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International Baccalaureate Diploma Program Sri KDU Smart School Extended Essay -Chemistry- Spectrophotemetric determination of iron content in broccoli plants Brassica oleracea Which part of the broccoli plant contains the highest iron content and how different incubating temperature affects its iron content? 3990 Words Only By Choo Ken Loon 002206-004 Abstract This extended essay is on spectophotometric determination of iron found in different parts of the broccoli, Brassica oleracea and the effects of incubating temperature on the iron content. Spectophotometry quantification was adopted. Iron(II) was reacted with orthophenanthroline solution to produce orange-red colour complex exhibiting a maximum absorption peak, λmax at 510nm. Beer-Lambert’s law is applied where the absorbance reading is directly proportional to the concentration of the sample. A standard calibration curve for iron(II) solution was plotted which shows a significant (P<0.05) and good correlation (R2 = 0.9929) between concentration and absorbance. Samples from different parts of the broccoli (buds, stems and base) was obtained, heated to ash and dissolved in hydrochloric acid(4.0M) to form the required solution. Broccoli bud samples were incubated in water of different temperatures (24.0°C, 60.0°C, 80.0°C and 100.0°C) for the second part of the investigation. Statistical results show a significantly higher (P<0.05) iron content at the buds compared to the stems and the base of the broccoli. The amount of iron in the buds and the stems are 2.90mg dm-3g-1 to 0.30mg dm-3g-1 respectively, indicating 90% higher iron content in the buds. Investigation on different incubating temperature shows a negative correlation between incubating temperature and iron content. Statistical results showed a significant decrease in iron content observed only when the incubating temperature is at 100°C. Iron content for control sample(24.0°C), 8.30mg dm-3g-1 decreases to 2.65mg dm-3g-1 at 100.0°C, implying a significant 61% drop. Incubating temperatures of 60°C to 80°C result to a range of decrease of iron content between 1.8% and 25%. Statistical tests were carried out for all results to support the significant difference between the samples (P<0.05). The conclusion was that the iron content is highest at the buds of the broccoli and increasing incubating temperature decreases iron content. (296 words only) 2 Acknowledgement I would like to thank: Mr Lawrence Kok for his unending support and guidance My parents for supporting me and enduring my needs My friends for everything they have done And All the other people who helped in this investigation 3 Table of Contents Abstract ............................................................................................................................................................................2 Acknowledgement ........................................................................................................................................................... 3 1.0 Introduction ..................................................................................................................................................... 5 1.1 Rationale of study ......................................................................................................................................... 5 2.0 Hypotheses ....................................................................................................................................................... 7 2.1 Investigation on the different parts of the broccoli plant .............................................................................. 7 2.2 Investigation on the different incubation temperature................................................................................... 9 3.0 Methodology................................................................................................................................................... 10 4.0 Plotting a standard calibration curve for Iron(II) ...................................................................................... 12 4.1 Requirements for the plotting of the standard calibration curve for Iron(II) ............................................... 12 4.2 Procedure to prepare iron(II) phenanthroline complex and plotting the calibration curve .......................... 13 4.3 Data Collection ........................................................................................................................................... 14 4.4 Data Processing........................................................................................................................................... 15 5.0 Methodology for iron extraction from different parts of the broccoli plants ........................................... 16 5.1 Preparing samples from different parts of the broccoli plant ...................................................................... 16 5.2 Reducing iron(III) and measuring its absorbance ....................................................................................... 17 5.3 Data Collection ........................................................................................................................................... 18 5.4 Data Processing........................................................................................................................................... 20 6.0 Methodology adopted to investigate the effects of different incubation temperature on the amount of iron in broccoli buds ..................................................................................................................................... 23 6.1 Preparing samples incubated in distilled water of different temperatures ................................................... 23 6.2 Reducing iron(III) and measuring absorbance ............................................................................................ 24 6.3 Data Collection ........................................................................................................................................... 24 6.4 Data Processing........................................................................................................................................... 27 7.0 Data Presentation .......................................................................................................................................... 30 8.0 Data Processing: ANOVA and Tukey’s HSD Test ..................................................................................... 32 9.0 Data Analysis ................................................................................................................................................. 35 9.1 Parts of the broccoli plant ........................................................................................................................... 35 9.2 Incubating temperature ............................................................................................................................... 