Effect of Food Source on Enzymatic Activity in C. maculatus [draft 2]
RHodson_Independent_project_lab_report
1. An Analysis of the Amount of β-carotene in Carrot Samples
By: Roman Hodson (rh28397)
TA: Maggie Weber
May 7, 2015
2. 1
Abstract
This experiment used UV-Vis spectrophotometry to determine if the amount of β-
carotene in non-organic and organic carrot samples decreased after being left to sit for a week in
a dark laboratory cabinet due to rotting. The data was inconclusive however, because the samples
were not properly dried before experimentation meaning they contained added water weight, so
less carrot was weighed out than expected. In addition, the calculated β-carotene concentrations
were less than the expected value of 74.06 ppm, which is most likely due to loss of β-carotene
during the extraction procedure.1
However, the experiment was successful in determining that β-
carotene absorbs at 449 nm, as reported by Biswas et. al.1
Therefore, the results are inconclusive
as they were not able to confirm or deny the hypothesis.
Introduction/Background
This experiment is concerned with determining the amount of β-carotene in organic and
non-organic carrot samples using UV-Vis spectrophotometry. The molecular structure of β-
carotene is provided in Figure 1.
Figure 1. β-carotene Structure2
As shown in Figure 1, β-carotene is a large, non-polar organic compound, classified as a
carotenoid, or a phytochemical.3
Carotenoids are red, orange, or yellow fat-soluble compounds,
mainly found in plants and vegetables.3
The β-carotene in carrots is what gives carrots their
orange color. β-carotene is referred to as a phytochemical when being described as a compound
which affects human health.4
As a phytochemical, β-carotene has antioxidant properties, and
3. 2
diets which contain β-carotene have been shown to reduce the risk of certain diseases, such as
certain cancers and diabetes.4
In addition to reducing the risk of varying diseases, β-carotene
allows humans to access vitamin A. The structure of vitamin A is shown in Figure 2.
Figure 2. Vitamin A Structure5
Vitamin A is vital for human health, as it has important roles in embryonic development,
immune system health, eye development, and vision.6
The National Institutes of Health
recommends 0.05 mcg RAE of β-carotene, and 900 mcg RAE of vitamin A for males and 700
mcg RAE of vitamin A for females per day.7
Since β-carotene and vitamin A work in tandem to
promote good health, their consumption is crucial. Therefore, it is important to let the public
know the amount of β-carotene they are consuming in their diet, so they can decide if they need
to adjust their eating habits.
There was a method developed, reported by Biswas et. al, which used UV-Vis
spectrophotometry to determine the amount of β-carotene in carrot samples.1
UV-Vis
spectrophotometry is based on the concept that molecules with pi-bonding or non-bonding
electrons can absorb light in the visible and ultraviolet (UV) spectrum, which promotes their
electrons to higher energy levels.8
The energy of a photon is described by Equation 1
E = hν =
ℎ𝑐
𝜆
(1)
4. 3
where E is the energy of the photon (J), h is Planck’s constant (J s), ν is the frequency of light
(Hz), c is the speed of light (m s-1
), and λ is the wavelength of light (nm).8
A transition from a
lower energy level to a higher energy level can only occur if the energy of the photon equals the
difference in energy between the two energy levels.8
In addition, since the frequency of light is
invariant in a vacuum and wavelength is inversely proportional to energy, a smaller energy gap
transition corresponds to a longer wavelength of light. Conversely, the larger the energy gap
between energy levels, the shorter the wavelength of light which is required for excitation.8
Figure 3 shows the process of absorption.
Figure 3. Absorption9
Absorbance can be used as a spectroscopic technique to determine the concentration of a
species, using Beer’s Law. Beer’s Law states that the absorbance of a species is proportional to
its concentration, shown in Equation 2
A = εlc (2)
5. 4
where A is absorbance, ε is the molar extinction coefficient (M-1
cm-1
), l is the path length of the
cuvette (cm), and c is the concentration of the species (M-1
). In addition, Beer’s Law is based on
the idea that the particles are infinitely far apart and do not interact with one another.8
This
previous statement means that the solution which contains the absorbing species must be
adequately dilute for it to be modeled using Beer’s Law. An important aspect of Beer’s Law is
the molar extinction coefficient, which describes how well a species absorbs light. Even if a
species is dilute in solution, if it has a large molar extinction coefficient it still has the ability to
absorb a large amount of light. Absorbance is measured as a function of the intensity of light,
shown in Equation 3
A = -log(
𝐼
𝐼 𝑜
) (3)
where Io is the initial intensity of light, and I is the intensity of light it passes through the sample.
