Analysis of Fat in Snack Foods by Gas Chromatography and Gas Chromatography / Mass Spectrometry
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This presentation discusses the analysis of fat in snack foods using gas chromatography and gas chromatography/mass spectrometry. It covers the principles, procedure, and results of the experiment. The types of fat present in Twisties and Pretzels are also identified. The presentation is presented by Abrar Taif and lab demonstrator Ben Ford.
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Lab Demonstrator- Ben Ford Presented by: Abrar Taif (44182562) CBMS 825 Chemical Analysis II Analysis of Fat in Snack Foods by Gas Chromatography and Gas Chromatography / Mass Spectrometry Experiment 3
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Introduction ο΄Snack foods that contain large amount of fat is of great significant health concern ο΄Saturated fats increases blood cholesterol in humans1 ο΄High LDL level associated with increased risk of heart disease and stroke in humans1 ο΄Perception of Saturated and Unsaturated fats2 ο΄Saturated Fats have single C-C bond2 ο΄Unsaturated Fats have one more more double C=C bond2 ο΄The principles involving the application of gas chromatography (GC) and gas chromatography/mass spectrometry (GC-MS) ο΄The investigation of operational differences between flame ionisation detector that implements gas chromatography and mass spectrometer detector that implements gas chromatography/mass spectrometer. ο΄The significance of derivation technique of fatty acid in snacks while applying gas chromatography (GC)
AIM ο΄The aim of the experiment is to analyze types of fat in snack foods by using gas chromatography and gas chromatography/ mass spectrometry.
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Experimental Principals Flame Ionisation Detector through application of Gas ChromatographyFID ο΄Mechanism: - Compounds burned in H-air flam. - C-containing compounds produce ions βattracted to the collector - No. of ions hitting the collector is measuredβ signals generated ο΄Selectivity: - Compounds with C-H bonds β - Poor response for other organic compounds ο΄Sensitivity:0.1-10 ng ο΄Linear range:105β 107 ο΄Gases: - combustion: H & air - makeup: He & N ο΄Temperature:250-300 Μ C (400-450 Μ C for β temp. analysis)
Principle of GC-MS using mass spectrometer detector
Comparison between GC using flame ionisation detector and GC-MS using mass spectrometer detector Gas Chromatogrpahy (GC)Gas Chromatography-Mass Spectrometer (GC-MS) Carrier gas. βHydrogen (H2) Ion Source InjectorInjector ColumnElectromagnet Detector (FIDDetector (MS at 74 m/z) Gas ChromatographyMass Spectrometer
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Derivatisation technique of fatty acid when using GC ο΄For analysis by GC & GC-MS, analyte must be volatile. ο΄Fat and oil triglycerides: Not very volatile. Large molecules (800-1000 mw). ο΄Methods for the conversion of fats and oils into fatty acid methyl esters: ο΄Acid or base-catalysed trans-esterification where reaction with ethanol in the presence of acid or base catalyst directly (boron trifluoride/methanol) directly convert triglyceride to fatty acid methyl esters. The acid catalyst is the lewis acid BF3. ο΄Saponification or acid hydrolysis or enzymatic hydrolysis of the triglacyride to releas fatty acid then by acid catalyzed esterification to give FAMEs. β’TG hydrolysis β’fatty acid Derivatisation β’Fatty acid methyl esters (FAME) Analysis by GC or GC-MS
Procedure Preparation of FAMEs from fats in snack food ο΄Two snack foods were selected to be analyzed using GC and GC/MS. Twisties (contains 23.3 g/ 100g total fat) and Pretzels (contains 3.6 g / 100 g total fat). ο΄Approximately 5 g were crushed using clean mortar and pestle. ο΄The nutritional information on the packing was examined for both snack foods and the aliquot mass was calculated using the formula ο΄Aliquotmass = (15000 / fat in productsg/100 g) mg ο΄Amount of 643.78 mg of Twisties and 4167.7mg of Pretzels were taken after crushing the sample and aliquoting them ο΄Internal standard (tridodecanoin - C12:0 triglyceride) was added. ο΄Aa volume of 20 mL of 1:1 (v/v) chloroform / methanol was added and the mixture was ultrasonicate for 5 minutes. ο΄The snack foods were Filtered from the1:1 (v/v) chloroform / methanol solution using a Buchner funnel and the beaker was washed with 5 mL of 1:1 (v/v) chloroform / methanol. ο΄Remove 1 mL of the filtered and place in clean scintillation vial. ο΄The sample was evaporated to dryness (oil form) by adding 2 mL of BF3/ methanol derivatisation reagent to the vial , the vial was caped and the mixture was shook vigorously. ο΄The mixture was heated to 60 Β°C in the oven for 10 minutes and shaking of the mixture was maitained every 2 minutes. ο΄The vial was removed from the oven and left to cool down. Then, 5 mL of hexanes and 5 mL of saturated NaCl were addedto the vial. ο΄The vial was caped and the mixture was shook vigorously for a minute. ο΄After separation of the two phases, 1 mL of the top layer was removed using pasture pipette and transfer into clean vial. This is the sample to be analyzed contains methyl ester derivatives. ο΄The computer was prepared to collect data and 0.5 mL of the sample was injected into GC and GC/MS.
