment, we had to click a button as soon as we saw an object appear above. We recorded ten timings for each of us. We determined average and standard deviation of each trial. This experiment only took into account the reaction time.

In the second experiment, we were shown dark objects and light objects, and we only had to click the button when we saw a dark object. This experiment took into account both reaction and thinking times. If we were to subtract the time of experiment 2 from experiment 1 then we would get the thinking time.

In the third experiment, we had to read a set of directions, and then perform them. This experiment also tested reaction time and thinking time, but also took into account reading time.

In the fourth experiment, we had to read a set of directions, but perform the opposite of what they said. This experiment took into account thinking, reaction, reading times, but also analysis time.

Before we started the lab, we determined that in each experiment the average time would increase. Our results were:
Debs: Case 1 Case 2 Case 3 Case 4
AVERAGE: 308 362 653 861
SD: 56 79 193 254

Sana’s Case 1 Case 2 Case 3 Case 4
AVERAGE: 299 328 1055 542
SD: 89 78 905 197

Is Thinking Material or Ethereal?

The organization of life changes when it's matter is shifted in to different spaces and states. The process of moving matter takes time and in this lab we tried to find out if thinking also takes time because then it would imply the movement of matter. Our hypothesis was thinking does not take time and that would mean that we are all material and not ethereal. This laboratory exercise was based on a notion that was developed by Emily Dickinson in the late 1800s where she questioned the validity and physical properties of thoughts and emotions.
The experiment consisted of four parts that each tested a different process that occurs in the brain. In the first part reaction time was measured, in the second part thinking was also measured, in the third part reading was added to the tasks to be measured and in the final part the client was required to negate instructions that appeared on the screen. These are our averaged results for the experiment in milliseconds:
Case 1 Joelle-224, Akudo-276 Case 2 Joelle-298, Akudo-321
Case 3 Joelle-614, Akudo-510 Case 4 Joelle-839, Akudo-478
These results showed that thinking took time and with the increasing complexity of activities more time was necessary. The observations suggest that thinking is material..

Lab #7: Time to Think

Problem: Does thinking take time?

Hypothesis: If thinking does not take time, it is ethereal and if thinking does take time, it is
material

Method: We used a computer test in order to measure different times for different tests.

Results :
Savithri- Test 1: 351 sd 21
Test 2: 456 sd 81
Test 3: 675 sd 140
Test 4: 967 sd 141

Debbie- Test 1: 248 sd 26
Test 2: 374 sd 46
Test 3: 494 sd 61
Test 4: 512 sd 56
Test one showed us reaction time.
Test two showed us reaction time + thinking time
Test three showed us reaction time + thinking time + reading time
Test four showed us reaction time + thinking time + reading time + negating time

From this, we asses that thinking does in fact take time, so thinking is

The purpose of this lab was to measure reaction time in response to thinking time. Our hypothesis was that the relationship between reaction and think time was direct. The longer it takes to think about the task (i.e. the more complicated the task), the longer the reaction time would be.

Methods
We used a computer program that gave us a specific task and we had to press a button accordingly. For example, the first and simplest of the tasks was to press a button when we saw an object. The final and most complicated of the tasks was to read a set of directions and press the button following the opposite of what the directions stated. Thus, when the directions said to press the button, we must not press the button but wait for the next command.

Observations
Act Time: 788 (plus or minus) 841ms
Think Time: 640 (plus or minus) 121ms
Read Think Time: 1745 (plus or minus) 1596ms
Read Think-Negate Time: 1191 (plus or minus) 616ms

Time to act: 788 (plus or minus) 841ms
Time to think: -148 (plus or minus) 850ms
Time to read: 1105 (plus or minus) 1601ms
Negate time: -554 (plus or minus) 1711

Discussion
Our hypothesis was proven correct.

The motivating force behind this experiment was to investigate the correlation between thinking and time.
Question: Is thinking material or ethereal?

Hypothesis: Thinking is material rather than ethereal; thinking takes time.

Method:
Repeated task of pushing butting in computer experiment to observe the difference in reaction speed of action, thinking, reading and negating. Two trials were conducted, each performing the four case experiments.

Data:

Trial one:
Act: Average 391 Milliseconds SD 55
Act and Think: Average 431 SD 60
Read Act Think: Average 537 SD 59
Read Think Negate Act: Average 550 SD 101

Trial two:
Act: Average 368 Milliseconds SD 50
Act and Think: Average 422 SD 101
Read Act Think: Average 589 SD 68
Read Think Negate Act: Average 708 SD 161

Conclusion:
The data supports our hypothesis, in that thinking is material. As the tasks of thinking, reading and negating took increasingly more time than the original case, this concludes that thinking takes time.