The value of absorbance is important for UV-Vis spectrophotometry, as it determines whether or
not the relationship between concentration and absorbance is linear. For example, if the
absorbance has a value of 1, 90% of the incoming light is being absorbed by the sample. This
high absorbance causes deviation from linearity, as the sample approaches optical saturation at
absorbance values greater than 1.10
Optical saturation is a phenomenon where there are equal
populations of molecules in the ground and excited states.10
As the absorbing species approaches
optical saturation, it can no longer absorb light in a linear fashion. Therefore, the amount of light
the species absorbs decreases with increasing absorbance values. A representative graph of
Beer’s Law and its deviations from linearity is provided in Figure 4.
6. 5
Figure 4. Beer’s Law Representative Graph11
If the absorbance is too high, UV-Vis spectrophotometry cannot accurately determine the
concentration of a species in solution.
As stated previously, UV-Vis spectrophotometry uses absorbance to determine the
concentration of a species in solution. A diagram of a UV-Vis spectrophotometer is provided in
Figure 5.
Figure 5. UV-Vis Spectrophotometer12
As shown in Figure 5, the initial intensity of light decreases as it passes through the sample. An
absorption spectrum is made by comparing a known initial intensity of light to the intensity of
light after it passes through a sample.13
In addition, the UV-Vis spectrophotometer uses a range
7. 6
of wavelengths to create an absorbance spectrum. This range of wavelengths corresponds to
varying photon energies, and therefore varying excited states, shown in Figure 6.
Figure 6. Absorption and Differing Excited States14
Using the knowledge that certain transitions only occur with the correct amount of energy, a
sample is exposed to a range of wavelengths. Allowing the sample to absorb various
wavelengths allows for the determination of what wavelengths cause excitation. Figure 7
provides an example of an absorbance spectrum.
8. 7
Figure 7. Absorbance Spectrum9
Looking at Figure 7, it is evident that a species absorbs over a range of wavelengths rather than
just one wavelength. This range of absorbance, rather than just one absorbance peak, is due to
solvation energetics. In solution, the solute particles are surrounded by solvent particles which
help to dissolve the solute.15
However, not all of the solvent particles are arranged the same way
across the solution, which leads to a distribution of energy between the solute particles.15
Solvation energetics is demonstrated in Figure 8, with Figure 9 comparing a spectrum with and
without solvation energetics.
9. 8
Figure 8. Solvation Energetics15
Figure 9. Absorption Spectrum with and without Solvation Energetics15
As shown in Figure 9, an absorbance spectrum without solvation energetics has sharp peaks
where the energy level transitions occur, rather than broad peaks. Solvation energetics can be
avoided if the sample is in the gas phase.15
However, in this experiment the sample is in the
liquid phase.
As stated previously, this experiment used UV-Vis spectrophotometry to determine the
amount of β-carotene in non-organic and carrot samples. The purpose of this experiment was to
determine whether the non-organic carrots or organic carrots contained the most β-carotene. In
10. 9
addition, this experiment investigated if the amount of β-carotene in the non-organic and organic
carrot samples decreased due to rotting after being left to sit for a week in a dark laboratory
cabinet. It is expected that the amount of β-carotene will decrease after the samples are left to sit
out for a week in the dark, due to the carrot rotting.
