Robby Rigby
Department of Chemistry and Biochemistry
California State University, San Bernardino
PRISM Summer Research Project (July 11-29, 2011)
Mentor: Dr. Kimberley R. Cousins
Correlations Between Citrus Fruit Properties and
Ascorbic Acid Content
ABSTRACT
Vitamin C content in a citrus fruit can be determined by titration with iodine solution. By
analysis of a citrus fruit’s physical properties (pH, sugar content, total volume of juice, density,
and circumference), a partial least-squares regression can be performed, and the total content of
ascorbic acid inside of a citrus fruit can be predicted. There is definitely correlation between the
pH and vitamin C content in Valencia Oranges, as well as the pH versus the Brix values. By
comparison to grapefruit data, oranges and grapefruits are chemically dissimilar and should be
modeled separately.
INTRODUCTION
L-ascorbic acid, generally called vitamin C, is an essential micronutrient that has been
proven to help aid the immune system of many organisms. Although many animals and plants
are capable of creating their own vitamin C from glucose, unfortunately humans are not
competent, so consumption of vitamin C is vital.
Vitamin C is best known for its ability to prevent and cure scurvy; however, this powerful
antioxidant has many other benefits. Vitamin C has demonstrated its ability to prevent heart
disease, lower cholesterol, strengthen our connective tissues through the production of collagen,
and promote our state of mind through the synthesis of neurotransmitters. Since vitamin C has
been linked so tightly to our well-being, it is important to understand how we can consume the
correct foods containing vitamin C, how we can decrease the degradation of this nutrient, and
study the mechanisms and correlations related to ascorbic acid content in our foods.
Fortunately, vitamin C is present in many citrus fruits. Vitamin C is most commonly
consumed through oranges or other fruits and vegetables, but in this experiment the study of
vitamin C in oranges, specifically Valencia Oranges, and grapefruits will be analyzed.
Throughout this experiment, a correlation of vitamin C content versus other aspects and
properties of the citrus fruit will be observed and analyzed. There are many factors that
contribute to the vitamin C content in citrus fruits, which include, but are not limited to the
maturity, the breed, and production. Now although variation between samples is usually a
significant problem in certain research projects, this project commends variation in the physical
properties in order to obtain variation in data. As a result, Valencia Oranges will be studied, but
the location of harvest will vary.
In this research, the variation of vitamin C content between different Valencia Oranges
will be correlated with different physical properties. The citrus fruits will be examined by their
density, circumference, sugar content (Brix value), pH, and their total volume of juice present.
Since there are different concentrations of acids present in citrus fruits (ascorbic, malic, citric,
and lactic acid), citrus fruits will generally have different hydrogen concentrations; therefore
different acidity levels.
The sugar content of the citrus fruits will be determined with an Abbe-Refractometer.
The Abbe-Refractometer measures the refractive index from a drop of juice extracted from each
fruit. The Abbe-Refractometer sandwiches a sample (liquid or solid) between a refracting and
illuminating prism. A light source is then passed through the illuminating prism and the
refractive index of the sample can be measured since an angle of incidence is formed from the
refraction of light. The angle of incidence corresponds to the refractive index, which is then used
to determine the sugar content, or the percent sucrose solid Brix in each citrus fruit. This is only
possible because the refractive index of water, 1.333, and the refractive indices of solutions of
sucrose in water are different depending on the concentrations of sucrose present. From a
calibration line of refractive indices and percent solid Brix, interpolation can be used to
determine the Brix values of each citrus fruit.
After obtaining data from all the physical properties being analyzed, the statistical
program, R, will be used to calculate a partial least-squares regression line from a few
components of raw data with the kernel algorithm available through the program. A partial leastsquares regression (PLSR) model, specifically created with the kernel algorithm, is desired for
raw data containing many variables, with rather few trials or samples being tested. The PLSR
model is typically used to create a linear relationship between a set of output and input variables
with the use of matrices. By entering the raw data into R, uncorrelated latent variables are first
produced and then a partial least-squares regression is conducted on the subset of latent
variables, forming coefficients for each variable inputted. From the coefficients created, analysis
of the data can be performed to determine which variable is contributing the most to the PLSR.
This is done on the basis of the size of the coefficient, as well as the size of the variables’ output.
The PLSR is used to derive an equation so the prediction of vitamin C content in citrus fruit can
be acquired on the basis of its physical properties.
The goal of this research is to produce a simplistic strategy to predicting vitamin C
content in citrus fruits while they are being harvested.
