Proximate analysis of Fonterra


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Proximate analysis of Fonterra

  1. 1. 06165605 Lab Report: Proximate Analysis 151.231 Food Chemistry for Nutrition Jessica Woods- 06165606 5/24/2013 Dr. Sung Je Lee
  2. 2. 1 Contents Abstract...............................................................................................................................................2 Introduction ........................................................................................................................................3 Materials and Methods.......................................................................................................................7 Conclusion.........................................................................................................................................18 References ........................................................................................................................................20 Appendix .............................................................................................................................................0
  3. 3. 2 Abstract A proximate analysis of whole milk powder was carried out to determine the percentages of its constituents. A proximate analysis is a quantitative analysis of the different macronutrients in a food sample, in this case a whole milk powder sample. The objective was to determine the percentage quantity of the components of the sample. The components analysed were calcium content, moisture, protein, fat, carbohydrates and ash. Calcium was measured using a dye binding assay, which yielded the result of 764mg/100g on average. This result was precise but inaccurate. To determine the amount of moisture the air-oven method was used. This provided a 2.0334% moisture content which had a low level of precision and reasonably high level of accuracy. In order to provide the amount of protein in the whole milk sample the Kjeldahl method was used, which provided both nitrogen and crude protein. Using a conversion factor of 6.25 due to the product being milk the result was 3.7523% for nitrogen and 23.940% for protein. This was a reasonably high level of accuracy and precision for nitrogen and a satisfactory level of accuracy and low level of precision for crude protein. The Ash content was revealed using the dry ashing method, which gave a very high level of accuracy and precision, so high that there was 0% relative error. The crude fat content was discovered using the mojonnier method which gave a reasonably high level of accuracy and a low level of precision, the coefficient of variance was 31.84%, which is well above the limit of 4%. Carbohydrate content was exposed by means of subtracting the sum of all of the other components percentages from a hundred. The resulting 40.94% revealed a high level of accuracy but low precision.
  4. 4. 3 Introduction The food industry is highly regulated by government protocols and international standards and policies which ensure appropriate quality control and supply chain management of food products. In order to ensure that food products meet these requirements food analysis of the composition and characteristics of the foods are mandatory. The entire supply chain is monitored and controlled, from raw ingredients, through to production and within the marketplace (Nielson, 2010). Proximate analysis is the technique used in this lab experiment. Proximate analysis is the analysis of food material in order to determine the percentages of ‘moisture, protein, fat, ash and crude fibre in food.’ The term nitrogen-free extract (NFE) is used to cover all the other material not present in the sample. This is not measured using proximate analysis, but rather through ‘subtracting the sum of percentages of moisture, protein, fat, fibre and ash from a hundred. This calculation determines the errors of various calculations. When deciding on the technique to use the method will depend on the requirements of the situation and the availability of resources. Resources include the equipment, analytical skills and available chemicals. The requirements may be related to either speed, accuracy, precision, specificity and the requirements of the samples (Food Chemistry for Nutrition Laboratory Manual, 2013). In order to achieve adequate precision ‘Standard Analytical Methods should be used as reference methods.’ The samples food matrix is also taken into account when considering the type of testing method; within the food industry they also consider their main aim and what component they are investigating. The proximate analysis is generally regarded as a general analysis because the analysis is undertaken without considering the final form after the experiment (Aurand, Woods, Wells & Marion, 1987).