37 10.0 Evaluation ...................................................................................................................................................... 39 10.1 Uncertainties and Limitations ..................................................................................................................... 39 10.2 Ways of Improvement................................................................................................................................. 40 10.3 Further Investigations ................................................................................................................................. 41 11.0 Conclusion ...................................................................................................................................................... 42 12.0 Reference ........................................................................................................................................................ 43 13.0 Appendix.........................................................................................................................................................45 4 1.0 Introduction 1.1 Rationale of Study Iron, one of the most abundant metals on Earth, is essential as it maintains good health [1] including growth, reproduction and the human immune system. Iron is vital as a component to form haemoglobin for oxygen transportation. Iron deficiency is the number one nutritional disorder [2], it causes fatigue and anaemia where red blood cells with low concentration of haemoglobin fail to supply adequate amount of oxygen to the body tissues. Thus, it was found worthy to study iron because it is directly related to our daily diet and health. Questions were devised on how to maximize the iron intake when consuming particular vegetable where certain variables were manipulated. The iron content in different parts of a specific vegetable was initially investigated. Broccoli, Brassica oleracea was chosen due to high iron content (0.73mg/100g)[4] and a source of many useful nutrition including high amount of calcium, beta-carotene, vitamin C and fibre. This is to raise awareness regarding the proper part of the plant to be consumed which gives us more iron. Further investigation was planned on the effects on iron content due to the cooking procedure. It was proposed that the temperature of water used to incubate vegetable would affect the nutrient content in the vegetable significantly. It is important to create awareness on how simple preparation of vegetable would affect the nutrients found in the particular vegetable as very often vegetables are overcooked and this affects the valuable nutrients found in it. 5 The research is planned to be carried out on distinct parts of the broccoli plant Brassica oleracea, namely the buds, stems and the base. The preparation method by soaking broccoli in water was selected because it is a common and simple method of preparation. Hence, the precise research question is: “Which part of the broccoli plant contains the highest amount of iron and how different incubating temperature affects its iron content?” Figure 1: The different parts of the broccoli plant the buds, the stems and the base. 6 2.0 Hypotheses 2.1 Investigation on the different parts of the broccoli plant [5] Chlorophyll found in the chloroplast is responsible for light absorption during photosynthesis. Ferredoxin1, cytochromes b6f2 and other electron-carrier proteins are involved in the photosynthetic pathway while cytochrome c3, Fe –S clusters and other electron-carrier proteins are present in mitochondrial electron-transport chain all which function as electron carriers. All the listed protein complexes above have iron as part of its component. It is hypothesized that broccoli buds contains the highest amount of iron because of higher density of iron-containing electron-carrier proteins: Photosynthetic pathway 1. Broccoli buds are greener due to higher density of Chlorophyll a4 compared to the stems and base since it is needed for photosynthesis. 2. More electrons are excited due to higher amount of energy absorbed by chlorophyll. 3. More ferrodexin, cytochrome b6f proteins and other electron-carrier proteins are required for electron transportation. Mitochondrial electron-transport chain 1. Mitochondria are more abundant in broccoli buds compared to the stems and base of the broccoli plant because the stems and base consist of mostly xylem and phloem which functions in food and water transport. 1 Acidic, low molecular weight, soluble iron-sulphur proteins 2 Monomeric unit of the complex that contains six bound prosthetic groups, three hemes (f, two hemes b, bp and bn), one [2Fe-2S] cluster, and one molecule each of chlorophyll-a and carotene 3 Able to transition between ferrous and ferric states within the cell, therefore functioning efficiently. 4 Magnesium-containing substituted tetrapyrroles. 7 2. More cytochrome c, Fe –S clusters and other electron-carrier proteins are required to function for the transportation of electrons for the complex processes occurring in the mitochondria which involves electron transfer for energy production. Figure 2: Electron-carrier proteins in the form of ferrodexin and cytochrome b6f located in the chloroplast. Figure 3: Mitochondrial electron-transport chain where cytochrome c and Fe –S clusters are located. 8 2.2 Investigation on the different incubating temperature It is hypothesized that iron content in the broccoli plant decreases as the incubating temperature increases because at high temperature: 1. Cell walls break down easily. 2. Increased rate of denaturation of the protein membrane present at the cell membrane. 3. Increased kinetic energy5 increases probability of the electron-carrier proteins diffusing out of the cell membrane. 4. Proteins in the plant might denature and react with each other forming unknown products of altered physical properties such as the increased solubility and ability to diffuse through the cell membrane, resulting to iron leaching out of the plant. 5. The number of molecules having higher energy increases, increasing rate of reaction between molecules present in the plant according to the Maxwell–Boltzmann distribution, thus iron-containing proteins reacts at a higher rate, resulting to a greater loss of iron from the plant through leaching. Fraction of molecules with a given speed Figure 4: Maxwell-Boltzmann distribution on the distribution of molecular speed at different temperature. 