Measurement of Fatty Acid Response Factor ο΄Thechromatographic conditions of GC-17A (SHIMADZU) and GCMS-QP5000 (SHIMADZU) were confirmed and the computer was prepared to collect data by follow-up the steps mentioned in experiment 4 manual. ο΄After the READY light on GC turns green and click sound on GC-MS was noticed, 0.5 ΞΌL ofFAME standardwas injected using 1ΞΌL syringe followed by pressing START button on front of GC. ο΄FAME standard 20 ug/mL contains C12:0, C14:0, C14:1, C16:0, C16:1, C18:0, C18:1, C18:2, C20:0 and C20:1 ο΄Check to see the run starts, wait for approximately 20 minutes to finished. ο΄When ready light turn green again, inject the sample again (duplicate).
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Results and DiscussionRaw Data from Gas Chromatography Fig-1 GC of Fame Std 2 Fig 2 -GC of Twisties Fig 3- GC of Pretzels
Raw Data from Gas Chromatography-Mass Spectrometer Fig-4- GC-MS of Fame Std 2 Fig-5- GC-MS of Pretzels Fig-6- GC-MS of Twisties
Relative Response Factor (RRF) Relative Response Factor(RRF) is an analytical parameter used in chromatographic procedures to control impurities/degradants in drug substance and drug product. RRF is used to correct the difference in detectorresponseof impurities with analyte peak. RRF is established by slope method with linear range of solutions4 For the obtained data using GC, RRF can be calculated by: NoFAMEConc ug/mlRetention TimeAreaRRF 1C12:0207.280106378.61.000 2C14:0208.190118253.20.900 3C16:0208.440109277.70.973 4C16:1209.090126228.30.843 5C18:0209.300113907.20.934 6C18:1209.990131208.10.811 7C18:22010.170115905.20.918 8C20:02010.460104388.61.019 9C22:02010.870122088.20.871 10C22:12011.040106585.60.998 Fig-7- GC RRF of Fame Std- 2 NoFAMEConc ug/mlRetention TimeAreaRRF 1C12:0206.864 1649313 21.000 2C14:0207.916 2032978 40.811 3C16:0208.219 2002117 20.824 4C16:1208.949 2353971 10.700 5C18:0209.195 2268987 80.727 6C18:1209.939 2502264 80.659 7C18:22010.147 2389465 30.690 8C20:02010.477 2250828 80.733 9C22:02010.870 2635729 70.626 10C22:12011.078 2540487 50.649 Fig-8- GC-MS RRF of Fame Std-2
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Gas Chromatography Fat content (g/100g)Aliquot mass (mg)Standard added (mg) Twisties23.3643.787.7 Pretzels3.64166.75.6 Noise level0.4 millivolt Gas Chromatography/Mass Spectrometry Fat content (g/100g)Aliquot mass (mg)Standard added (mg) Twisties23.3642.35.4 Pretzels3.64167.76.2 GC MS0.5*100000 Fig- 9-Standards and aliquots added in GC process Fig-10- Standards and Aliquots added in GC-MS process To measure the concentrations of fates in our samples: Concentration of analyte = Concentration of analyte per 100g=100 Species amount=