Experimental
This experiment consisted of an extraction process, the creation of standard addition
solutions, as well as a spike recovery in order to determine the amount of β-carotene in non-
organic and organic carrot samples. A study by Biswas et. al reported that acetone works as an
extracting solvent for β-carotene.1
However, during the first three weeks of experimentation,
acetone proved to be an inadequate extracting solvent, as the solution became cloudy during the
dilution steps in the creation of standard additions solutions. Using acetone as a solvent most
likely extracted other compounds, such as various lipids, inherent in the carrot besides the β-
carotene. This extraction of additional compounds caused the solution to become cloudy upon
further addition of acetone. Therefore, hexanes was implemented as an extracting solvent, as
suggested in a study by Taungbodhitham et. al, which proved to be effective.16
In preparing for the extraction process, samples of non-organic and organic carrots were
finely ground using a blender the night before experimentation. During experimentation, three 12
g samples of non-organic and organic carrots were placed into 50 mL centrifuge tubes. Then,
these centrifuge tubes had 15 mL of hexanes added to them, and were centrifuged for 5 minutes
at 4000 revolutions/minute. While these samples were centrifuging, a 5 mg/ 50 mL stock
solution of β-carotene in hexanes was created. After centrifuging, the extracted samples were
11. 10
pooled into two different beakers, denoting if they were non-organic or organic, and were then
filtered 4 times using vacuum filtration.
After the filtration steps, standard addition solutions were created. During this part of the
experiment, 4 standard solutions of 25x dilution were made in triplicate for each of the carrot
types, resulting in a 24 total standard addition solutions. The standard addition solutions were
created using 1.6, 0.8, 0.4, and 0.2 ppm additions of the stock β-carotene solution. After creating
the standard addition solutions, the samples were run through the UV-Vis spectrophotometer
over a wavelength range of 300-600 nm, using hexanes as a blank. The same procedure was
carried out for the week old carrot samples.
The next part of the experimental procedure consisted of spike recoveries in order to
determine the amount of β-carotene lost during the extraction step. For this procedure, 12 g of
non-organic and organic carrot samples had 1.6 ppm β-carotene added to them before
undergoing the extraction process described previously. After undergoing the same extraction,
filtration, and 25x dilution process, the spike recovery samples were run through the UV-Vis at a
wavelength range of 300-600 nm using hexanes as a blank.
Results and Discussion
This section does not include all of the data obtained during experimentation, but instead
contains representative Tables and Figures. Supplementary Tables and Figures are provided in
the appendix. In the context of this report, the word “fresh” indicates that the samples were
prepared the night before experimentation, and word “week old” indicates the samples that were
left to sit for a week in a dark laboratory cabinet. Figures 10-13 provide representative
absorbance spectra and standard additions curves for the fresh non-organic and organic samples.
12. 11
In addition, Table 1 provides the statistical data obtained from the standard additions curves for
the fresh samples, with Table 2 providing the data in terms of weight percent.
Figure 10. Organic Sample A Absorbance Spectrum
Figure 11. Organic Sample A Standard Additions Curve
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
400 420 440 460 480 500
Absorbance
Wavelength (nm)
Organic Sample A
1.6 ppm
0.8 ppm
0.4 ppm
0.2 ppm
449 nm
y = 0.1768x + 0.0618
R² = 0.999
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
-1 -0.5 0 0.5 1 1.5 2 2.5 3
Absorbance
Concentration (ppm)
Organic Standard Addition A
14. 13
Table 1. β-carotene Concentrations of Fresh Carrot Samples
Sample Average Conc
(ppm)
Standard
Deviation
%RSD Confidence
Interval
(ppm)
Non-Organic 10.45 0.54 5.15 10.45 ± 0.91
Organic 8.33 1.39 16.66 8.33 ± 2.34
Table 2. β-carotene Weight Percent Data of Fresh Carrot Samples
Sample Average Mass
(mg)
Standard
Deviation
%RSD Confidence
Interval (mg)
Weight
Percent (%)
Non-Organic 0.157 8 x 10-3
5 0.157 ± 0.014 1.31 x 10-3
Organic 0.125 2.1 x 10-2
17 0.125 ± 0.036 1.04 x 10-3
Looking at the data from Tables 1 and 2, the average concentration of β-carotene in the
non-organic samples is 14.1% of the expected concentration of 74.06 ppm, and the average
concentration of β-carotene in the organic samples is 11.2% of the expected concentration. This
difference in concentrations is most likely due to the loss of β-carotene during the extraction
steps. In reality, the average masses should be higher for the carrot samples, and therefore the
weight percent of β-carotene in the carrot samples should be greater than the values calculated.