5 Average kinetic energy, EK is directly proportional to the absolute temperature. Emean = 3⁄2kBT. 9 3.0 Methodology Since the iron content in broccoli is in small amount, a sensitive and less complicated method was used – Spectrophotometry [6]. The theory involved relates concentration of the solution containing iron to its absorbance of light at a specific wavelength. A visible spectrophotometer which passes a light beam with wavelength complement to the colour of the sample was use to measure the amount of light each iron(II) sample of different concentrations would absorb. For this investigation, the product was orange-red in colour, thus a light beam of specific wavelength which exhibits an absorbance peak at 510nm, λmax was used. Beer’s Law[7] was applied, it can be expressed as: A = εlc6 The same type of cuvette was used in all the measurements and the molar absorptivity is constant for all the samples, therefore both ε and l are constants. Hence, this indicates that the absorbance of a sample is directly proportional to its concentration, A c and the relationship between variables A and c is linear. In this research, iron solution is reacted with orthophenanthroline (ο-phen) (figure 7) to form an orange-red iron(II) orthophenanthroline complex (figure 8) at optimum pH of 3.5 where the complex would be stable for at least 20 hours at pH 2 – 9 [8]. The chemical equation is given as: Fe2+ + 3Phen ↔ Fe(Phen)3 2+ 6 A is the absorbance of the sample. ‘ε’ is the molar absorptivity, which is a constant. ‘l’ is the thickness of the cuvette holding the sample. ‘c’ is the concentration of the absorbing species. 10 The stoichiometric ratio is 1: 3. Figure 5: The structure of o-phenanthroline. Figure 6: The structure of iron(II) phenanthroline complex and the solution. Figure 7: Visible Spectrophotometer 11 4.0 Plotting a standard calibration curve for Iron(II) 4.1 Requirements for the plotting of the standard calibration curve for Iron(II) Iron(II) solution with known concentration were prepared. The solutions were reacted with o- phennanthroline to form an iron complex and the absorbance of each complex measured. The required solutions7 are: 1. Iron(II) standard solutions8 of concentrations 25.0x10-5M, 10.0x10-5M, 7.50x10-5M, 6.00x10-5M, 5.00x10-5M and 2.50x10-5M. 2. 10% hydroxylammonium chloride9, NH3OHCl solution. 3. 5% of trisodium citrate10, Na3C6H5O7 solution. 4. 0.01M Orthophenanthroline solution of 0.01M. 7 See appendix 1 for procedures to prepare the required solutions. 8 See appendix 2 for dilution of iron(II) standards 9 Excess reducing agent. 10 Buffer reagent. 12 4.2 Procedure to prepare iron(II) phenanthroline complex and plotting the calibration curve 1. 1.0cm3 of 25.0x10-5M iron(II) standard was transferred into a 100.0cm3 container using a micropipette. 2. 0.5cm3 of 5% trisodium citrate solution was added followed by 0.5cm3 of 10% hydroxylammonium chloride solution and finally 1.0cm3 of 0.01M phenanthroline solution. 3. The mixture was left for 60 minutes for the orange-red complex to form completely. 4. 1.0cm3 of the solution was transferred into a cuvette. 5. The instrument was calibrated using a blank solution11 with wavelength setting at 510nm. 6. The cuvette was inserted into the cuvette holder inside the visible spectrophotometer. 7. The absorbance reading was recorded at 510nm, λmax12, again after 90 and 120 minutes. 8. Steps 1-7 were repeated using iron(II) standards of 10.0x10-5M, 7.50x10-5M, 6.00x10-5M, 5.00x10-5M and 2.50x10-5M. Figure 8: Iron(II) phenanthroline complex at different concentration. 11 A solution containing all reagents except iron. 12 A wavelength that exhibits maximum absorption peak. 13 4.3 Data Collection Absorbance reading, A after Mean Absorbance(a) Concentration, c / ± (95%) Confidence mol dm-3 60 minutes 90 minutes 120 minutes Interval13 25.0x10-5 0.801 0.761 0.721 0.761 ± 0.100 10.0x10-5 0.337 0.373 0.302 0.337 ± 0.090 7.50x10-5 0.228 0.233 0.232 0.231 ± 0.007 6.00x10-5 0.189 0.206 0.196 0.197 ± 0.020 5.00x10-5 0.059 0.202 0.107 0.123 ± 0.600 2.50x10-5 0.118 0.062 0.089 0.090 ± 0.070 Table 1: The concentration of iron(II) standards, the corresponding absorbance reading after 60, 90 and 120 minutes respectively and the mean absorbance. (a) Mean absorbance ± (95%) Confidence Interval obtained at 60, 90 and 120 minutes. Standard deviation for standard iron(II) concentrations were not recorded as uncertainty due to the apparatus used for the preparation of the standards is assumed to be insignificant. Due to the instability of the instrument, the absorbance readings fluctuate throughout the absorbance measuring process. Mean absorbance was calculated using the absorbance measured at intervals of 60, 90 and 120 minutes and the confidence interval was calculated. 13 See appendix 3 for further calculations on (95%) confidence interval. 14 4.4 Data Processing Graph of Absorbance, A against Concentration, c / x10-4 mol dm-3 1.000 y = 0.3045x + 0.0055 R² = 0.9929 0.800 (P<0.05) Absorbance, A 0.600 0.400 (a) 0.200 0.000 0 0.5 1 1.5 2 2.5 3 -0.200 Concentration of iron, c / x10-4 mol dm-3 Graph 1: The calibration curve for iron(II) plotted from the collected data. (a) Error bars denote (95%) confidence interval. (b) Significant correlation between concentration and absorbance (R2 = 0.9976, α = 0.05, P<0.05)14 14 See appendix 4 for regression analysis. 15 5.0 Methodology for iron extraction from different parts of the broccoli plants The samples undergo dry ashing so that iron would be oxidized by air. Ash was dissolved in (4.0M) hydrochloric acid15 to obtain an aqueous solution for absorbance measurement. 5.1 Preparing samples from different parts of the broccoli plant 1. Random samples from the buds, stems and base were collected from a broccoli plant (Brassica oleracea). Triplicate samples were obtained from different broccoli plants. 2. The samples were heated for 30 minutes in an oven on a heating tray to obtain dry mass16. 3. 4.000g of samples from the buds, stems and base respectively was weighed using and electronic balance (±0.001g) and placed into a crucible. Triplicate samples were prepared. 4. The crucibles without the lids on were heated directly in a crucible using a Bunsen burner for six hours. 5. 1.0cm3 of concentrated hydrochloric acid (4.0M) was added to each of the crucible to dissolve the ash to form aqueous iron(III) solution. Figure 9: Samples from the broccoli buds, stems and base on a heating tray and during dry ashing. 15 See appendix 5 for pictures of the ash dissolved in HCl acid. 16 Mass of the dried matter which does not contains water. 16 5.2 Reducing iron(III) and measuring its absorbance 1. 1.0cm3 of solution together with ash was transferred into a microcentrifuge tube using a micropipette (100 – 1000)µl. The centrifuge machine is used to precipitate unwanted ash in the microcentrifuge tube. 2. 1.0cm3 of solution is transferred from the microcentrifuge tube into a 100.0cm3 container. 3. 0.5cm3 of 5% trisodium citrate solution was added followed by 0.5cm3 of 10% hydroxylammonium chloride solution and finally 1.0cm3 of 0.01M phenanthroline solution. 4. Absorbance of the samples was measured at time intervals 60, 90, 120 minutes. 