Apple Oxida+on Purpose: One of the problems in making fruit salad is keeping the apples looking fresh. Many cooks use lemon juice to keep the apples from turning brown. Apples turn brown because of oxida+on. Apples Oxidize because of an enzyme known as polyphenoloxidaise. This enzyme is present in the apples flesh and is apples brown. Another way of saying apple oxidiza+on is enzyma+c browning. There are two ways of stopping the reac+on. One way is to cut off the key ingredient, which is Oxygen, or inhibit the enzyme. A substance can inhibit Polyphenoloxidaise with a ph level under 4.0. the purpose of this experiment is to see what concentra+on of lemon juice will inhibit the browning process. If lower concentra+ons of lemon juice can inhibit browning then money can be saved during the food prepara+on process by dilu+ng more expensive lemon juice with less expensive water.
Hypothesis: Because polyphenoloxidase is inhibited by a solu+on with a ph of less than 4.0, the dilu+on of lemon juice to a ph of 3.5 should s+ll inhibit browning of apples. The maximum dilu+on of lemon juice to a ph of 3.5 is calculated as follows: To find the dilu-on amount for 100ml of lemon juice, take the ini-al concentra-on of the acid in lemon juice and then calculate the needed dilu-on amount to make the ph=3.5 ph=concentra-on of the acid divided by total concentra-on of the solu-on ph=- log[h+]/[sample] ph=2=- log[h+]/[sample] : measured ph for lemon juice 2=- log[h+]/100ml 10-2 =[H+]/100mL 100mL* 10-2 =[H+] 1mL=[H+] : star-ng sample of lemon juice of 100ml. :acid content in lemon juice Dilu-ng to a ph of 3.5 means the sample must be diluted with water. The next steps solve for how much water to add to reach a ph of 3.5 assuming water has negligible acid content. ph=3.5=- log[h+]/[sample] 3.5=- log[1ml]/[100ml+x] 10-3.5 =[1mL]/[100mL+x] [100mL+x]=[1mL]/10-3.5 [100mL+x]=3162ml [x]=3062ml water to be added to get a ph of 3.5 Now solving for the percent of lemon juice (LJ) ater dilu-on with water. 100ml LJ/(100ml LJ+3062ml water)*100% = % Lemon Juice 100mL/3162mL*100%=3.2% lemon juice ater dilu-on by water Since the percent of lemon juice concentra+on to keep the dilu+on s ph above 3.5 is 3.2%, then the apple should not brown if the percent of lemon juice is above 3.16% in the dilu+on.
Methods Create Sample solu+ons 100% Lemon Juice: Pour 50 ml of lemon juice into a container 50% Lemon Juice: Pour 25ml of lemon juice and 25ml of water 25% Lemon Juice: Pour 12.5ml of lemon juice and 37.5ml of water 12.5% Lemon Juice: Pour 6.25ml of lemon juice and 43.75ml of water 6.25% Lemon Juice: Pour 3.125ml of lemon juice and 46.875ml of water 100% Water: Pour 25ml of water into a container 100% Orange Juice: Pour 25ml of orange juice into a container Control: No solu-on applied to apple slice Apple Prepara+on Cut 8 slices off of an apple For the second cut on the inside of the apple face the core side down Use a pipe^e to pour 2ml of the substance on seven of the apples and leave a control Repeat steps 8 and 9 five -mes Color Assay Data Collec+on Procedure Take a picture at 0 min of all the apples being out Take a picture at 15 min Take a picture at 1hr Take a picture at 2hr
Chemical Assay Data Collec+on Procedure Create a template 1.5 in. By 1.5 in. to keep the surface area the same between condi-ons Take a pre- test measurement of the CO2 and O2 Wait 4 min. Cut a slice off of the apple (this step and the following three steps take about one min. Use a template to cut the apple slice to a uniform size Use a pipe^e and pour 1ml of a solu-on on and cover the top Set the apple slice with solu-on applied into the bio chamber put the lid on the bio chamber, the lid contains the O2 and CO2 probe Record O2 and CO2 data at - 5 min, 0 min, 15 min, 30 min, 45 min, 60 min, 75 min, 90 min, 105 min, and 120 min. Wash out bio chamber
Figure1: Chemical Assay Carbon Dioxide and Oxygen Concentra-on Measurement Apparatus CO2 Sensor O2 Sensor Temperature & Humidity Sensor Sensor Display