However, looking at Figures 10 and 12, the sample absorbed at or near 449 nm, which was the
wavelength at which β-carotene absorbs, as reported by Biswas et. al.1
The following data is representative of the week old non-organic and organic carrot
samples. Supplementary Tables and Figures are provided in the appendix. Figures 14-17 show
the absorbance spectra and standard additions curves for the week old non-organic and organic
samples. In addition, Table 3 provides the statistical data obtained from the standard additions
curves for the non-organic and organic carrot samples, with Table 4 providing the data in terms
15. 14
of weight percent. In addition, Figures 18 and 19 show the absorbance spectra of the spike
recovery samples.
Figure 14. Week Old Non-Organic Sample B Absorbance Spectrum
Figure 15. Week Old Non-Organic Sample B Standard Additions Curve
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
400 420 440 460 480 500
Absorbance
Wavelength (nm)
Week Old Non-Organic Sample B
449 nm
y = 0.1186x + 0.1709
R² = 0.9768
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
-3 -2 -1 0 1 2 3
Absorbance
Concentration (ppm)
Week Old Non-Organic B Standard
Additions
16. 15
Figure 16. Week Old Organic Sample A Absorbance Spectrum
Figure 17. Week Old Organic Sample A Standard Additions Curve
0
0.05
0.1
0.15
0.2
0.25
0.3
400 420 440 460 480 500
Absorbance
Wavelength (nm)
Week Old Organic Sample A
1.6 ppm
0.8 ppm
0.4 ppm
0.2 ppm
449 nm
y = 0.1213x + 0.0589
R² = 0.9916
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
-3 -2 -1 0 1 2 3
Absorbance
Concentration (ppm)
Week Old Organic A Standard Additions
17. 16
Table 3. β-carotene Concentrations of Week Old Carrot Samples
Sample Average Conc
(ppm)
Standard
Deviation
%RSD Confidence
Interval
(ppm)
Non-Organic 21.32 13.57 63.65 21.32 ± 22.88
Organic 12.27 0.15 1.20 12.27 ± 0.25
Table 4. β-carotene Weight Percent Data of Week Old Carrot Samples
Sample Average Mass
(mg)
Standard
Deviation
%RSD Confidence
Interval (mg)
Weight
Percent (%)
Non-Organic 0.319 0.204 64 0.319 ± 0.343 2.7 x 10-2
Organic 0.184 2 x 10-3
1 0.184 ± 0.004 1.5 x 10-2
Looking at the data in Tables 3 and 4, it is apparent that the amount of β-carotene in the
carrot samples seem to have increased by sitting in the dark for a week. However, this previous
statement is most likely not the case. It is most likely that the apparent increase in β-carotene
concentration is due to water’s evaporating during the samples’ time in the laboratory cabinet.
During the week with the fresh samples, there would be added water weight to the samples
because the water would not have evaporated yet, and during the weighing process less carrot
would be weighed out compared to a sample with its water evaporated. In addition, the data from
the non-organic sample is not statistically reliable as it has a large standard deviation, and as
indicated by Table 4, an impossible confidence interval. This inconclusive data is most likely
caused by the results gathered from Figure 31 in the appendix, as the spectrum is not reliable.
However, this data does show that the β-carotene does absorb at a wavelength at or near 449 nm.
In addition, the results show that results closer to the expected concentration can be achieved if
18. 17
the samples are dried before experimentation, because the dry samples do not carry the extra
water weight.
In addition to the standard addition solutions, spike recoveries were performed in order to
determine the amount of β-carotene lost during extraction. Figures 18 and 19 provide the spike
recovery spectra, and Table 5 provides the spike recovery concentration data. Also, Figure 20
provides the hexanes blank spectrum.
Figure 18. Non-Organic Spike Recovery Spectrum
-0.005
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
400 420 440 460 480 500
Absorbance
Wavelength (nm)
Non-Organic Spike Recovery
449 nm
20. 19
Table 5. Spike Recovery Data
Sample Spike Concentration (ppm) Extraction Efficiency (%)
Non-Organic 45.0 24.1%
Organic 50.5 18.8%
In addition to determining the extraction efficiency, the limit of detection was determined to be 3
x 10-3
ppm, which was calculated in part using the blank absorbance spectrum provided in Figure
20. Looking at the data from Figures 18 and 19, the results show that β-carotene absorbs at 449
nm. However, the results from the spike recoveries are not conclusive, as the absorbance values
do not fall within the range of 0.1-1.0, as this previously stated range is optimal for determining
concentrations.10
In addition, these spike recoveries were performed with the fresh samples, and
therefore had added water weight to them, meaning that less carrot was weighed out than what
was recorded. These previously stated factors render the data from the spike recoveries
unreliable.