PROCEDURE/ METHODS
First an ascorbic acid solution was produced by dissolving 0.1000 grams of ascorbic acid
in a 100 ml volumetric flask. This solution was used to standardize an iodine solution composed
of 5.00 grams of potassium iodide, 0.268 grams of KIO3, and 30 mL of 3 M sulfuric acid, diluted
to the mark in a 500 mL volumetric flask. Next, a 25.0 mL aliquot of the ascorbic acid solution
was placed into an Erlenmeyer flask with an addition of 30 drops of 1% starch indicator. The
ascorbic acid solution was then titrated with the iodine solution until a blue endpoint was
persistent for 20 seconds. A total of three trials were obtained at 0.1 mL precision. The iodine
solution was re-standardized every day to maintain accurate readings.
After daily standardization of the iodine solution, a citrus fruit, specifically an orange or a
grapefruit was analyzed based on its mass, volume, density, circumference, Vitamin C content,
total juice volume, brix level, and its pH. The mass of the citrus fruit was obtained by a balance
and was recorded to two decimal places.
The volume was determined by a difference of volume method. For the smaller sized
fruits, the volume was determined from the change in volume after the fruit was added to a
volume of water in a 2000 mL graduated cylinder. For the larger sized fruits, a large container
was placed into an even larger empty container, and then the smaller container was filled with
water until nearly overfilled. The fruit was then placed into the water and the displaced water
was measured in the 2000 mL graduated cylinder. The density was then determined from the
recorded mass and volume of each fruit analyzed.
After the volume was determined, the circumference was determined. The fruit was
measured with a copper wire and ruler from stem to stem. A measurement perpendicular to the
first measurement was taken as well. An average circumference was then determined from the
two measurements and then recorded.
After determining the circumference, the fruits were sliced down the middle and then
juiced by hand. Through careful and diligent juicing, the total volume of juice was measured
with a graduated cylinder. After the total volume of juice was determined, a coffee filter was
used to remove the pulp and to produce a juice that was much easier to pipette accurately for
future titration. The pH of the juice was tested with a pH meter, and the juice was also used for
titration.
After determining the pH of the juice, a small sample was distributed to a AbbeRefractometer with a pipette. The compensator dial on the Abbe-Refractometer was adjusted to
match the temperature on the thermometer, and then the juice droplet was analyzed. The
refracted index measured was recorded to four decimal places. The recorded refracted index
observed with each juice sample was used to determine the sugar content or the percent sucrose
solid Brix level in the citrus fruit through a calibration line, created from refracted index data
discovered through the Internet.
Before beginning the titration, a 10 mL aliquot of the juice from the fruit was pipetted
quantitatively and placed into a 50 mL Erlenmeyer flask, along with about 20 drops of 1% starch
indicator. The juice was then titrated with the standardized iodine solution until a blue endpoint
was reached and persisted for 20 seconds. A total of three trials were completed for each juice
titration at 0.1 mL precision.
The titration determined the Vitamin C content present in the 10 mL aliquot of juice
being tested. This value was then re-written to a value of mg/100 mL Vitamin C content in the
orange. With the use of the Vitamin C content per 100 mL, an accurate measure of Vitamin C
present in the whole fruit was determined.
In this experiment, a total of twelve Valencia Oranges and four grapefruits from varying
locations in California were tested.