Color Assay Tool Development Create Sample Brown Solu+ons 100% Brown: 50 ml of coffee 0 ml of milk 90% Brown: 48 ml of coffee 5 ml of milk 80% Brown: 41 ml of coffee 9 ml of milk 70% Brown: 35 ml of coffee 15 ml of milk 60% Brown: 30 ml of coffee 22 ml of milk 50% Brown: 25 ml of coffee 26 ml of milk 30% Brown: 15 ml of coffee 35 ml of milk 20% Brown: 10 ml of coffee 40 ml of milk 10% Brown: 5 ml of coffee 45 ml of milk 5% Brown: 5 ml of coffee 95 ml of milk 0% Brown: 0 ml of coffee 50 ml of milk Take pictures of brown solu-ons Use Gimp sotware s ability to break color down into red green and blue to determine the percentage of blue in each brown sample Plot %blue vs brown samples Use excel sotware s ability to find the slope of a line to determine the slope fit Es-mate y intercept point and then calculate variance for each sample and then sum the variances Vary the y intercept un-l the minimum variance is established, this is then the y intercept The resul-ng equa-on is blue=slope*brown+ y intercept Rearanging this equa-on can now be used as a color assay for brown Brwn = (%blue- y intercept)/slope Brown=(%blue- 94)/-.825
% Blue (Concentrate) 120.0 100.0 80.0 60.0 Blue as an Indicator of Brown: Brown=(%Blue- 94)/-.852 SAMPLE MIXTURE MEASURED CALCULATED Coffee (ml) d) Data Table Variance= Brown = (Bluebrown)^2 SLOPE(Blue) + 94 Milk Sample Blue Background (ml) (%) Blue (%) Brown (%) % Blue 50 0 7 71 100.0 9.9 8.8 1.0 48 5 12 67 90.6 17.9 16.9 1.1 41 9 18 70 82.0 25.7 24.2 2.4 35 15 24 67 70.0 35.8 34.4 2.0 30 22 36 73 57.7 49.3 44.9 19.8 25 26 30 63 49.0 47.6 52.3 21.5 15 35 38 62 30.0 61.3 68.5 51.3 10 40 41 58 20.0 70.7 77.0 39.4 5 45 46 58 10.0 79.3 85.5 38.1 5 95 53 56 5.0 94.6 89.7 24.0 0 100 58 55 0.0 105.5 94.0 131.2 331.8544 36 40.0 20.0 a) Brown Sample Solu-on Pictures 0.0 0.0 20.0 40.0 60.0 80.0 100.0 120.0 Brown (Percent of Concentra+on of Coffee in Coffee- Milk Solu+on) Figure 2: Calcula+ng Color Assay Metric: a) pictures of the brown samples, b) resul-ng blue color percentage from Gimp sotware, c) slope fit from Excel sotware Slope func-on, d) data table.
Results The results are graphically depicted in figures 3-7. Figure 3shows that in the first 15 minutes that the amount of Co2 spikes and that is con-nues to rise over -me but never like the first 15 minutes. Figure 4 shows the average and standard devia-on of the solu-ons for their percent of brown. 100% Lemon juice s average was the lowest and there was li^le varia-on in the results. Water, 50% lemon juice, and orange juice worked be^er than the control but their results varied more than the 100% lemon juice s did. There is a -tra-on curve that is easy to detect in figure 4 is in the different concentra-ons of lemon juice. There is li^le reac-on in the 100% lemon juice and around 50% lemon juice is around where the equivalence point was. The slope of the equivalence point is almost undefined. At 25% lemon juice is where it start to level off and the rate of oxida-on from there on is close together. Figure 5 is a picture of the apple slices and it is easy to tell that the 100% lemon juice was the lightest and looked fresher than the rest. Figure 6 shows the same thing as figure 3. the amount of CO2 produced is greatest in the first 15 minutes. There was an anomaly in figure 6 and it was that water was the best where as in the rest of my tests it did not work very well in slowing down the rate of oxida-on. The more CO2 is produced the more the apple slice is oxidizing. Figure 7 measured the amount of O2 for the same samples and the same -me as in figure 6. The graph showed that the amount of O2 over -me went down but the results varied greatly. The amount of oxygen would go down drama-cally in the first 15 minutes but then in some of the cases the amount of oxygen would go back to what it was. There were also a couple of anomalies. Water did the best where Lemon juice did the worst. Lemon juice has always don well, this is not normal. The more amount of O2 is present the less the apple slice is oxidizing. My data indicates that most cost effec-ve way to slow down the rate of oxida-on is 50% lemon juice. The reason I did not choose 100% is because in figure 4 and in most of the other figures 50% lemon juice did not work the best but it did work and it was be^er than the control.