17 5.3 Data Collection: Random Mean Absorbance reading, A after Mean absorbance(a) ± Part of the plant samples absorbance for (95%) Confidence (triplicates) each sample Interval 60 minutes 90 minutes 120 minutes 1 0.596 0.669 0.621 0.629 0.639±0.100 Buds 2 0.602 0.730 0.616 0.649 3(b) - - - - 1 0.077 0.152 0.033 0.087 Stems 2 0.060 0.089 0.064 0.071 0.079±0.100 3(b) - - - - 1 0.054 0.118 0.012 0.061 Base 2 0.089 0.055 0.075 0.073 0.070±0.020 3 0.014 0.145 0.070 0.076 Table 2: Parts of the plant, random samples (n=3), the absorbance reading after 60, 90 and 120 minutes respectively and the mean absorbance with (95%) confidence interval for triplicate samples. (a) Mean absorbance ± (95%) Confidence Interval obtained for the random triplicate samples. (b) / - Results were not included into the mean absorbance due to inconsistencies and irregularities. A 90% confidence interval Q test (rejection test) is performed to determine the outliners in the data collected.17 17 See appendix 7 for further calculations on Q test. 18 Qualitative Observations Some brown-black coloured substance18 was observed sticking on the side of the inner wall of the crucible after heating. The black substance was scraped off using a sharp pointed wooden splinter and was dissolved in hydrochloric acid (4.0M) together with the ash. The intensity of the orange-red coloured complex decreases in the sequence of buds, stems and base. 18 See Appendix 5 for picture of the brown-black substance sticking on the wall. 19 5.4 Data Processing With reference to the standard calibration curve, the concentration of iron(II) in the different part of the broccoli plant was determined. Amount of Mean Absorbance(a) Parts Of The Concentration of Concentration of iron(II) per ± (95%) Confidence Broccoli iron(II) ± SD19, c / iron(II) ± SD, c / gram of sample Interval Plant x10-4 mol dm-3 mg dm-3 ± SD, c / (n = 3) mg dm-3 g-1 Buds 0.639±0.100 2.08±0.78 11.61±0.44 2.90±0.11 Stems 0.079±0.100 0.241±0.068 1.35±0.38 0.34±0.09 0.212±0.061 Base 0.070±0.020 1.18±0.34 0.30±0.09 Table 3: Parts of the broccoli plant, mean absorbance with (95%) confidence interval and the amount of iron(II) per gram of sample. (a) Mean absorbance ± (95%) Confidence Interval obtained for the random triplicate samples. SD = Standard Deviation 19 See Appendix 8 for calculations for the standard deviation of the concentration of iron(II). 20 Example calculation on the amount of iron(II) found in broccoli buds From the standard calibration curve of iron(II), the regression equation relating absorbance to concentration is given as A = 0.3045c + 0.0055 (refer to page 16). Since the graph is plotted as absorbance, A against concentration, c x10-4, the final value of c is multiplied by 10-4. The mean absorbance for samples from the buds is 0.639. ����−0.0055 Therefore: c =( ) x 10-4 0.3045 0.639−0.0055 =( ) x 10-4 = 2.08x10-4M 0.3045 The value in 2.08x10-4mol dm-3 is converted to units of mg dm-3 by multiplying with the relative atomic mass of iron, 55.85g mol-1. Therefore: c = 2.08x10-4M x 55.85g mol-1 = 11.61mg dm-3 Finally, calculations were made to determine the amount of iron per gram sample. 11.61 Therefore: c = = 2.90mg dm-3g-1 4 Similar calculations were performed for different parts of the plants. 21 Example calculation on the standard deviation of amount of iron(II) found in broccoli buds Calculations for standard deviation were performed using Windows Excel 2007. The formula20 used is as shown below: sr 1 1 (�������� − ���� )2 SX = ���� { ���� + ���� +���� 2 (���� ���� − ���� )2 }1/2 0.02305 1 1 (0.639− 0.290)2 = 3044 .14 { 2 + 6 +(3044.14)2 (3.26x10 −8 )}1/2 = 7.83x10-6mol dm-3 The value in 7.83x10-6mol dm-3 is converted to units of mg dm-3 by multiplying with the relative atomic mass of iron, 55.85g mol-1. Therefore: SX = 7.83x10-6M x 55.85g mol-1 = 0.437mg dm-3 Finally, calculations were made to determine the standard deviation for concentration, SX per gram sample. 0.437 Therefore: c = = 0.109mg dm-3g-1 4 Similar calculations for standard deviation were performed for different parts of the broccoli plant. The results show that the broccoli buds contained the highest amount of iron, therefore, broccoli bud was selected for the second part of the research question which investigates the effects of incubating temperature on the amount of iron in broccoli buds. 20 See appendix 6 for the explanations of the symbols used in the formula. 22 6.0 Methodology adopted to investigate the effects of different incubating temperature on the amount of iron in broccoli buds 6.1 Preparing samples incubated in distilled water of different temperatures 1. Random samples from the buds were collected from broccoli plant (Brassica oleracea). Triplicate samples were obtained from different broccoli plants. 2. Water baths at room temperature 24.0°C, 60.0°C, 80.0°C and 100.0°C were prepared using electric water baths. 3. 4.000g of samples from the buds was weighed using an electronic balance (±0.001) into separate water baths. Triplicate samples were prepared for each temperature. 4. The samples were soaked for 15 minutes and then filtered. 5. The filtered samples were carefully transferred to crucibles without the lids on and then heated directly using a Bunsen burner for six hours. 6. 1.0cm3 of concentrated hydrochloric acid (4.0M) was added to each of the crucible to dissolve the ash to form aqueous iron(III) solution. Figure 10: Water baths used to incubate the samples. 23 6.2 Reducing iron(III) and measuring absorbance Same procedures from part 5.2 (page 18) was carried out to reduce the iron(III) in the samples and to measure the absorbance. 6.3 Data Collection Due to the intense colour formed by the complex, the samples were diluted by a factor of 5 to reduce the orange-red colour intensity formed, enabling the visible spectrophotometer to measure the absorbance21. 1.0cm3 of sample was pipette out and diluted with 4.0cm3 of distilled water to create a 5.0cm3 solution. 21 A deviation would occur if the intensity of the sample is too high. 24 Incubating Random samples Absorbance reading, A after temperature Mean absorbance Mean absorbance(a) ± for each sample (95%) Confidence (±0.1)°C (triplicates) 60 minutes 90 minutes 120 minutes Interval 1 0.289 0.457 0.371 0.372 Room Temperature, 2 0.356 0.408 0.365 0.376 0.369±0.020 24.0°C 3 0.342 0.463 0.270 0.358 1 0.340 0.429 0.373 0.381 60.0°C 2 0.316 0.400 0.310 0.342 0.362±0.050 3 0.316 0.438 0.334 0.363 1(b) - - - - 80.0°C 2 0.221 0.415 0.226 0.287 0.280±0.030 3 0.241 0.319 0.258 0.273 1 0.067 0.050 0.082 0.066 100.0°C 0.068 0.119 0.096 0.094 0.121±0.200 2 3 0.180 0.270 0.181 0.204 Table 4: Incubating temperature, the sample number, the absorbance reading after 60, 90 and 120 minutes respectively and the mean absorbance with (95%) confidence interval for triplicate samples, all of which the samples were diluted by a dilution factor of 5. (a) Mean absorbance ± (95%) Confidence Interval obtained for the random triplicate samples. (b) / - Results were not included into the mean absorbance due to inconsistencies and irregularities. 25 Qualitative Observations After incubating the broccoli buds in water of 100.0°C, it is observed that the water turns greenish in colour. The intensity of the greenish colour decreases as the temperature of the water decreases. However, the intensity of the orange-red coloured complex decreases as the temperature of the water for the sample increase. Figure 11: The greenish colour filtrate for the samples at 100.0°C incubating temperature. 