Analysis of Twisties Sample NoFAMErtAreaRRF Amount (mg) 1C 12:07.2717893.71.0007.7 2C 14:08.173240.10.9001.3 3C 16:0 4C 16:19.0859840.20.84321.7 5C 18:19.821383.10.8110.5 6C 18:19.977048.90.8112.5 7C 18:210.072303.40.9180.9 8C 18:210.1553467.50.9182.2 9C 22:010.4414459.51.0196.3 10C 22:1 Fig-11- Analysis of Twisties sample by GC NoFAMErtAreaRRF Amount (mg) 1C 12:06.867138879741.0005.4 2C 14:0 3C 16:0 4C 16:07.91635377470.8111.1 5C 18:0 6C 16:18.964722134710.70019.7 7C 18:19.93770388990.6590.2 8C 18:210.159705934660.69018.9 9C 18:210.478198421230.6905.3 10C 22:110.85410760640.6490.27 Fig-14 Analysis of Twisties sample by GC-MS mgg /100 g Total Fat43.16.69 Total Saturated Fat15.32.37 Total Monounsaturated Fat24.73.83 Total Polyunsaturated Fat3.10.48 Total Unsaturated Fat27.84.31 Fig-12- Amount of different types of fat in Twisties through GC mgg /100 g Total Fat50.97.92 Total Saturated Fat6.51.01 Total Monounsaturated Fat20.23.14 Total Polyunsaturated Fat24.20.07 Total Unsaturated Fat44.43.21 Fig-13- Amount of different types of fat in Twisties through GC-MS
Analysis of Pretzel Sample NoFAMErtAreaRRF Amount (mg) 1C 12:07.27272181.0005.6 2C 14:08.181133.10.9000.2 4C 16:19.0868381.50.84311.9 5C 18:19.989619.10.8111.6 6C 18:210.084721.30.9180.9 7C 18:210.16114766.80.91821.7 8C 18:210.371118.30.9180.2 9C 20:010.46180788.21.01937.9 10C 22:010.8017836.50.8713.2 Fig-15- Analysis of Pretzel by GC mgg /100 g Total Fat83.21.99 Total Saturated Fat46.91.13 Total Monounsaturated Fat13.50.32 Total Polyunsaturated Fat22.80.54 Total Unsaturated Fat36.30.86 Fig-16- Amount of different types of fat in Pretzelthrough GC NoFAMErtAreaRRF Amount (mg) 1C 12:06.833238452191.0006.2 2C 14:07.8809451380.8110.2 3C 16:18.925660147510.82414.1 4C 16:18.98113980160.8240.3 5C 18:19.91276886780.6591.3 6C 18:210.135977158420.69017.5 7C 20:010.4781475935530.73328.1 8C 22:010.83649946330.6260.1 9C 22:111.0449442080.6490.2 10C 22:1 Fig-18- Analysis of Pretzel by GC-MS mgg /100 g Total Fat68.01.63 Total Saturated Fat34.60.83 Total Monounsaturated Fat15.90.38 Total Polyunsaturated Fat17.50.42 Total Unsaturated Fat33.43.21 Fig-17- Amount of different types of fat in Pretzelthrough GC-MS
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Test of significant difference within the saturated FAMEs using GC FAME Twisties RRFPretzels RRF C 12:01.0001.000 C 14:00.9000.900 C 18:0 C 20:01.019 C 22:01.0190.871 mean0.9780.948 u1.0001.000 SD0.0640.073 Null hypothesis: There is no significant difference between the saturated FAMEs relative response factor at 95% confidence level. Alternative Hypothesis: There is significant difference between the saturated FAMEs RRF at 95% confidence level. Test statistics: Critical values:At the 95% confidence level using a two-sided t-test and with 3 degrees of freedom t = 3.18. Decision:As the calculated t-value0.20 and 0.36< 3.18, we accept the null hypothesis. Conclusion:There is no significant difference between the saturated FAMEs relative response factor using GC at 95% confidence level.