  5. 5. 4 Proximate analysis is the main way in which food composition is reported. This gives it relevance for the food industry as it can provide comparisons between different foods. Comparisons can be made between ‘nutritive value, legal aspects of blending of various foods in the industry,’ It is different from an ‘ultimate’ analysis which is used to determine a specific element or compound present in the food, rather than the estimation of a certain component involved in performing a proximate analysis (Food Chemistry for Nutrition Laboratory Manual, 2013). Total moisture and solids content of the sample was determined using the air oven method. Oven methods are popular in the food industry, with various oven methods being approved by the AOAC International. The simplicity of the method and the numerous samples which can be analysed simultaneously has contributed to the methods popularity (Nielson, 2010). However, different ovens will yield different amounts of moisture. A fan forced oven will yield a better result than a vacuum oven. fan forced ovens have the least variation of heat throughout the oven, this is because the fan forces the air movement down and throughout the ovens cavity, it is common for there to be less than 1°C difference throughout the oven. In a vacuum oven there is often a wider temperature spread throughout the cavity, this is due to the glass door acting as a heat sink (Nielson, 2010). It is also very important during sample collection and handling that precautions are made to ensure inadvertent moisture losses or gains do not occur. The financial gain of using water as filler in foods means that moisture content is important for manufacturers to analyse. The total solids are the matter which is left after moisture removal. The moisture content of dried milk, such as the whole milk used in this experiment, is valuable for preservation and quality as it affects the stability of the product (Nielson, 2010). Total fat content was determined using the Mojonnier method. The principle behind this method is that fat is extracted using a mixture of ethyl ether and petroleum ether. Petroleum decreases the solubility of the water during the ether phase and petroleum ether
  6. 6. 5 serves as a lipid solvent. The extract is then dried and expressed as a percentage of fat by weight. Ammonia and ethanol are also used. The ammonia reduces the viscosity of the product by dissolving the casein and neutralising its acidity. The ethanol is important for aiding in the separation during the ether-water phase and it also prevents the milk and ether from forming a gel. Due to the sample being a dairy based sample; ammonium hydroxide was needed to break the covalent and ionic bound lipids so that they could be extracted. Dairy products need to undergo this procedure during lipid extraction due to their tightly bound lipids to proteins and carbohydrates, making the use of simply non-polar solvents inadequate (Nielson, 2003). The Kjeldahl method was employed to determine the percentage of nitrogen in the sample, which is used via the conversion factor to discover the amount of crude protein. The conversion factor is based on assuming a ratio of protein to nitrogen depending on the food group being analysed. In the digestion step of the method the nitrogen is converted into ammonium using a catalyst and concentrated sulphuric acid at a high temperature. The temperature must not exceed 400°C otherwise volatile compounds may be lost. During distillation, the digested sample becomes alkaline through the use of NaOH. Next the nitrogen is distilled and then the resulting NH3 is trapped in a boric acid solution. The following titration with HCL will determine the amount of ammonia nitrogen in this solution and a colour change can be observed. The conversion factor used in this experiment was 100/15.67 to give 6.38 because milk and dairy products contain 15.67% nitrogen (Food Chemistry for Nutrition Laboratory Manual, 2013). The ash content of the sample refers to the inorganic residue that remains after incineration in a muffle furnace causing oxidation. The ash is representative of all the minerals contained within the powder sample, which is why it is important for analysing food. It is also the first step for specific elemental analysis. Ash content from plant sources is variable and the ability to determine mineral content of food is essential for a nutritional evaluation. A disadvantage of this experiment is that there can be a loss of the volatile elements and
  7. 7. 6 interactions between mineral components and crucibles (Food Chemistry for Nutrition Laboratory Manual, 2013).
  8. 8. 7 Materials and Methods Total Moisture and Total Solids. Air-oven Method Materials  Air oven  Aluminium moisture dishes  Tongs  Desiccator Three aluminium moisture dishes with cover slips were carefully weighed to be approximately 2g of sample in each dish. The weights were taken with and without the lids. The samples were placed in an air oven set at 105°C overnight. The lids are placed beneath the dishes during this process. After being cooled, the samples were weighed again. Determination of Ash Muffle Furnace Materials  3 cubicles  Muffle furnace  Bunsen burner  Desiccator  Whole Milk Powder sample Three crucibles were placed in a muffle furnace set at 525-550°C for an hour. The crucibles were then removed using forceps and weighed once they had cooled down. Precisely 10g of sample was placed into each crucible and they were charred using a Bunsen burner. They were then transferred to the muffle furnace and ashed for 4-5hours at 525-550°C. Following this, the dishes were removed, cooled using a desiccator and weighed. They crucibles are returned to the furnace for a further hour, taken out to cool for another hour and then the
  9. 9. 8 ash content remaining in the crucibles is the final ash content of the sample. The sample can be further used in calcium determination so should be saved. Determination of Nitrogen and Crude Protein Kjedahl Method Materials  Distillation unit  Titration materials  Whole milk powder sample  H2SO4  Block digestor unit- technician only  Kjeldahl digestion flask  conical flask (2)  HCL  distilling unit  NaOH Step 1: Digestion -conversion of amine nitrogen to ammonium ions carried out by Laboratory Technician The method involves 0.5-1g sample being placed in a digestion tube. Two Kjeltabs and 25mL of concentrated H2SO4 is then added to the sample. A blank containing no sample but all reagents is carried out simultaneously. The samples are then digested at low temperatures with steady increases in temperature; this is done using a block digestor unit. This is continued until the sample is clear or reaches 420°C. This can be a timely process, depending on the type of samples being used. Removal of the tubes from the heating unit must be done carefully, the water aspirator should be about half on and the exhaust manifold should be left in place. Cool until the highest point of the tubes is touchable. 70mL of distilled water to each tube should be added followed by a gently shake. At this stage, it should be observed that all solids have been dissolved.