1) plants resembling earth trees (tall, rigid, with a hard bark-covered trunk like stem, and branches ending in leaves): 2+ different species

we considered the two "trees" we found to be different species because, while they were similar in size and general tree-like attributes, they had different leaf forms, different branch patterns and different trunk characteristics ("bark" texture and color, size, ratio to rest of tree)

2) bushes/shrubs: 5+ since these plants seemed to be of a size in between that of the "trees" and the ground cover plants, we decided to call them "bushes" due to their similarities with earth bushes. these plants were all roughly 3-6 feet tall, with branches that ended in leaves an/or needles. these were of varying shapes and sizes and textures and colors, but they all shared the characteristic of being smaller than those of the trees. Some bushes were found to bear fruit or seed-like "pods", as was one of hte trees, whereas nothing of that form was found on ground cover plants upon our brief inspection. However, this could be much better determined by more extensive research. We came up with three possible hypotheses explaining the size of hte shrubs: a) they are a different category of plants from the trees and ground cover, b) they are trees whose growth is not yet complete, or c) they are trees whose growth has been stunted by being shaded from light by the (seemingly) fully developed trees.

3) ground cover plants: 31+ these came in all shapes and sizes, from under two centimeters up to more than 30, and everthing in between. their stems were more flexible and soft than those of hte trees and shrubs, and they seemed to lack the protective "bark" layer for the most part. the exception to this were some small plans with similar leaves to one of hte trees, and our hypothesis is that this could possibly be a "sapling" or some sort of very early "tree" growth. within the category of "ground cover" we discoverd what we believe to be two sub-categories, one being "moss" and the other "fungi", based on their similarities to the earth organisms by those names. the "fungi" seemed to only be growing on what we believe to be teh dead remains of a "tree," which lead us to believe that they may be some sort of parasite, possibly the cause of the "tree"'s death. Another hypothesis is that the seemingly dead tree died because it was completely shaded by light from both the tree branches above it and a large hunk of what appeared to be shale rock. another interesting characteristic of the ground cover is taht we were able to determine that, at least amongst the plants that we sampled, there is an obvious root structure underlying hte soil while the part above is green and of a different texture. this lead us to believe that these plants possibly recieve some sort of chemical from the sunlight that affects their coloring, similar to plants on earth. we were unable to verify this finding with the trees and shrubs, as the plants were too big for any excavation under such a short research period, but with a more extended deadline and budget we would be able to further investigate this topic. what we were able to verify was that the trees seem to have a broad underground root system as well, which we concluded after observing roots partially protruding from the ground surrounding the tree which had similar "bark" patterns, leading us to believe that they were part of the same plant. also, the bushes and trees did display the same generally green coloring as the ground cover.

specific examples:

-there was one seemingly dead bush, which had no leaves and whose branches were dry, brown and brittle both inside and out upon inspection, whereas the other bushes had branches whose insides were somewhat moist and green.

-there was a big patch of ground cover which appeared different from the rest, and which seemed to be in cooler, moister soil overall. at hte time of our inspection the area was completely covered by shadow, and with further research we would be able to determine if this were a different climate which would affect the plant's progress. also, as the patch of this different vegetation was rather large, wiht all the plants growing densely together, we could assume that they do in fact reproduce and were spreading. however, few plants and VERY few ground cover plants bore any evidence of fruits, seeds, or any other reproductive method resembling those of earth plants. however, we have no way to know if this is simply because htese plants reproduce on some sort of larger cycle, which we would be able to determine wiht more extensive research and more time for the project.

-on the ground on nearly all of hte site, particularly near the "trees", we observed leaves which appeared to be from said trees and which were both brown and yellow in coloring, and appeared to be either dead or dying. the brown ones were of a brittle, easily broken texture, whereas the yellow retained some of the rubbery, plastic categories of the green tree leaves.

laura silvius
mary beth curtiss
virginia culler

sorry about the confusion

Questionables (molds and fungi that are either animal or plant)

- Moss (2)
soft spikes growing on the bark of trees
fern like, on ground between plants with star blooms

- Fungus (3)
blue fungus growing on trees, sprawling out from a central place
striped mushroom in shades of brown and white
yellow that sprouted like a mushroom on stump

Grasses (10)

Crab Grass
Club-shaped, leaved ivy
Prairie Grass
Wheat Grass
Long, thin grass, dark green, growing parallel to ground
Standard short grass, more yellow (lack of water?), 2-3 inches
Clovers (4)

Three-leaved
Four-leaved
14 round points
Speckeled leaves

Plants (15)

Strawberry-like plants, red berries
Mutant Collard Greens (2)

Green Stems, thin leaves
Purple Stems, wide leaves

Marigold-like, non-blooming plants
Dandilions (4)

Spiked leaves
Low, fuzzy
Rounded
Fern-like, centralized, low to ground

Small plants(7)

Vertical (5)

Spiked, enlongated leaves, with red base
Minature pussywillow, long stem, with white bloom
Lower leaves purple, upper leaves green (of medium size)
Violets
Mushroom-shaped leaves

Horizontal (2)