Test of significant difference within the saturated FAMEs using GC & GC-MS Note- We apply the same 6 step principle for double sided t-test at 95% Confidence Intervalwith n-1 degree of freedom to determine the significant differences of saturated FAMES from both GC& GC- MS methods TwistiesPretzels GCGC-MSGCGC-MS Test of significant different Test statistic value 0.200.500.360.66 Critical value at 95 % Cl 3.1812.713.182.78 Conclusion: significant difference (Yes/No) NONONONO
Limit of Detection (LOD) Limit of detection (LOD) of C12:0 on GC (FID) based on 10:1 signal to noise ratio: 10X =10 x noise = 10 x 0.4 mV = 4 mV Area of noise peak = 1.06 x 1.10()x 0.4 = 0.466 mV LOD = (0.466/106378.6) x1.06 = 4.64 x 10-6 Limit of detection (LOD) of C12:0 on GC-MS (TIC) based on 10:1 signal to noise ratio: 10X =10 x noise = 10 x 0.5 = 5 mV Area of noise peak = 1.06 x 1.10(W1/2) x 5 = 5.83 mV LOD = (5.83/16493132) x1.06 = 3.74 x 10-7 Limit of detection (LOD) of C12:0 on GC-MS (SIM m/z 74) based on 10:1 signal to noise ratio: 10X =10 x noise = 10 x 0.5 mV = 5.0 mV Area of noise peak = 1.06 x 1.10 (W1/2) x 5.0 = 5.83 mV -5
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Comparison between obtained results and manufacture tabulated values Twisties (g/100g)Manufacturer specifications/ g/100g Pretzels(g/100g) GCGC-MSTwistiesPretzelsGCGC-MS Total Fat6.697.9223.33.61.991.63 Total Saturated Fat2.371.011.130.83 Total Monounsaturated Fat3.833.140.320.38 Total Polyunsaturated Fat0.480.070.540.42 Total unsaturated fat4.313.210.863.21 β’Differences in experimental values compared to manufacturer values noticed β’Both Twisties and Pretzels have less total fat compared to manufacturers recommended values β’Further repeats and more accurate techniques required to get a precise value
Relative Merits of Techniques οPredictable response ofGC-FIDis useful for an initial quantitative overview of sample composition. οGC-MSdetector demonstrates lower LOD. GC-MS provides reliable, structural and mass information. οTotal Ion Chromatogram (TIC)is a chromatogram created by summing up intensities of all mass spectral peaks belonging to the same scan. οGC-MS (SIM m/z 74)Select 74 ion to monitor and only those mass fragments are detected by mass spectrometer. The advantage of SIM is that much mass intensities for 74 ion compared to TIC (74 m/z is the base peak of fatty acid methyl ester).
Possible Sources of Error in this Experimental Procedure β’Parallax error in reading the volumetric flask and uncertainty on glassware such as volumetric flask β’Integration of software with GC and GC-MS β’GC Syringe contamination and possible malfunction of GC instrument β’Sample storage and shelf life of experimental reagents and standard solutions β’Inappropriate sample preparation β’Poor injection technique β’Temperature and performance of column and detector β’The temperature of the injector β’Baseline noise
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Conclusio n β’The techniques of GC-MS and GC-FID were used to determine the amount of fat in Twisties and Pretzels β’The results that were obtained from the techniques were lower than those from manufacturer specifications β’Accuracy and precision of results obtained can be improved by repeating the experiment and increasing the number of standards.
Learning Outcomes β’Sample derivatisation techniques and why they are needed for GC analyses. β’Knowledge of the shorthand naming system used for fatty acids. β’Sample preparation techniques for GC analysis. β’Practical experience in the application of a derivatisation procedure. β’Practical experience in the use of internal standardisation for quantitative chemical analysis β’Practical experience in the use of the use splitless injection technique and GC and GC/MS instrumentation.
References: 1.Aued-Pimentel, S., Kus, M.M.M., Kumagai, E.E., Ruvieri, V. and Zenebon, O., 2010. Comparison of gas chromatographic and gravimetric methods for quantization of total fat and fatty acids in foodstuffs. QuiΜmica Nova, 33(1), pp.76-84. 2.Barwick, V.J., 1999. Sources of uncertainty in gas chromatography and high-performance liquid chromatography. Journal of Chromatography A, 849(1), pp.13-33. 3.Carrasco, T.P.E.N.A., Deelder, P.A.M. and Mayboroda, O.A., 2014. Evaluation of GC- APCI/MS and GC-FID as a complementary platform. Metabolomics of urinary tract infection: a multiplatform approach, 21(4), p.61. 4.Chemical analysis II CBMS825 Experiment 3: Analysis of Fat in Snack Foods by Gas Chromatography and Gas Chromatography/Mass Spectrometry, Macquarie University, 5.D.A.Skoog, D.M.West, F.J.Holler, S.R.Crouch, Fundamentals of Analytical Chemistry, 9th Edition 2014, Thomson Brooks/Cole. 6.Experiment 3 βAnalysis of Fat in Snack Foods by Gas Chromatography and Gas Chromatography/Mass Spectrometry, Macquarie university, Faculty of Science and Engineering, Department of Chemistry & Biomolecular Sciences, CBMS308/CBMS708/ CBMS825 Chemical Analysis II, 7.Healthy for good, Eat smat, viewed 18/03/2019,<https://healthyforgood.heart.org/Eat-smart/Articles/Saturated-Fats>. 8.Labtexts, Core Analytical Chemistry Instrumental Analysis Chromatography Gas Chromatography, viewed 01/04/2017, https://chem.libretexts.org/Core/Analytical_Chemistry/Instrumental_Analysis/Chromatography/Gas_Chromatography. 9.Nutrition source, What should you eat, viewed 18/03/2019, https://www.hsph.harvard.edu/nutritionsource/what-should-you-eat/fats-and-cholesterol/.
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