  10. 10. 9 Step 2: Distillation and Titration Place 50mL of boric acid into a 250mL conical flask. Set the distilling unit on automatic and connect a tube to the unit, there should be a plastic hose inside the tube. Addition of 70mL of NaOH will be automatically carried out and after this the receiver conical flash containing the boric acid should be elevated. Contamination is likely to occur at this stage so the glass outlet tube should not be handles, but rather hold it via the plastic tubing. After the door is closed distillation will begin automatically. A beeping sound will indicate when the distillation process has been completed. Transfer the materials to the titration apparatus and being to titrate the sample with 0.10M of HCL until it reaches a grey-mauve point. This process is duplicated. Determination of fat content Materials  Dry Mojonnier tube  Water bath  Aluminium fat dish  Distilled water  petroleum ether  diethyl ether  fume hood  hot plate  petroleum Monjonnier Method-performed in triplicate Preparation of Dairy Products The preparation of Dairy Products method was used due to the sample category. A sample between 0.3 and 0.7g was extracted fat was placed in a dry Mojonnier tube. This particular experiment used 2.0023g, which was diluted with water to make 10mL. The sample had a further 2mL of ammonium hydroxide added and this was mixed in the lower bulb. The
  11. 11. 10 sample was then placed in a 60°C water bath for 5mins and swirled intermittently. After cooling, 2-4 drops of phenolphthalein was added and then 10mL of ethanol. The backwards and forwards motion between the sections of the mojonnier tube allowed for satisfactory mixing. 25mL of diethyl ether is then added followed by a thorough mixing. Mojonnier fat extraction procedure (all samples) The last ether to be added is 25mL of petroleum ether. It is very important that all ethers are added in the correct order. The petroleum ether is also useful in rinsing the neck of the tube. The sample must be rocked and placed in the centrifuge at 600rpm for 2 minutes. A small amount of water can be used to raise the level of liquid to the upper junction of the tube. Cautiously decant as much organic solvent as possible into the pre-weighed aluminium fat dish, use a fume hood during this part of the procedure. The aluminium fat dish should then be placed on the hot plate at a temperature below 40°C and the solvents will evaporate from the dish. This process was repeated with the only variables being the amount of reagents; 5mL of ethanol, 15mL of diethyl ether and 15mL of petroleum. The same aluminium dish is used and the heating and evaporation is repeated as for the 1st fat extraction. The oven was set at 100°C for 5-10 minutes and completely dried. Once cooled the aluminium dishes were placed a desiccator and weighed. This method was performed in triplicate. Determination of Calcium Dye Binding Assay for Calcium Materials  Stock standard solution  Calcuim carbonate  Beaker (100mL)  6M HCL  volumetric flask (100mL)  HCL  Ethanolamine  8-hydroxyquioline
  12. 12. 11  Test tubes  Distilled water  Hot plate  Samples from previous experiment  spectrophometer Preparation of Ash Approximately 0.100g of ash from the determination of ash experiment is placed into a 100mL beaker, an additional 15mL of HCL and 50mL of distilled water is added and boiled using a hot plate. The remaining solution was filtered into a 100mL volumetric flask. 5mL of HCL was used to rinse the beaker. After cooling, the solution was brought up to volume using distilled water. Preparation of stock standard solution (5mmol) - This section was undertaken by an experienced lab technician The solution was created using calcium carbonate (CaCO3), put into a 100mL beaker. 20mL of 6M HCL was added and dissolved. The solution that poured into a 100mL volumetric flask and the beaker was washed using distilled water. Dye binding assay 90ul of each sample was placed into labelled test tubes. Four standards using the pre- prepared stock and distilled water were added in with the samples. Two blanks were also created using 90ul of distilled water. 2.925ml of ethanolamine buffer was mixed in with each tube and mixed for 25 seconds. 1.125ml of reagent B was added to all the tubes and mixed well then set aside for two minutes. The absorbance’s at 550nm in the spectrophometer and were undertaken for all the samples, using the blanks as zero references and a standard curve was plotted.