26 6.4 Data Processing The absorbance for the diluted concentration and its actual concentration expressed in mg dm-3 g-1 for samples incubated at different temperature: Diluted concentration(a) Actual concentration Incubating Amount of Diluted concentration Amount of iron(II) in temperature Mean absorbance (b) Concentration of iron(II) in one of iron(II) one gram of sample ± (±0.01)°C iron(II) ± SD, c / gram of sample ± Confidence Limit ± SD22, c / SD, c / mg dm-3 ± SD, c / x10-4 mol dm-3 mg dm-3 g-1 mg dm-3 g-1 Room 0.369±0.020 1.19±0.06 6.64±0.31 1.66±0.08 8.30±0.38 Temperature, 24.0 0.362±0.050 1.17±0.05 60.0 6.53±0.30 1.63±0.08 8.15±0.38 0.280±0.030 0.901±0.062 80.0 5.03±0.35 1.25±0.09 6.25±0.43 0.121±0.200 0.379±0.058 100.0 2.12±0.33 0.53±0.08 2.65±0.40 Table 5: Incubating temperature, mean absorbance with (95%) confidence interval for triplicate samples, its corresponding concentration of iron(II) when compared to the calibration curve, concentration of iron(II) in mg dm-3 and the concentration of iron(II) in one gram of sample. The data are separated as diluted concentration and actual concentration. (a) diluted by a factor of 5 (b) Mean absorbance ± (95%) Confidence Interval obtained for the random triplicate samples. SD Standard Deviation 22 See Appendix 6 for calculations for the standard deviation of the concentration of iron(II). 27 Example calculation on the amount of iron(II) found after incubating at 100.0°C From the standard calibration curve of iron(II), the regression equation relating absorbance to concentration is given as A = 0.3045(c x 10-4) + 0.0055 (refer to page 16). Since the graph is plotted as absorbance, A against concentration, c x10-4, the final value of c is multiplied by 10-4. The mean absorbance for samples incubated at 100.0°C is 0.121. ����−0.0055 Therefore: c =( ) x 10-4 0.3045 0.121−0.0055 =( ) x 10-4 = 0.379x10-4M 0.3045 The value in 0.379x10-4mol dm-3 is converted to units of mg dm-3 by multiplying with the relative atomic mass of iron, 55.85g mol-1. Therefore: c = 0.379x10-4M x 55.85g mol-1 = 2.12mg dm-3 Calculations were made to determine the amount of iron per gram sample. 2.12 Therefore: c = = 0.53mg dm-3g-1 4 Finally, the value obtained was multiplied by 5 because the samples were diluted by a factor of 5. Therefore: c = 0.53 x 5 = 2.65mg dm-3g-1 Similar calculations were performed for different incubating temperature. 28 Example calculation on the standard deviation of amount of iron(II) found after incubating at 100.0°C Calculations for standard deviation were performed using Windows Excel 2007. The formula23 used is as shown below: sr 1 1 (�������� − ���� )2 SX = ���� { ���� + ���� +���� 2 (���� ���� − ���� )2 }1/2 0.02305 1 1 (0.121− 0.290)2 = { + 6 +(3044.14)2 (3.26x10 −8 )}1/2 3044 .14 3 = 5.84x10-6mol dm-3 The value in 5.84x10-6mol dm-3 is converted to units of mg dm-3 by multiplying with the relative atomic mass of iron, 55.85g mol-1. Therefore: SX = 5.84x10-6M x 55.85g mol-1 = 0.33mg dm-3 Calculations were made to determine the standard deviation for concentration, SX per gram sample. 0.33 Therefore: c = = 0.08mg dm-3g-1 4 Finally, the value obtained was multiplied by 5 because the samples were diluted by a factor of 5. Therefore: c = 0.33 x 5 = 0.40mg dm-3g-1 Similar calculations were performed for different incubating temperature. 23 See appendix 6 for the explanations of the symbols used in the formula. 29 7.0 Data Presentation The parts of the broccoli and the corresponding concentration of iron(II) per gram of sample, c / mg dm-3 g-1 Concentration of iron(II) in one gram of sample, 3.5 3 (a) 2.5 mg dm-3 g-1 2 c/ 1.5 1 0.5 0 Buds Stems Base Parts of the broccoli plant Graph 2: The graphical representation of the amount of iron(II) and in various parts of the broccoli plant. (a) = Error bars denote (95%) confidence interval of triplicate samples of each part of the broccoli plant. 30 The incubating temperature, T / °C and the corresponding amount of iron(II) per gram of sample, c / mg dm-3 g-1 10 Amount of iron(II) in one gram of sample, (a) 9 8 7 mg dm-3 g-1 6 c/ 5 4 3 2 1 0 24 60 80 100 Incubating temperature, T / °C Graph 3: The graphical representation of the amount of iron(II) and at different incubating temperature. (a) = Error bars denote (95%) confidence interval of triplicate samples for each incubating temperature. 31 8.0 Data Processing: ANOVA and Tukey’s HSD Test24 Data processing is carried out using Analysis of Variance (ANOVA) and Tukey’s HSD (honestly significant difference) test. ANOVA shows the variance between or within each group. A null hypothesis is first assumed where there is no difference between the means of different groups. Then the F ratio is calculated. mean square between groups F ratio = mean square within groups The result of ANOVA shows whether the F ratio is greater than the F critical value at the significance level of 0.05 (α=0.05), if so, the null hypothesis is rejected and there is one group that is significantly different from others. Three assumptions were made to carry out ANOVA: 1. The observations are independent (the value of one observations is not correlated with the value of another). 2. The observations in each group are normally distributed. 3. Equal variance for all groups. Tukey’s HSD post hoc analysis is then conducted to test the hypothesis that all possible pairs of means are equal. Pairs with differences exceeding the HSD are considered to be significantly different. 24 See appendix 9 for ANOVA and Tukey’s HSD Test. 32 ANOVA is performed using Microsoft Excel 2007 while Tukey’s HSD25 test is calculated manually. The results are tabulated as shown below: Variable F-value F-critical Indication Parts 2012.24 6.94 ANOVA tests on both sets of data show F-value > F-critical. This indicates that there is a group which is significantly Temperature 23.80 4.35 different from the others in their own respective set of data. Table 6: Results of ANOVA on two sets of data to determine whether there is significant difference between the mean absorbance reading of samples obtained from different parts of the broccoli and for the variable of the temperature of water which the broccoli buds were soaked in. 25 See appendix 9 for ANOVA and Tukey’s HSD Test. 33 Tukey’s HSD multiple comparison test was carried out and the results are tabulated as shown below: Group Combination Mean absorbance Mean difference of reading of different HSD critical value Implication absorbance reading parts of the broccoli plant Buds Stems 0.560 0.029 Significant difference Buds Base 0.569 0.029 Significant difference Stems Base 0.009 0.029 No Significant difference Table 7: Results of Tukey’s HSD test on the mean absorbance reading of samples from each part of the broccoli plant to determine which group is significantly different than the other. Significance test at α = 0.05. Group Combination, °C Mean Mean absorbance reading of difference HSD critical Implication broccoli plant soaked in different absorbance value temperature of water reading 100 80 0.159 0.111 Significant difference 100 60 0.241 0.111 Significant difference 100 24 0.247 0.111 Significant difference 80 60 0.082 0.111 No significant difference 80 24 0.089 0.111 No significant difference 60 24 0.007 0.111 No significant difference Table 8: Results of Tukey’s HSD test on the mean absorbance reading of samples that have been incubated in water of different temperature to determine which group is significantly different than the other. Significance test at α = 0.05. 