Conclusion
The data from this experiment is not conclusive as it is unreliable and could not be used
to confirm or deny the hypothesis. By not drying the fresh samples before experimentation, the
samples were incorrectly weighed, and therefore less β-carotene was extracted than planned,
which led to lesser β-carotene concentrations than the results from the week old samples. If the
samples were to have been dried before experimentation, the results possibly could have been
used to determine if the amount of β-carotene decreases over time. In addition, neither the fresh
nor the week old sample β-carotene concentrations were close to the expected value of 74.06
ppm, which is most likely due to loss of β-carotene during the extraction procedure. In addition,
the spike recovery data is not reliable either as it came from the fresh samples which had the
21. 20
added water weight. However, this experiment was successful in determining that β-carotene
absorbs at a wavelength at or near 449 nm, as expected from the report by Biswas et. al.1
In
conclusion, the results from the experiment are inconclusive, and better data could have been
obtained by drying out the samples before experimentation.
References
1. Biswas, A.K., Sahoo, J., & Chatli, M.K. (2011). A simple UV-Vis spectrophotometric method
for determination of β-carotene content in raw carrot, sweet potato, and supplemented chicken
meat nuggets. Food Science and Technology, 44, 1809-1813.
2. Chemical Book. (n.d.). Beta-Carotene. Retrieved April 18, 2015, from
http://www.chemicalbook.com/ChemicalProductProperty_EN_cb4148267.htm
3. MAYO Clinic. (n.d.). Beta-Carotene. Retrieved April 18, 2015, from
http://www.mayoclinic.org/drugs-supplements/beta-carotene/background/hrb-20058836
4. American Cancer Society. (n.d.). Phytochemicals. Retrieved April 18, 2015, from
http://www.cancer.org/treatment/treatmentsandsideeffects/complementaryandalternativemedicin
e/herbsvitaminsandminerals/phytochemicals
5. Vision Training. (n.d.). Vitamin A. Retrieved April 18, 2015, from http://www.vision-
training.com/en/eNewsletter/Australia/Winter%2008/Dry%20eyes/Vitamin%20A.html
6. Oregon State University. (n.d.). Vitamin A. Retrieved April 18, 2015, from
http://lpi.oregonstate.edu/mic/vitamins/vitamin-A
7. The National Institutes of Health. (n.d.). Vitamin A Fact Sheet. Retrieved April 18, 2015, from
http://ods.od.nih.gov/factsheets/VitaminA-HealthProfessional/
8. Harris, Daniel C., Quantitative Chemical Analysis, 8th
Ed. W.H. Freeman and Company:
New York, 2010, pp. 394-400, 404.
9. UC Davis. (n.d.). Overview of Spectroscopy. Retrieved April 18, 2015, from
http://chemwiki.ucdavis.edu/Analytical_Chemistry/Analytical_Chemistry_2.0/10_Spectroscopic
_Methods/10A%3A_Overview_of_Spectroscopy
10. O'Haver, T. (n.d.). Instrumental Deviation from Beer's Law. Retrieved April 18, 2015, 2015,
from http://terpconnect.umd.edu/~toh/models/BeersLaw.html
22. 21
11. SenseAir. (n.d.). Beer's Law [Image] Retrieved April 18, 2015, 2015 .
http://www.senseair.se/senseair/ research-development/technology/lambert-%E2%80%93-beers-
law/
12. Bio 750. (n.d.). Spectroscopy - UV-Vis [Image] Retrieved April 18, 2015, 2015 . Retrieved
from http://www.sci.sdsu.edu/TFrey/Bio750/ UV-VisSpectroscopy.html
13. UT Dept. of Chemistry (2015). CH376K Fluorimetry: Determination of Quinine in Tonic
Water & Urine.