  13. 13. 12 Results and Discussion Summary of results Components % of each component Actual value (%) Standard Deviation (SD) Coefficient Variance (CV) (%) Relative error (RE) (%) accuracy level Precision Level Crude Fat 27.2936 26.28 8.69 31.84 3.84 Reasonable Low Carbohydrate 40.94 40.51 12.7 na 1.06 High Low Total Moisture 2.0334 3.21 0.62 30.54 36.76 Very low low Total Solid 97.9665 96.9 0.62 0.63 1.22 Low Low Ash (total minerals) 5.81 5.8 0.04 0.69 0.00 Very high Very high Nitrogen 3.7523 3.92 0.13 3.47 1.57 Reasonably high Reasonably high Crude Protein 23.9401 24.31 0.83 3.47 1.52 Satisfactory low Calcium 764/100g 980/100g 11.04 1.44 22.04 Low High The crude fat component yielded a result which corresponds with a low level of precision and a reasonably low level of accuracy. The amount of crude fat was determined using the Mojonnier method, which has been proven to provide the best results for measuring the fat content in dairy products. Precision is related to the amount of statistical variation and accuracy is related to how near the measurement is to the accepted true value. In this case the true value for crude fat is reasonably close to that of the actual value taken from the Fonterra Certificate of Analysis. As a Coefficient of variance (CV) of no more than 4% is acceptable for food analysis, this crude sample exhibited an overwhelmingly low precision level with a CV of 31.84%. This was most likely due to the fact that during the Mojonnier fat extraction procedure some of the non-fat components were poured into the aluminium fat dish. It should only have been the organic solvent being decanted into the dish. This is an example of an operational and personal error. The standard error can provide an additional examination of the precision of the results. The standard error value of 5.02 represents the low level of precision further. There was also a
  14. 14. 13 difference of -16.9574 between two of the values. I would recommend this experiment be repeated. Table: Accuracy and precision when outlier is removed Component Average Standard Deviation Coefficient of variance (%) Relative error (RV)(%) Standard error (SE) Fat (3 triplicates) 27.2936 8.685208305 31.8214098 3.856925419 5.014407 Fat (outlier removed) 22.5109 3.689541763 16.39002333 -14.34208524 2.6089 When you remove the outlier you can see a remarkable difference in standard deviation, CV, RE and SE. The standard deviation and standard error exemplify less of a spread of experimental values without the outlier. This represents a higher level of precision, yet still about 4% CV and therefore still not precise. The CV of 16.39 is still high, yet much closer than that of the CV for the original three replicates, showing a higher level of precision however this is still too high to be considered precise. The relative error nevertheless is higher which indicates that this still not an accurate sample regardless of the exemption of the outlier. This indicates that although the outlier exhibited the most variation, it is not the only sample which exhibited experimental errors and therefore all three triplicates should be repeated with a higher level of accuracy and precision. Determination of Total Moisture and Total Solids The total moisture was determined using the total amount of moisture measured from the volatile matter that was lost when the sample was treated with heat. The outstanding sample is the total solid content for the sample being tested. The most accurate method for determination of total moisture and total solid is the use of a vacuum desiccator, however this is a lengthy process which utilises materials not available in the laboratory and therefore the air oven method was utilised. The air oven method is limited by the way the
  15. 15. 14 heat is distributed within the oven, leaving cold spots which may have also contributed to the error (Food Chemistry for Nutrition Laboratory Manual, 2013). Components % of each component Actual value (%) Standard Deviation (SD) Coefficient Variance (CV) (%) Relative error (RE) (%) accuracy level Precision Level Total Moisture 2.0334 3.21 0.62 30.54 36.76 Reasonably high low Total Solid 97.9665 96.9 0.62 0.63 1.22 Reasonably high Reasonably high Due to the dehydrated nature of the product the method used a different dying temperature for longer, yet the moisture is still expected to be low due to the dry nature of the product. The results obtained exemplified a low level of precision for total moisture. The CV was 30.54% which indicates a very low level of precision and a wide SD of 0.62. This represents a decent amount of dispersal exists from the average. The value 2.03% obtained from the experiment was closely aligned with that of the true value of 3.1%, with a difference of 1.18 indicating that there is a reasonably high level of accuracy. For total solids there was a slight difference between the actual true value and the % component from the experiment. Therefore the level of accuracy was reasonably high. The CV was also reasonably low at 0.63 which would indicate a reasonably high level of precision. The differences between the components and the true value are both below 1.19% difference and therefore the accuracy is not that low, but still reasonably low. This represents that it is likely that some experimental errors occurred. These may have been operational or personal errors or contamination may have occurred.