34 9.0 Data Analysis 9.1 Parts of the broccoli plant Graph 2 indicates that iron content is highest in the broccoli buds with 2.90mg dm-3g-1 followed by the stems and base which is 0.34mg dm-3g-1 and 0.30mg dm-3g-1 respectively indicating that the iron content in the broccoli buds is 88% ~ 90% higher when compared to the stems and base. Statistical tests performed at α=0.05 showed a significant difference in iron content found in broccoli buds and stems and broccoli buds and base as the mean difference of each group exceeds the critical value (Table 7). There is no significant difference between the iron content in broccoli stems and base. Therefore, results show that iron content is highest at the broccoli buds. There are two possible explanations on why iron content is highest at the broccoli buds: The broccoli buds are greener compared to the stems and the base due to higher chlorophyll density. Therefore, more light energy is absorbed for electron excitation during photosynthesis. Specific iron-containing electron-carrier proteins like ferredoxin and cytochrome b6f are required for electron transportation. In conclusion, broccoli buds are greener due to high chlorophyll density which absorbs more energy for more electron excitation. Thus, more iron-containing electron-carrier proteins are required for electron transportation, resulting to highest iron content in the broccoli buds. Another possible explanation is that electron-transport chains are present in the mitochondria. Mitochondria is found abundantly in the broccoli buds because they are involve in energy production while the stems and base contains xylem and phloem are involved in food and water uptake. Iron-containing electron-carrier proteins such as 35 cytochrome c and Fe –S clusters transports electrons in the mitochondrial electron-trasport chain. In conclusion, this process occurs more frequently in the broccoli buds due to higher abundance of mitochondria, resulting in a greater number of iron-containing electron-carrier proteins found in the broccoli buds. Thus, iron content is highest in the broccoli buds. 36 9.2 Incubating temperature Graph 3 indicates that the iron content in broccoli buds samples incubated at 100.0°C is the lowest followed by samples incubated at 80.0°C, 60.0°C and room temperature 24.0°C. Results show that iron content in the control sample incubated at room temperature 24.0°C and sample incubated at 100.0°C is 8.30mg dm-3g-1 and 2.65mg dm-3g-1 respectively indicating a 68% decrease in iron content after incubating at 100.0°C. Table 5 shows that some data have been omitted due to inconsistencies and irregularities compared to the other data. However, for this part of the data collected, Q rejection test was not performed. The omission was based solely on observations as the outlier data would influence the results of the investigation. Statistical tests performed at α=0.05 showed a significant difference in iron content of broccoli buds samples incubated at 100.0°C when compared to samples incubate at 80.0°C, 60.0°C and room temperature 24.0°C where the mean difference of each group exceeds the critical value (Table 8). Preliminary data suggest that iron content is the lowest when broccoli buds samples are incubated at 100.0°C. Given a few possible explanations: Cell walls break down easily and rate of denaturation of the protein membrane present at the cell membrane increases when exposed to high temperature. This enables proteins found in the buds to leach or diffuse out of the buds more easily which includes the diffusion of iron-containing electron-carrier protein complexes such as ferredoxin, cytochromes b6f, cytochrome c and Fe –S clusters. High temperature increases kinetic energy of the electron- carrier proteins, resulting to the increased probability of the protein molecules to diffuse out of the cell membrane. This is further suggested by the qualitative observations as the sample 37 filtrate of 100.0°C incubating temperature is greener compared to other sample filtrate of lower incubating temperature. This indicates that maybe chlorophyll diffuses out of the sample, causing the green colouration. In conclusion, increased incubation temperature causes increased rate of diffusion. It is also possible that the proteins present in the buds are denatured and reacts with each other forming unknown products of possible physical property changes such as increased solubility or the ability to diffuse through the cell membrane, resulting to higher quantity of iron diffusing out of the broccoli buds. Maxwell–Boltzmann distribution indicates that rate of reaction increases as temperature increases, thus temperature directly influences the rate of iron diffusing out of the broccoli bud. Therefore, iron content is lowest after broccoli buds samples are incubated at 100.0°C when compared to other lower incubating temperatures. 38 10.0 Evaluation 10.1 Uncertainties and Limitations Errors might occur during dry ashing of the samples using crucibles due to incomplete combustion. This is evident as some black substance suspected as carbon and unoxidized iron is still visibly sticking to the crucible. Since no lids were used, iron which is considered a volatile metallic compound may be lost during combustion. When reducing iron(III) and measuring the absorbance, solutions were added in the order: trisodium citrate solution, hydroxylammonium chloride solution and phenanthroline solution. It is unknown whether the sequence in which the solutions were added would affect the intensity of the orange-red complex formed. Simplified and modified procedures were carried out for this investigation due to time constraint as it is solely for iron content comparison and it does not reflects the actual amount of iron in the broccoli.[8] There might be interfering ions present in broccoli plants which would react with phenanthroline solution to produce a colour complex, interfering with the intensity of the orange-red complex produced by iron-phenenahroline complex. Due to time constraint, only triplicate random samples were performed in this investigation (n=3). Although random sampling was performed, the sample size (n=3) is too small to be a good representation of the general population of Brassica oleracea. Contamination in the samples might occur due to impurities left on the broccoli plants after washing. This is evident as some of the outlier data were omitted due to inconsistencies when compared to other samples. 