14. UCLA. (n.d.). Infrared Spectroscopy. Retrieved April 18, 2015, from
http://www.wag.caltech.edu/home/jang/genchem/infrared.htm
15. Shear, J. (n.d.). Solvation Energetics. Retrieved April 18, 2015, from
https://utexas.instructure.com/courses/1128486/files/folder/Course%2520Notes?preview=35842
117
16. Taungbodhitham, A. K., Jones, G. P., Wahlqvist, M. L., & Briggs, D. R. (1998). Evaluation
of Extraction Method for the Analysis of Carotenoids in Fruits and Vegetables. Food Chemistry,
63(4), 577-584.
23. 22
Appendix
1. Calculating concentration of β-carotene concentration organic sample A
Linear Fit: y = 0.1768x + 0.0618
x-intercept =
0.0618
−0.1768
= 0.349 ppm
Multiply by dilution factor: 0.349 ppm x 25 = 8.74 ppm
2. Calculating β-carotene average concentration of organic samples
Average concentration =
8.74+6.79+9.47
3
= 8.33 ppm
3. Calculating β-carotene standard deviation of organic samples
Standard deviation = √
(8.74−8.33)2+ (6.79−8.33)2+ (9.47−8.33)2
2
= 1.39
4. Calculating %RSD of organic samples
%RSD =
𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛
𝑎𝑣𝑒𝑟𝑎𝑔𝑒
× 100 =
1.39
8.33
× 100 = 16.66
5. Calculating confidence interval of organic samples
Confidence interval = average ± t
𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛
√ 𝑛
Confidence interval = 8.33 ± (2.92)
1.39
√3
= 8.33 ± 2.34 ppm
6. Spike Recovery Calculations (Non-Organic)
𝑝𝑝𝑚 𝛽 − 𝑐𝑎𝑟𝑜𝑡𝑒𝑛𝑒 𝑖𝑛 5 𝑚𝐿 𝑢𝑛𝑘𝑛𝑜𝑤𝑛 𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛
𝑝𝑝𝑚 𝛽 − 𝑐𝑎𝑟𝑜𝑡𝑒𝑛𝑒 𝑖𝑛 5 𝑚𝐿 𝑠𝑝𝑖𝑘𝑒𝑑 𝑢𝑛𝑘𝑛𝑜𝑤𝑛 𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛
=
𝑎𝑏𝑠𝑜𝑟𝑏𝑎𝑛𝑐𝑒 𝑝𝑒𝑎𝑘 𝑜𝑓 𝑢𝑛𝑘𝑛𝑜𝑤𝑛
𝑎𝑏𝑠𝑜𝑟𝑏𝑎𝑛𝑐𝑒 𝑝𝑒𝑎𝑘 𝑜𝑓 𝑠𝑝𝑖𝑘𝑒𝑑 𝑢𝑛𝑘𝑛𝑜𝑤𝑛
Β-carotene spike: 1.6 ppm
Absorbance peak of unknown = 0.309
Absorbance peak of spiked unknown = 0.0347
𝑥
𝑥 + 1.6 𝑝𝑝𝑚
=
0.309
0.0347
Solve for x
x = 1.8 ppm
multiply by dilution factor of 25
(1.8 ppm)(25) = 45.0 ppm
24. 23
7. Calculating limit of detection (used slope of Non-Organic Samples Standard Additions Curve)
Standard deviation = 1.91 x 10-4
LOD =
3 𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛
𝑠𝑙𝑜𝑝𝑒
Slope = 0.1771
LOD = 3 x 10-3
ppm
8. Calculating Weight Percent (Used Non-Organic Fresh Data)
Concentrations = 10.6, 9.84, and 10.8 ppm
Convert to mg
Mass = 10.6 ppm x (15 mL/1000) = 0.160 mg
Repeat for all concentrations
Find average mass
Average mass =
0.160 𝑚𝑔+0.147 𝑚𝑔+0.163 𝑚𝑔
3
= 0.157 𝑚𝑔
Weight Percent =
0.157 𝑚𝑔
1200 𝑚𝑔 𝑐𝑎𝑟𝑟𝑜𝑡
x 100% = 1.31 x 10-3
%
8. Supplementary Figures 21-36
Figure 21. Organic Sample B Absorbance Spectrum
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
400 420 440 460 480 500
Absorbance
Wavelength (nm)
Organic Sample B
1.6 ppm
0.8 ppm
0.4 ppm
0.2 ppm
449 nm