  16. 16. 15 Determination of Ash Components % of each component Actual value (%) Standard Deviation (SD) Coefficient Variance (CV) (%) Relative error (RE) (%) Accuracy level Precision Level Ash (total minerals) 5.81 5.8 0.04 0.69 0.00 Very high Very high The determination of the ash component yielded very high accuracy and precision. Although it is perfectly accurate, it is not perfectly precision which may be due to some experimental error. During the experiment some of the ash was lost the samples also ignited during the charring process. Determination of Crude Protein Components % of each component Actual value (%) Standard Deviation (SD) Coefficient Variance (CV) (%) Relative error (RE) (%) Accuracy level Precision Level Crude Protein 23.9401 24.31 0.83 3.47 1.52 High High The % of component and actual value were very close and therefore the results were accurate. The CV is below the 4% and therefore this can experiments results can be assumed to have good precision. The low standard deviation supports this. However, this experimental method cannot account for all the nitrogen present in the sample, this method only counts the amount of reduced nitrogen present. In this experiment the milk powder sample containing nitrogen-containing organic compounds was subjected to intense heat in concentrated sulphuric acid which liberates the nitrogen in the form of ammonium sulphate (Lab book, 2013). Selenium was used as a catalyst in this experiment. The use of selenium as a catalyst uses ‘clear time’ to decide when digestion has occurred. The problem with this method is that clear time is not an accurate measure of if digestion has occurred and this is an issue because clear time may occur a long time before decomposition has occurred. Selenium also
  17. 17. 16 has been shown to cause loss of nitrogen, which has a linear relationship with the length of digestion time (Kirk, 1950). This may have contributed to the experimental error. Determination of Calcium Components % of each component Actual value (%) Standard Deviation (SD) Coefficient Variance (CV) (%) Relative error (RE) (%) accuracy level Precision Level Calcium 764/100g 980/100g 11.04 1.44 22.04 Low High The sample was precise with a CV of 1.44, below 4%. However, it showed inaccuracy as the expected value of 980/100mg was very different from the % of Calcium in the sample. It is possible to have good precision and poor accuracy. Human error is most likely the reason for low accuracy, in one of the samples the sample was diluted with too much water and also the ash was split there is also the possibility that the tubes weren’t mixed properly after adding the reagents. These may have contributed to the results and caused the low level of accuracy. The method used was the Dye Binding Assay for Calcuim, which is been validated against atomic absorption spectrometry (AAC). However, this method cannot elicit the precise and accurate results that the AAC method can elicit and this may also have contributed to the errors in the results and provided a limitation of the experiment (Food Chemistry for Nutrition Laboratory Manual, 2013). Determination of Carbohydrates Components % of each component Actual value (%) Standard Deviation (SD) Coefficient Variance (CV) (%) Relative error (RE) (%) accuracy level Precision Level Carbohydrate 40.94 40.51 12.7 31.02 1.06 High Low The following formula was used to calculate the average % of carbohydrate in the sample: (ash + protein + moisture)-100=40.94 (average).