DATA/CALCULATIONS
Standardization
Mass of Ascorbic Acid
0.1011 g / 100 ml
Trial
Volume of Iodine Titrant Required
1
2
3
Average
Standard Deviation
Concentration of Standard (g AA/ ml Iodine)
19.8
19.75
19.75
19.76666667
0.028867513
0.001279
Re-Standardization Oranges (8-12) Grapefruits (1-4)
Mass of Ascorbic Acid
0.1019 g / 100ml
Trial
Volume of Iodine Titrant Required
1
18.8
2
18.85
3
18.9
18.85
0.05
Average
Standard Deviation
Concentration of Standard (g AA/ml Iodine)
Vitamin C Present
Sample
Orange: 1
Trials
Average
Standard Deviation
2
0.001351
Vol. of Iodine Titrant (Per 10ml Juice) Vit C (g/10 ml)
1
4.45
2
4.4
0.005626
3
4.35
4.4
0.05
1
2
3
3.1
3.1
3.15
3.116666667
0.028867513
1
2
3
3.5
3.45
3.55
3.5
0.05
1
2
3
5.55
5.6
5.6
5.583333333
0.028867513
1
2
3
5.35
5.3
5.2
5.283333333
0.076376262
1
2
4.4
4.45
Average
Standard Deviation
3
Average
Standard Deviation
4
Average
Standard Deviation
5
Average
Standard Deviation
6
0.003985
0.004475
0.007139
0.006756
0.005690
3
4.5
4.45
0.05
1
2
3
3.8
3.85
3.8
3.816666667
0.028867513
1
2
3
4.75
4.7
4.7
4.716666667
0.028867513
1
2
3
3.2
3.25
3.25
3.233333333
0.028867513
1
2
3
3.65
3.7
3.65
3.666666667
0.028867513
1
2
3
4.05
4
4
4.016666667
0.028867513
1
2
3
2.95
2.9
2.9
2.916666667
0.028867513
1
2
3
2.7
2.65
2.7
2.683333333
0.028867513
Average
Standard Deviation
7
Average
Standard Deviation
8
Average
Standard Deviation
9
Average
Standard Deviation
10
Average
Standard Deviation
11
Average
Standard Deviation
12
Average
Standard Deviation
1 Grapefruit
Average
Standard Deviation
0.004880
0.006374
0.004370
0.004955
0.005428
0.003942
0.003626
2
1
2
3
2.35
2.4
2.35
2.366666667
0.028867513
1
2
3
2.4
2.45
2.4
2.416666667
0.028867513
1
2
3
2.3
2.35
2.3
2.316666667
0.028867513
Average
Standard Deviation
3
Average
Standard Deviation
4
Average
Standard Deviation
0.003198
0.003266
0.003131
Sample Orange/Grapefruit #
% Sucrose Solid Brix 20°C ±0.3
pH
Mass (grams)
Volume of Whole Orange (ml)
Density (g/ml)
Circumference Range (mm)
Volume of Juice (ml)
Vitamin C Content (mg/100ml)
Total Quantity of Vitamin C in Fruit (mg)
Sample Orange/Grapefruit #
% Sucrose Solid Brix 20°C ±0.3
pH
Mass (grams)
Volume of Whole Orange (ml)
Density (g/ml)
Circumference Range (mm)
Volume of Juice (ml)
Vitamin C Content (mg/100ml)
Total Quantity of Vitamin C in Fruit (mg)
Sample Orange/Grapefruit #
% Sucrose Solid Brix 20°C ±0.3
pH
Mass (grams)
Volume of Whole Orange (ml)
Density (g/ml)
Circumference Range (mm)
Volume of Juice (ml)
Vitamin C Content (mg/100ml)
Total Quantity of Vitamin C in Fruit (mg)
1 (Mentone) 2 (Mentone) 3 (Mentone) 4 (Yucaipa) 5 (Yucaipa) 6 (Yucaipa) 7 (Mentone)
14.26%
11.85%
11.55%
13.78%
14.14%
12.75%
13.66%
3.52
3.7
3.69
3.46
3.43
3.41
3.45
181.86
183.75
303.82
170.42
159.3
168.82
239.85
185
185
310
175
180
177
240
0.983
0.9932
0.9801
0.9738
0.885
0.9538
0.9994
22.95
22.85
27.85
22.75
22.45
23.3
25.4
100
96
130
70
72
75
117
56.26
39.85
44.75
71.39
67.56
56.9
48.8
56.26
38.26
58.18
49.97
48.64
42.68
57.1
8 (Organic)
9 (Sun Pac)
10 (Cali Val) 11 (Cali Val) 12 (Unkwn) 1 GF (Fresh) 2 GF (Older)
13.78%
11.73%
11.37%
11.61%
13.96%
11.12%
10.94%
3.6
3.72
3.69
3.76
3.94
3.24
3.26
202.27
247.18
223.95
164.81
195.83
405.78
344.92
205
0.9867
23.35
80
63.74
50.99
275
0.8988
26.3
90
43.7
39.33
225
0.9953
24.65
105
49.55
52.03
165
0.9988
22
85
54.28
46.14
218
0.8983
23.15
85
39.42
33.51
3 GF (Fresh)
430
0.9437
31.75
150
36.26
54.39
360
0.9581
29.75
154
31.98
49.25
4 GF (Fresh)
9.62%
3.35
437.77
455
0.9621
33.3
160
32.66
52.26
11.24%
3.27
387.79
400
0.9695
31.35
135
31.31
42.27
Predicted Ascorbic Acid = 4.650(D) – 39.38(pH) + 1.309(B) – 0.3055(C) – 0.2547(V) + 206.2
D = Density
B = Brix Value
C = Circumference
V = Total Juice Volume
Results/Discussion
After completion of my research and experimentation, I have seen many trends between the
physical properties of citrus fruits and the vitamin C content present. Before using partial least-squares
regression, the strongest correlations between the citrus fruits were between the pH and the Brix
values for both the oranges and the grapefruits. There was also a strong correlation between the Brix
values and the ascorbic acid content, as well as the pH compared to the ascorbic acid content.