39 Systematic error also arises due to the visible spectrophotometer. Fluctuations occur frequently when the absorbance of the samples were being measured, giving inconsistent absorbance readings. The dry mass of the samples might vary as there is difficulty in obtaining the dry mass. Samples heated in the over for too long might be charred but samples heated for a short duration might still contain water. Hence, this uncertainty affects the accuracy on the iron content in the samples. 10.2 Ways of Improvement Methods can be carried out to improve dry ashing method used. Microwave furnaces can be used to replace the crucibles used. Samples are placed in small chamber to undergo combustion quickly and preventing the loss of volatile metallic compounds. Although expensive, it provides an alternative method of dry ashing using crucible which would reduce the systematic error present. [9] Atomic-absorption spectroscopy (AAS) can be used for more accurate quantification of iron in various samples. Samples are first vaporized and absorption of visible light excites the electrons to a higher electronic energy level, enabling the concentration of iron to be accurately quantified. Although AAS instrument would provide accurate data, it is an expensive equipment. [10] Other colorimetric reagents can be used to increase the sensitivity of iron quantification such as 4,7-Diphenyl-1,10-phenanthroline as it extracts the iron in the reagents and water used in the test and thus of reducing the blank to zero. [11] 40 Sample size should be increased in order to improve the accuracy and reliability of the data. Increasing sample size will reduce the standard deviation. The larger the sample size, the more likely it is able to represent the general population of Brassica oleracea. 10.3 Further Investigations and Unresolved Questions Prior investigation with o-phenanthroline on spinach, Amaranthus gangeticus on iron content in different coloured part of the leaves: red and green failed due to interfering ions and inconsistent data collected. Thus, method of quantification other than using o- phenanthroline will be needed for this investigation. Investigation on the effects of different cooking methods on the iron content of the vegetable such as stir-frying, steaming and microwaving should be explored in order to raise awareness. It is believed that iron content would not decrease as significantly if broccoli is steamed or microwaved because water is not directly in contact with the broccoli, thus reducing leaching of iron from the broccoli. An investigation can be carried out on how pH condition affects the iron content in broccoli. Broccoli can be incubated in water of different pH value for this investigation to determine the effects of pH on the iron content. 41 11.0 Conclusion With enough supporting statistical evidence, it can be concluded that broccoli (Brassica oleracea) buds has the highest iron content at 88% ~ 90% higher than the iron content at the stems and buds. After being incubated at temperature of 100.0°C, the iron content in the broccoli buds significantly decreases by 68% when compared to samples incubated at room temperature 24.0°C. It is suggested that iron content decreases as the incubating temperature increases. 42 12.0 Reference [1] National Institutes of Health, 2004. Dietary Supplement Fact Sheet: Iron. [Online] (Updated 24 August 2007) Available at: http://ods.od.nih.gov/factsheets/iron.asp [Accessed 14 December 2008] [2] Office of Dietary Supplements, 2005. Facts About Iron. [Online] (Updated 7 September 2005) Available at: http://ibdcrohns.about.com/cs/nutrition/a/fdairon_2.htm [Accessed 14 December 2008] [3][4] USDA National Nutrient Database, 19??. Nutrient Data Labotory. [Online] Available at: http://www.nal.usda.gov/fnic/foodcomp/search/ [Accessed 15 December 2008] [5] Garrett, R. H., & Grisham, C. M., 2005. Biochemistry. 3rd ed. Belmont (CA): Thomas Learning, Inc. Koolman, J. & Roehm K. H., 2006. Color Atlas of Biochemistry. 2nd ed. New York: Thieme Stuttgart. Institute for Protein Research, Osaka University, 200?. Ferredoxins... Ubiquitous Iron- Sulfur Proteins. [Online] Available at: http://www.protein.osaka-u.ac.jp/enzymology/Fd_Model/Ferredoxin.html [Accessed 27 March 2009]. Carnegie Mellon University, 200?. Research Projects. [Online] Avalibale at: http://www.chem.cmu.edu/groups/hendrich/research/index.html [Accessed 27 March 2009]. Darragh, F., 200?. Kinetics: Collision Theory, Maxwell-Boltzmann Distribution. [Online] Available at: http://www.bustertests.co.uk/studies/kinetics-collision-theory-maxwell- boltzmann-distribution.php [Accessed 1 July 2009]. [6] Daniel C. H., 2002. Quantitative Chemical Analysis, 6th ed. s.l. s.n. [7] Anon. Spectrophotometric Determination of Iron in Vitamin Supplement Tablets. [Class Handout] [8] Krishna Murti, G. S. R.,Volk, V. V. & Jackson M. L., 196?. Colorimetric Determination of Iron of Mixed Valency by Orthophenanthroline, [online]. Abstract only. Available at: http://soil.scijournals.org/cgi/content/abstract/30/5/663 [Accessed 30 March 2009] [9] Skoog, D. A, West, D. M., Holler, F. J., Crouch, S. R., 2004. Fundamentals of Analytical Chemistry, 8th ed. US: Thomas Learning, Inc. 43 [10] Tissue, B. M., 1996. Atomic-Absorption Spectroscopy (AA). [Online] (updated 21 August 1996) Available at: http://elchem.kaist.ac.kr/vt/chem-ed/spec/atomic/aa.htm [Accessed 8 July 2009] [11] GFS Chemicals, 199?. Organics - Phenanthrolines and Bipyridines. [Online] Available at: http://www.gfschemicals.com/statics/documents/technical/technical300af5f5bcce4870 85c1ff0229dcac49.html [Accesed 8 July 2009] Kuzma, J. W. & Bohnenblust, S. E., 2001. Basic Statistics for the Health Sciences, 4th ed. s.l., Mayfield Publishing Company. Christian, G. D., 2004. Analytical Chemistry, 6th ed. s.l., Matrix Publising Services. Lim, J. A., 2008. Antimicrobial Activity, extended essay. 44 13.0 Appendix Appendix 1: Procedure to prepare the required solutions 1. 1000.0cm3 of 25.0x10-5M iron(II) solution was prepared using (0.049 ± 0.001)g of hydrated iron(II) sulphate, Fe(SO4)2(NH4)2∙6H2O, the solution contained 1.0cm3 of concentrated hydrochloric acid (4.0M). A series of dilution was carried out to obtain the iron(II) solution of concentrations 10.0x10-5M, 7.50x10-5M, 6.00x10-5M, 5.00x10-5M and 2.50x10-5M. 2. 10% hydroxylammonium chloride, NH3OHClsolution was prepared by dissolving (10.000 ± 0.001)g of solid in 100.0cm3 of distilled water. 3. 5% of trisodium citrate, Na3C6H5O7 solution was prepared by dissolving (5.000 ± 0.001)g of solid in 100.0cm3 of distilled water. 4. 0.01M Orthophenanthroline solution was prepared by dissolving (0.198±0.001)g of the solid in 10.0cm3 of ethanol26 and 90.0cm3 of distilled water was added to form a 100.0cm3 solution. 26 Ethanol was added to dissolve the phenanthroline solids as it consists of polar molecules while ethanol is a polar solvent. 