  18. 18. 17 The average was close to the actual (true) value and therefore there was a high level of accuracy but precision was low, as indicated by the CV and SD. The low precision can be accounted for by the accumulation of experimental error across the experiments for ash, protein and moisture.
  19. 19. 18 Conclusion The Mojonnier method provided a crude fat value which showed high level of precision and a reasonable amount of accuracy. The CV was much greater than 4%, yet after the main outlier was accounted for there was still a low level of precision and the standard error supported this. There were both low levels of accuracy and precision in regards to total solids and total moisture. The moisture component showed the lowest level of accuracy with a CV of 30.54%. The air oven method was used, which is considered inferior to the use of a vacuum desiccator. The total moisture content was 2.03% which showed a large amount of dissimilarity from the expected value and therefore a reasonably low level of accuracy. The solid component showed both high accuracy and precision. The carbohydrate was detected using the sum of percentages of moisture, crude protein, crude fat and ash and subtracting it from a hundred. This method is subject to numerous errors which could have occurred during the experiments to discover the components which are subtracted from a hundred per cent. The carbohydrate produced results which had a high level of accuracy but a low level of precision. Calcium was determined using the Dye Binding Assay of Calcium method. This method has not been accredited as being the most precise measurement but was used due to constraints used to determine the method. The AAC method is expensive and cost was a constraint. The CV and SD attributed to a high level of precision. The disparity between the percentage of the component and the actual true value however determined that the level of accuracy was low. The percentage of crude protein in the sample was determined by the Kjeldahl method. The method determines the total amount of reduced nitrogen present in an organic nitrogen- containing sample. The sample was tested by this method and the results showed a high level of accuracy and precision. The expected value and the percentage found from the experiment were very similar and the CV was below 4%.
  20. 20. 19 The determination of ash was conducted through the Dry Ashing Method. There was a very high level of accuracy as the true value and the percentage achieved in the experiment were extremely similar and the CV was well below 4%.
  21. 21. 20 References P L. Kirk. (1950). Kjeldahl Method for Total Nitrogen. Analytical Chemistry195022 (2), 354- 358 Retrieved from Nielsen, S.S. (2003). Food Analysis Laboratory Manual. New York, USA: Kluwer Academic/Plenum Publishers ojonnier+method&hl=en&sa=X&ei=5uSFUd3sEMm4iAeck4CgAw&redir_esc=y Nielson, S. S. (2010). Food Analysis. (4th ed.). New York, USA: Springer false Nielson, S. S. (2010). Food Analysis. (4th ed.). New York, USA: Springer Retrieved from R91MDsiEC&pg=PA87&dq=moisture+content+of+food&hl=en&sa=X&ei=qeCFUYyTG4aFiAfX 94GYBg&sqi=2&ved=0CC0Q6AEwAA#v=onepage&q=moisture%20content%20of%20food&f =false Aurand, L. W., Woods, A., Wells & Marion, R (2009). Food composition and analysis. Food and Agriculture Organisation of the United Nations. Retrieved from dq=Food+composition+and+analysis&hl=en&sa=X&ei=H4- RUYv8J4aEiAfB1YDYCQ&redir_esc=y Food Chemistry for Nutrition Laboratory Manual. (2013) 151.231 Institute of Food, Nutrition and Human Health, Massey University: Albany.