60 Figure 3: Graph of Percent Apple Browning vs Time and Associated Data Table 50 Percent Brown From Color Assay Metric 40 30 20 100% LS 50% LS 25% LS 12.5% LS 6.25% LS Orange S Water S Control S 10 0 0 50 100 150 200 250 Time (minutes)
Figure 4: Graph of Percent Apple Brown vs Solu+on Type. Blue Bar Represents Average Browning, Air Bars Represent +/- Standard Devia+on. 55 50 Brown (%) 45 40 35 30 25 20 100% Lemon 50% Lemon 25% Lemon 12.5% Lemon 6.25% Lemon Orange Water Control Solu+on Type Figure 5: Color Assay Picture. The solu-on applied to apples slices correspond with the labels from figure 4.
Figure 6: Graph of Change in CO2 vs Time and Associated Data Table 900 800 700 Change in CO2 Concentra+on (ppm) 600 500 400 300 CO2 Lemon1 CO2 Control 1 200 CO2 Orange 1 CO2 Water 1 100 0 0 20 40 60 80 100 120 140 Time (minutes)
Figure 7: Graph of Change in O2 vs Time and Associated Data Table 2000 1000 0 0 20 40 60 80 100 120 140 Change in O2 Concentra+on (ppm) - 1000-2000 - 3000 O2 Lemon1 O2 Control 1-4000 O2 Orange 1 O2 Water 1-5000 - 6000 Time (minutes)
Discussion: In the hypothesis it was stated that if the percentage of lemon juice to inhibit apple browning or oxida-on was above 3.16% lemon juice concentra-on. What the results showed is that browning started to occur somewhere around 50% lemon juice concentra-on. In the first 15 minutes the graph shows that the amount of brown in the apples spiked. The amount of brown went up slowly ater the 15 minute point. This means that apple oxida-on happens the quickest during the first 15 minutes of it being cut. It was observed that ini-al oxida-on happened before the solu-on was able to be applied to the apples. If the apple was cut in a vacuum and the solu-on applied to the apple, then there would be no oxida-on before the solu-on was applied. This would take away one of the variables that could have accelerated browning of apples. To measure the ph of the solu-ons ph strips were used. The numeric interpreta-on of the strips may not have been accurate. The likely error could have been as much as 1. If the ph of the lemon juice was actually 3, then the calcula-on for what percent of lemon juice would stop the oxida-on on an apple would be a higher percentage.
The new calcula+on for the maximum dilu+on of lemon juice to a ph of 3.5 is calculated as follows similarly to the hypothesis sec+on: ph=3=- log[h+]/[sample] : measured ph for lemon juice 3=- log[h+]/100ml : star-ng sample of lemon juice of 100ml. 10-3 =[H+]/100mL 100mL* 10-3 =[H+] 0.1mL=[H+] :acid content in lemon juice Dilu-ng to a ph of 3.5 means the sample must be diluted with water. The next steps solve for how much water to add to reach a ph of 3.5 assuming water has negligible acid content. ph=3.5=- log[h+]/[sample] 3.5=- log[.1ml]/[100ml+x] 10-3.5 =[.1mL]/[100mL+x] [100mL+x]=[.1mL]/10-3.5 [100mL+x]=316.2ml [x]=216.2ml water to be added to get a ph of 3.5 Now solving for the percent of lemon juice (LJ) ater dilu-on with water. 100ml LJ/(100ml LJ+216.2ml water)*100% = % Lemon Juice 100mL/316mL*100%=31.6% lemon juice ater dilu-on by water This calcula+on indicates that an apple should not brown if the percent of lemon juice is above 31.6%. While this matches the data the ph of lemons is typically has a ph of 2.3 according to phoflemonjuice.com
When cuong into an apple, the flesh releases liquid apple juice. When the lemon juice solu-on was put on the apple further dilu-on of the lemon juice occurred because the liquid apple juice and other apple materials were present on the apple flesh. This ma^ers because the percent of lemon juice on the apple has gone down and more should be applied to meet the percentage of lemon juice concentra-on otherwise the amount of oxida-on would have increased.
Learning Objec+ves Experimenta+on design: Purpose: start with broad introduc-on and narrow to specific experiment Hypothesis: predict results by applying science and mathema-c principals Methods: describe standard and custom developed methods Results: Create graphs dependent vs independent variables Creare graphs discribing experimental varia-on using error bars Discussion: describe accuracy of results vs hypothesis and likely sources of varia-on ph: science, applica-on and calcula-on of ph Titra+on: understanding the chemical ac-vity chemical compounds & enzymes and their related ac-vity S shaped curves from no ac-vity to maximum ac-vity. Custom Assay Development: Gimp to break down image color into RGB brown samples to create brown color con-muum slope fit and variance to create custom algorithm for brown assay metric Bar graphing technique for showing average and error bars Opera+on of electronic data acquisi+on system for collec-ng O2 & CO2 gas concentra-ons