However, the strongest correlation before applying the partial least-squares regression with regards to
ascorbic acid present in the oranges was with the Brix values. I noticed that the higher the sugar
content of the orange, the higher the concentration of vitamin C present. As for the relationship
between the pH and the vitamin C content for the oranges, the lower the pH; or the more acidic the
orange, the higher the vitamin C concentration. However, when I tested the pH of the grapefruits I
discovered the pH was much lower than that of the oranges, but the vitamin C concentration was also
lower. The average pH for an orange was 3.58, while the average pH of a grapefruit was 3.28. If the
same relationship between the pH and the vitamin C content applied to the grapefruit, then an
expectation of 83.92 mg/100 mL of ascorbic acid should have been present. However, the average
content of ascorbic acid in a grapefruit was only 33.05 mg/100 mL so implication of chemical
diversity is definitely in existence between the two fruits. From these experiments, I have
hypothesized that oranges may contain a higher vitamin C content at a higher acidity level, because
the acids may be preserving or helping to produce more vitamin C in the oranges when it is being
grown. Another reason behind this may be due to the fact that the higher the acidity level of the
orange, the lower the total volume of juice extracted. I believe this is occurring because when more
juice is present, there is occasionally more water inside the juice, which is contributing to the dilution
of the acids present.
When comparing the average vitamin C content in Valencia Oranges graphed against the pH, I
determined that the average vitamin C content should have been around 56.14 mg/100 mL. Based on
my data, the average vitamin C content was actually 54.25 mg/100 mL. Therefore, there is a strong
correlation between the pH and the vitamin C content in the oranges.
Through experimentation, I also noticed how oranges from the same location contained similar
properties in pH and Brix values. The grapefruits appeared to demonstrate the same characteristic, but
they were only harvested from one location so future research is required. In general, I have concluded
that the lower the pH, the higher the sugar content. Again, this may be due to the fact that water inside
of the oranges is contributing to less sugar content and a higher pH, so it makes sense that the lower
the total volume of juice extracted, the lower the pH and the higher the Brix value.
After using the statistical program, R, and creating a partial least-squares regression, a very
strong correlation was formed. Based on the coefficients generated by the PLSR and the ranges of the
variables, I discovered that the main contributors to the line were the pH, the total volume of juice,
and the Brix values. The PLSR appears to be very useful in predicting the vitamin C content in a
Valencia Orange, if the pH, Brix value, circumference, total volume of juice, and the density of the
orange are known, especially if the three contributors are known. When I created another PLSR based
on the three contributors, the correlation only decreased by 1%, so it is safe to say that you only really
need to know the pH, Brix value, and the total volume of juice in the orange, to predict a relatively
accurate vitamin C concentration inside of that orange.
CONCLUSION
After completing this research project, I noticed that there is room for improvement. With
additional data points and data modeling, a better fit equation might be found. Further research
is also necessary to provide more data points for grapefruits and to develop an analogous
model.
REFERENCES
Dr. J, Roger Bacon. Determination of vitamin C by an iodometric titration.
http://paws.wcu.edu/bacon/Vitamin%20C.pdf (accessed: Jul 7, 2011).
Nagy, Steven, "Vitamin C contents of citrus fruits and their products:a review", Journal of
Agricultural and Food Chemistry, 1980, 28(1), 8-18.
R Development Core Team (2008). R: A language and environment for statistical
computing. R Foundation for Statistical Computing,Vienna, Austria. ISBN 3-900051-07-0,
URL:http://www.R-project.org.
Structure Probe, Inc. Cargille refractive index liquids-conversion chart to brix valuesstandard group for calibration. http://www.2spi.com/catalog/ltmic/brix.html (accessed Jul 14, 2011).
ACKNOWLEDGEMENTS





The National Science Foundation, supporting the CSUSB PRISM Program, DMS-1035120
Dr. Kimberley R. Cousins, Department of Chemistry and Biochemistry, CSUSB
Dr. Rolland Trapp, Department of Mathematics, CSUSB, head of PRISM
California State University, San Bernardino, for their hospitality
Vannary Sann, Student Assistant for Dr. Cousins