45 Appendix 2: Dilution of iron(II) standards Steps were carried out to dilute the 25.0x10-5M iron(II) stock solution to the solutions of lower concentration 10.0x10-5M, 7.50x10-5M, 6.00x10-5M, 5.00x10-5M and 2.50x10-5M. The dilution table is as shown below: Concentration of Volume of 2.5x10-4M iron(II) solution Volume of distilled iron(II) standards / transferred using pipette / cm3 water added to form -3 3 the 100cm3 solution / mol dm (±0.03)cm cm3 (±0.08)cm3 10.0x10-5 40.00 60.00 7.50x10-5 30.00 70.00 6.00x10-5 24.00 76.00 5.00x10-5 20.00 80.00 2.50x10-5 10.00 90.00 Table 9: Concentration of iron(II) standards, volume of 25.0x10 -5M iron(II) solution transferred to a 100.0cm3 volumetric flask using a graduated pipette and the volume of water added to form a 100.0cm 3 solution. According to the table above, the required volume of 25.0x10-4M iron(II) solution is transferred to a 100.0cm3 volumetric flask using a graduated pipette. Distilled water is added until the bottom of the meniscus reaches the calibration mark. 46 Appendix 3: Confidence Limit Confidence limit allows us to estimate the range within which the true value might fall, within a given probability, defined by the experimental mean and the standard deviation. The confidence limit is given by: �������� Confidence limit = ���� ± ���� where t is a statistical factor that depends on the number of degrees of freedom, v and the confidence level desired. The number of degrees of freedom is one less than the number of measurements, s is the standard deviation of the mean and N is the number of samples. v Confidence Level 1 12.701 2 4.303 3 3.182 4 2.776 5 2.571 6 2.447 7 2.365 8 2.306 9 2.262 Table 10: Values of t for v Degrees of Freedom for confidence level of 95%. 47 Appendix 4: Regression Analysis Regression analysis was carried out to determine that there is a significant correlation between the concentration of iron and absorbance used to plot the standard calibration curve for iron(II) in section 4.0. The regression analysis is carried out with α = 0.05. Regression Statistics Multiple R 0.996 R Square 0.993 Adjusted R Square 0.991 Standard Error 0.0232 Observations 6 ANOVA df SS MS F Significance F Regression 1 0.302 0.302 559.25 1.896x10-5 Residual 4 0.00216 5.403x10-4 Total 5 0.304 Standard Lower Upper Lower Upper Coefficients Error t Stat P-value 95% 95% 95.0% 95.0% Intercept 0.00554 0.0153 0.362 0.736 -0.0370 0.0481 -0.0370 0.0481 Concentration 0.305 0.0129 23.65 1.90x10-5 0.269 0.340 0.269 0.340 Table 11: Results for the regression analysis of standard calibration curve for iron(II) with α = 0.05. Notation Meanings df Degree of freedom MS Mean square SS Sum of squares The analysis shows that the P-value is 1.90x10-5 (P<0.05). Therefore, there is a significant correlation between the concentration of iron and absorbance used to plot the standard calibration curve for iron(II). 48 Appendix 5: The ash was dissolved in acid. Black coloured substance can be sticking on the side of the inner wall 49 Appendix 5: Q Test Q test is carried out to determine whether a particular measurement should be rejected. The Q test is a statistical test which is used when only a small number of results are obtained. | outlier −nearest neighbour | Qcalc = range The value of Qcalc is compared to a set of Q test rejection coefficients for 90% confidence level. N 3 4 5 6 7 8 9 10 11 12 Q 0.94 0.76 0.64 0.56 0.51 0.47 0.44 0.41 0.39 0.37 Table 12: Number of samples and the corresponding Q test rejection coefficients for 90% confidence level. The outlying data can be rejected when Qcalc > Q test rejection coefficient. 50 Appendix 6: Standard Deviation for concentration of iron(II) The standard deviation for concentration of iron(II) is calculated using a statistic formula. An assumption was made such that there is negligible systematic errors during preparation. The formula is given as shown: sr 2 SX = ���� 1 1 − {���� + ���� +���� 2(��������(���� ���� )���� )2 }1/2 − ���� where: SX = Standard deviation of the concentration of the sample sr = Standard deviation of the standard calibration curve m = Slope of the standard calibration curve n = Number of calibration standards �������� = Mean absorbance of the samples ���� = Mean absorbance of all standards �������� = Concentration of the standards ���� = Mean concentration of the standards 51 Appendix 7: Calculations of ANOVA and Tukey’s HSD Test A null hypothesis is first assumed where there is no difference between the means of different groups. H0: μ1 = μ2 = μ3 = ... = μk The theoretical basis for performing ANOVA is the partitioning of the variance of all observations into two sources of variation: variation between the group means and variation within each group. The sampling distribution used for testing is called the F distribution. The notations of ANOVA and meanings are tabulated as shown below: Notation Meanings 2 MSw or �������� Within-group variance / mean square within 2 MSb or �������� Between-group variance / mean square between df Degree of freedom k Number of groups n Number of observation in each group N Total number of observation α Significance level SSb Sum of squares between group SSw Sum of squares within group Table 13: Notations of ANOVA and meanings. If MSB > MSW, the variance between group is greater than the variance within group, then there is treatment effect. There is no treatment effect when MSB ≈ MSW. MS b F ratio = MS w MSb has k – 1 degree of freedom, dfb. MSw has N – k degree of freedom, dfw. Source of Sum of df Mean F ratio Critical F P value variation Squares Squares, (α = 0.05) (s2) Between SSb k-1 ���� MSb = ����−1 �������� MS���� Fk-1,N-k Computer MS���� generated Within SSw N-k �������� ���� MSw = ����−���� Total SSt N-1 Table 14: One-way ANOVA table. 52 Post hoc Tukey’s HSD test is performed when the F ratio is greater than the critical F which means that there is significant difference between at least one pair. Tukey’s HSD test is carried out to perform multiple comparisons. The formula for calculating the HSD value is as shown below: MS ���� HSD = q (α, k, N-k) ���� There is significant difference when the difference between the mean of the groups is greater than the HSD value. 53 The table below shows the ANOVA table generated using Microsoft Excel 2007. 1. The part of the broccoli which contains the highest iron content Groups Count Sum Average Variance Buds 2 1.278 0.639 0.0002 Stems 2 0.158 0.079 0.0001 Base 3 0.21 0.070 0.00006 ANOVA Source of SS df MS F P-value F crit Variation Between Groups 0.457 2 0.228 2012.2 9.86x10-7 6.94 Within Groups 0.0005 4 0.0001 Total 0.4572 6 Table 15: ANOVA table 0.0001 HSD = 5.04 3 = 0.029 54 2. The effects of incubating temperature on the amount of iron. Groups Count Sum Average Variance Room Temperature 3 1.106 0.369 8.933x10-5 (24°C) 60°C 3 1.086 0.362 0.0004 80°C 2 0.560 0.280 9.80x10-5 100°C 3 0.364 0.121 0.005 ANOVA Source of Variation SS df MS F P-value F crit Between Groups 0.1192 3 0.040 23.80 0.0005 4.35 Within Groups 0.0117 7 0.0017 Total 0.1308 10 Table 16: ANOVA table 0.0017 HSD = 4.68 3 = 0.111 55