Correlations Between Citrus Fruit Properties and Ascorbic Acid Content

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 KIO 3, 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 Abbe- Refractometer 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 19.8 2 19.75 3 19.75 Average 19.76666667 Concentration of Standard (g AA/ ml Iodine) 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 Average 18.85 Standard Deviation 0.05 Concentration of Standard (g AA/ml Iodine) 0.001351 Vitamin C Present Sample Trials Vol. of Iodine Titrant (Per 10ml Juice) Vit C (g/10 ml) Orange: 1 1 4.45 2 4.4 0.005626 3 4.35 Average 4.4 Standard Deviation 0.05 2 1 3.1 2 3.1 0.003985 3 3.15 Average 3.116666667 3 1 3.5 2 3.45 0.004475 3 3.55 Average 3.5 Standard Deviation 0.05 4 1 5.55 2 5.6 0.007139 3 5.6 Average 5.583333333 5 1 5.35 2 5.3 0.006756 3 5.2 Average 5.283333333 Standard Deviation 0.076376262 6 1 4.4 2 4.45 0.005690

3 4.5 Average 4.45 Standard Deviation 0.05 7 1 3.8 2 3.85 0.004880 3 3.8 Average 3.816666667 8 1 4.75 2 4.7 0.006374 3 4.7 Average 4.716666667 9 1 3.2 2 3.25 0.004370 3 3.25 Average 3.233333333 10 1 3.65 2 3.7 0.004955 3 3.65 Average 3.666666667 11 1 4.05 2 4 0.005428 3 4 Average 4.016666667 12 1 2.95 2 2.9 0.003942 3 2.9 Average 2.916666667 1 Grapefruit 1 2.7 2 2.65 0.003626 3 2.7 Average 2.683333333

2 1 2.35 2 2.4 0.003198 3 2.35 Average 2.366666667 3 1 2.4 2 2.45 0.003266 3 2.4 Average 2.416666667 4 1 2.3 2 2.35 0.003131 3 2.3 Average 2.316666667

Sample Orange/Grapefruit # 1 (Mentone) 2 (Mentone) 3 (Mentone) 4 (Yucaipa) 5 (Yucaipa) 6 (Yucaipa) 7 (Mentone) % Sucrose Solid Brix 20 C ±0.3 14.26% 11.85% 11.55% 13.78% 14.14% 12.75% 13.66% ph 3.52 3.7 3.69 3.46 3.43 3.41 3.45 Mass (grams) 181.86 183.75 303.82 170.42 159.3 168.82 239.85 Volume of Whole Orange (ml) 185 185 310 175 180 177 240 Density (g/ml) 0.983 0.9932 0.9801 0.9738 0.885 0.9538 0.9994 Circumference Range (mm) 22.95 22.85 27.85 22.75 22.45 23.3 25.4 Volume of Juice (ml) 100 96 130 70 72 75 117 Vitamin C Content (mg/100ml) 56.26 39.85 44.75 71.39 67.56 56.9 48.8 Total Quantity of Vitamin C in Fruit (mg) 56.26 38.26 58.18 49.97 48.64 42.68 57.1 Sample Orange/Grapefruit # 8 (Organic) 9 (Sun Pac) 10 (Cali Val) 11 (Cali Val) 12 (Unkwn) 1 GF (Fresh) 2 GF (Older) % Sucrose Solid Brix 20 C ±0.3 13.78% 11.73% 11.37% 11.61% 13.96% 11.12% 10.94% ph 3.6 3.72 3.69 3.76 3.94 3.24 3.26 Mass (grams) 202.27 247.18 223.95 164.81 195.83 405.78 344.92 Volume of Whole Orange (ml) 205 275 225 165 218 430 360 Density (g/ml) 0.9867 0.8988 0.9953 0.9988 0.8983 0.9437 0.9581 Circumference Range (mm) 23.35 26.3 24.65 22 23.15 31.75 29.75 Volume of Juice (ml) 80 90 105 85 85 150 154 Vitamin C Content (mg/100ml) 63.74 43.7 49.55 54.28 39.42 36.26 31.98 Total Quantity of Vitamin C in Fruit (mg) 50.99 39.33 52.03 46.14 33.51 54.39 49.25 Sample Orange/Grapefruit # 3 GF (Fresh) 4 GF (Fresh) % Sucrose Solid Brix 20 C ±0.3 9.62% 11.24% ph 3.35 3.27 Mass (grams) 437.77 387.79 Volume of Whole Orange (ml) 455 400 Density (g/ml) 0.9621 0.9695 Circumference Range (mm) 33.3 31.35 Volume of Juice (ml) 160 135 Vitamin C Content (mg/100ml) 32.66 31.31 Total Quantity of Vitamin C in Fruit (mg) 52.26 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