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transcript
06165605
Lab Report: Proximate Analysis
151.231 Food Chemistry for Nutrition
Jessica Woods- 06165606
5/24/2013
Dr. Sung Je Lee
1
Contents Abstract ............................................................................................................................................... 2
Introduction ........................................................................................................................................ 3
Materials and Methods ....................................................................................................................... 7
Conclusion ......................................................................................................................................... 18
References ........................................................................................................................................ 20
Appendix ............................................................................................................................................. 0
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.
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).
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
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
6
interactions between mineral components and crucibles (Food Chemistry for Nutrition
Laboratory Manual, 2013).
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
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.
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
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
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.
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
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
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.
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
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).
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.
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%.
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%.
20
References
P L. Kirk. (1950). Kjeldahl Method for Total Nitrogen. Analytical Chemistry195022 (2), 354-
358 Retrieved from
http://pubs.acs.org.ezproxy.massey.ac.nz/doi/pdf/10.1021/ac60038a038
Nielsen, S.S. (2003). Food Analysis Laboratory Manual. New York, USA: Kluwer
Academic/Plenum Publishers
http://books.google.co.nz.ezproxy.massey.ac.nz/books?id=nw7LC7UlsYUC&pg=PA34&dq=M
ojonnier+method&hl=en&sa=X&ei=5uSFUd3sEMm4iAeck4CgAw&redir_esc=y
Nielson, S. S. (2010). Food Analysis. (4th ed.). New York, USA: Springer
http://books.google.co.nz/books?id=TZHlxAcANjUC&printsec=frontcover#v=onepage&q&f=
false
Nielson, S. S. (2010). Food Analysis. (4th ed.). New York, USA: Springer Retrieved from
http://books.google.co.nz/books?id=JM-
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
http://books.google.co.nz/books?id=WeNJAAAAYAAJ&q=Food+composition+and+analysis&
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.
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
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 %
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
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
Ab
s a
t 5
50
nm
mg Ca++/100 mL
Ca standard curve
Standard Solutions Results
Absorbance of Samples
Average mg calcium/100g powder
Standard Deviation
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
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.
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 %
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
8