Red stem, small round green leaves, glossed
Thin, green Ivy with small staggered leaves

Trees and Bushes (5)

Maple tree
Silvery-green leaves, pointy
Pine bush with red berries
Larger leaves, thin, yellowy green
Small, hard, glossy dark-green leaves

• "Mosses": [on the ground] Mosses do not have the strong root structure to support upward growth. Instead, they grow out across the ground, covering a larger ground area than most of the other plants "discovered." (2 specimens found)
  
• "Grasses": [close to the ground] Grasses tend to be long and thin, with only one section. The root structure is relatively weak, and broke when we cruelly yanked the blade of grass from its home, the ground. It stands upright, but remains flexible, not retaining its upright posture when confronted by wind, stomping feet, or other forces of nature. (8 specimens found)
  
• "Trees": [farthest from the ground] Trees have sturdy, thick trunks that are rough to the touch. Of the four categories of plants, the trees grow the tallest. The trunk is very visible; only the tops of the trees are covered by leaves, which extend from smaller branches, all connected to the central trunk, which grows out of a complex root system. (2 specimens found)
  
• "Shrubs": [far from the ground] These feisty organisms are defined by an intersection of the characteristics usually associated with both grasses and trees. (Neato!) Their trunks are weaker than those of trees, and the complexity of their branches echoes the complexity of the trees' root systems. Shrubs do not have a clearly-defined trunk (as found in "trees"), but rather there are many branches sprouting from the ground. (3 specimens found)
  

Conclusion: We first organized our findings into groups such as plants, trees, bushes, fungi and moss. Trees we recognized as being taller than the average man, with a tough skin (bark) on its base and large braches with leaves nearing the top. Bushes were defined as being about 4-6 feet tall, wide and dense (we chose not to include the dead bush). Fungi we defined by where and how they grew: on the trees (feeding off another organism...animals?) and they grew out. Moss grew more horizontally and grew in cracks, around roots and on rocks and concrete. Plants was the widest category, incorporating the most divesity, including small plants, plants whose growth was more obviously horizontal or vertical.

- Moss (2)
soft spikes growing on the bark of trees
fern like, on ground between plants with star blooms

- Fungus (3)
blue fungus growing on trees, sprawling out from a central place
striped mushroom in shades of brown and white
yellow that sprouted like a mushroom on stump

Grasses (10)

Crab Grass
Club-shaped, leaved ivy
Prairie Grass
Wheat Grass
Long, thin grass, dark green, growing parallel to ground
Standard short grass, more yellow (lack of water?), 2-3 inches
Clovers (4)

Three-leaved
Four-leaved
14 round points
Speckeled leaves

Plants (15)

Strawberry-like plants, red berries
Mutant Collard Greens (2)

Green Stems, thin leaves
Purple Stems, wide leaves

Marigold-like, non-blooming plants
Dandilions (4)

Spiked leaves
Low, fuzzy
Rounded
Fern-like, centralized, low to ground

Small plants(7)

Vertical (5)

Spiked, enlongated leaves, with red base
Minature pussywillow, long stem, with white bloom
Lower leaves purple, upper leaves green (of medium size)
Violets
Mushroom-shaped leaves

Horizontal (2)

Red stem, small round green leaves, glossed
Thin, green Ivy with small staggered leaves

Trees and Bushes (5)

Maple tree
Silvery-green leaves, pointy
Pine bush with red berries
Larger leaves, thin, yellowy green
Small, hard, glossy dark-green leaves

Results for Experiment #1

After timing for 10-second intervals for each set of microspheres (2, 4 and 8 micrones), our results were as follows:

2 micrones moved 2.6 um

4 micrones moved 1.3 um

8 micrones moves .65 um

***Our hypothesis, that smaller micrones move more distance in the same amount of time than larger micrones, was upheld through our observations.

Results for Experiment #2

Trial 1- 3% salt: mostly turgid cells but a few partially plasmolyzed cells

Trial 2- 0% (DIH2O): still mostly turgid cells but less partially plasmolyzed cells

Trial 3- 25% salt: more plasmolyzed cells and less turgid cells

*THE CELLS IN DIFFERENT ENVIRONMENTS*

Attack of The Three Little Salt Molecules
There once were three little salt molecules; their names were 3%, 0%, and 25%. All they wanted to do was to break into the onion's cell wall, so that they could have control over the cell membrane. The three little molecules each tried, and had different results.
The 3% went first. He tried to huff and puff the cell wall down, but only could blow through a few times. The onion cell was only partially injured.
Next, 0% decided to take a turn. He tried to huff and puff the onion's cell wall down too, but he failed miserably. He could only get a very few parts of the wall to let him in.
Last, but definitely not least, 25% ran up to the cell wall and more than huffed and puffed; he blew the weak wall down, a lot. He won the three little salt molecules' contest, because he was the strongest salt of all. yay!
THE END.