  22. 22. Appendix Determination of Moisture and Total Solids Wet Basis Moisture % protein % fat % carbohydrate % ash % 2.0334 23.9401 27.2936 40.94 5.81 The content of total solids is 98% Dry basis (based on the total solids content) Protein % = 123.9401 x 100/98 = 126.469% Fat % = 27.2936x 100/98 = 27.85% Carbohydrate % = 40.94x 100/98 = 41.775% Ash % = 5.81 x 100/98 = 5.9286% protein % fat % carbohydrate % ash % 126.469 27.85 41.775 5.9286 Dish + lid (g) Sample (g) Dish + lid + sample after drying (g) TM (%) TS(%) 1 29.0195 1.8682 30.8527 1.8734 98.1265 2 28.9464 1.8739 30.7694 2.7162 97.2838 3 30.4670 1.9593 32.3967 1.5107 98.4893 Averages 2.0334 97.9665
  23. 23. 1 Calculation for Total Moisture formula: – % TM = % of total moisture W1 = weight in grams of moisture dish + lid W2 = weight (g) of moisture dish + lid + sample (before drying) W3 = weight (g) of moisture dish + lid + sample (after drying) Calculation for Total solids formula: Example Calculation – – 29.0195+1.8682=30.8877 (0.035/1.8682)x100 =1.8734 %TM=1.9% Total solid example calculation: = 98.1265 %
  24. 24. 2 Determination of Calcium Sample (g) Absorbances Ash weight from food sample (g) Ash Used (g) Amount of Calcium in Ash (mg) Calcium Content in Original Sample (mg/100g) 1 9.64 0.56 0.56 0.1077 14.0612 758 2 9.64 0.56 0.56 0.1214 15.8349 758 3 9.64 0.56 0.56 0.1179 15.7737 777 Average 764 Calcium Calculation Formula (mg/g) X = Calcium content from graph (mg) Ar = Ash weight from food sample (g) Aw = Ash weight used for calcium analysis in 100mL volume (g) F = Weight of food sample used for ash determination (g) Example calculation: = 7.77196 mg/g or 776.90 mg/100g
  25. 25. 3 Calcium standard curve Tube stock standard solution (ml) H2O (ml) Dilution factor CaCO3 concentration (mM) Ca ++ concentration (mg/100 mL) Examples: Absorbance at 550nm 1 4 0 0 5 20 1.086 2 2 2 2 2.5 10 0.639 3 1 3 4 1.25 5 0.303 4 0.5 3.5 8 0.625 2.5 0.064 Sample g ash/100mL Abs mg Ca/100 mL mg Ca/g powder mg Ca/100 g powder 1 0.1077 0.949 14.0612 7.5814 758.14 2 0.1214 1.065 15.8349 7.5742 757.42 3 0.1179 1.061 15.7737 7.7690 776.90 764.15 11.04 y = 0.0566x - 0.0077 R² = 0.9769 0 0.2 0.4 0.6 0.8 1 1.2 0 5 10 15 20 25 Absat550nm mg Ca++/100 mL Ca standard curve Standard Solutions Results Absorbance of Samples Average mg calcium/100g powder Standard Deviation
  26. 26. 4 Determination of Protein & Nitrogen Sample after digestion (g) HCl (M) HCI (mL) Nitrogen (%) Crude Protein (%) 1 0.4895 0.1067 12.60 3.8451 24.5319 2 0.4939 0.1067 12.10 3.6596 23.3485 Average 3.7523 23.9401 Nitrogen Content percentage calculation formula: % Protein = % nitrogen x 6.38 6.38 Because this is the conversion factor for dairy products and the sample in this experiment is whole milk powder. Example calculation: = 3.8451 % % Protein = 3.8451 6.38 = 24.5319
  27. 27. 5 Determination of Crude Fat Weight of Original Sample (g) Weight of Empty Fat Dish (g) Weight of dish + Fat after Extraction (g) Crude Fat Content (%) 1 1.5099 19.9168 20.2173 19.9020 2 2.0023 18.2948 18.7977 25.1198 3 1.9984 18.0314 18.7680 36.8594 Average 27.2936 Crude Fat Calculation formula: W₁ = weight of empty flask (g) W₂ = weight of flask and fat (g) W₃ = weight of sample taken (g) Example calculation: – = 19.9019% =19.9020% when rounded up.
  28. 28. 6 Determination of Ash Empty crucible (g) W1 Original Sample (g) W3 Weight After Ashing (g) Ash Content 1 19.4488 9.2962 19.9866 5.7851 2 24.4392 9.6387 24.9963 5.7798 3 23.1293 9.9971 23.7174 5.8556 Average 5.8068 Calculation for Ash Content: w1 = tare weight of crucible (g) w2 = weight after ashing (g) w3 = original sample weight (g) Example calculation: – = 5.7851 %
  29. 29. 7 Precision and accuracy calculations: Coefficient of Variance (CV) example calculation: Example: = 31.84% % Relative Error formula: – Example calculation for fat: – =3.84 Standard Error formula: √ Example calculation for fat: √ =5.014407
  30. 30. 8