This document describes the development of a halal testing method to differentiate gelatin from different sources using reverse phase high performance liquid chromatography (RP-HPLC) combined with principal component analysis. It discusses gelatin production processes, amino acid analysis methods, and the validation of the developed HPLC method. The method was validated for specificity, linearity, precision, accuracy, detection and quantitation limits to differentiate bovine, porcine, fish and other animal sources of gelatin.

1. DEVELOPMENT OF HALAL TESTING METHOD TO
DIFFERENTIATE THE GELATIN FROM DIFFERENT
SOURCES USING AN RP-HPLC INCORPORATED
WITH PRINCIPAL COMPONENT ANALYSIS
Presented by;
AZILAWATI MOHD ISMAIL
FOOD TECHNOLOGIST
MALAYSIA HALAL ANALYSIS CENTRE (MYHAC),
HALAL HUB DIVISION, JAKIM

2. WHAT IS HALAL? (LAWFUL)
 Halal is an Arabic term meaning “lawful” or “permissible” according to Islamic law (shariah
compliant)
 Thoyyiba– good or wholesome (quality, safety, hygiene, clean, nutritious, secure)
 Halal products must not involve the use of haram (prohibited) ingredients and are not
harmful or intended for harmful use (toyyiban compliant).
 The products should comply with following requirements:
 Does not contain elements not allowed according to Islamic law
 Has not been in contact with prohibited/not allowed substances during production,
transportation and storage
 Is not stored in facilities or premises or transported using transportation vehicles
which are not allowed

3.  Unlawful(haram) things are prohibited to everyone alike.
 Basically, all food products are permitted except those that are explicitly forbidden
according to islamic dietary laws including:
i. Swine/pork/porcine and its by-products
ii. Alcohol and intoxicants
iii. Blood and blood by-products
iv. Meat from cadavers and meat of animals that have not been slaughtered according
to islamic rules
v. Foods contaminated with any of the above products
WHAT IS HARAM? (UNLAWFUL)

4. MASHBOOH
“HALAL IS CLEAR AND HARAM IS CLEAR;
IN BETWEEN THESE TWO ARE CERTAIN THINGS THAT ARE SHUBHAH (SUSPECTED).
MANY PEOPLE MAY NOT KNOW WHETHER THOSE ITEMS ARE HALAL OR HARAM.
WHOSOEVER LEAVES THEM, HE IS INNOCENT TOWARDS HIS RELIGION AND HIS CONSCIENCE.
HE IS, THEREFORE, SAFE.
ANYONE WHO GETS INVOLVED IN ANY OF THESE SUSPECTED ITEMS, HE MAY FALL INTO THE UNLAWFUL
AND THE PROHIBITION.
THIS CASE IS SIMILAR TO THE ONE WHO WISHES TO RAISE HIS ANIMALS NEXT TO A RESTRICTED AREA,
HE MAY STEP INTO IT.
INDEED FOR EVERY LANDLORD THERE IS A RESTRICTED AREA.
INDEED THE RESTRICTIONS OF ALLAH ARE THE UNLAWFUL (HARAM).”
 HADITH BUKHARI AND MUSLIM

5. 3 MAIN COMPONENTS PRIOR TO GET
HALAL PRODUCTS CERTIFIED
DOCUMENTATION
SUBMISSION
AUDIT FIELD
SAMPLING FOR
LABORATORY
ANALYSIS

6. HALAL TESTING METHODS
 ALCOHOL
 FAT AND OIL - EMULSIFIER
 PROTEIN AND GELATIN
 MEAT SPECIATION
 GENETICALLY MODIFIED ORGANISM
 BRISTLE AND LEATHER

7. CHALLENGES IN HALAL PRODUCTS TESTING
i. Lack of sensitive test methods
ii. High cost for method development
iii. Products are complex and/or highly processed
iv. Low traceability as limited amount of halal/non-Halal ingredient is
used in certain products
v. Economically Motivated Adulteration products (EMA) – involving
the replacement of high cost ingredients with lower grade and
cheaper substitues

8.  Gelatin is a product of thermal denaturation or disintegration of insoluble collagen by
partial acid or alkaline hydrolysis process.
 Gelatin is only derived from sources rich in Type I collagen that generally contains no
Cys.
 Consist of high molecular weight polypeptide with repetition of Gly-Pro-Hyp
 A mixture of water-soluble protein (85 to 92 % of protein , mineral salts and moisture)
 Type of sources – mainly derived from bones, hides, skin and cartilages
 Bovine
 Porcine
 Marine - cold and warm water fish (scale and bone)
 Poultry - chicken
 Others - donkeys and horses
GELATIN

9. DENATURATION HYDROLYSIS PROCESS

10. GELATIN
 Raw materials for industrial-scale manufacture are slaughter by-products and
byproduct of the fish-processing industry, available in sufficient quantities at an
economical price
 Animals that have been officially declared fit for human consumption.
 2 main process:
i. Acid process
 Limited to the tissue of younger animals
(calf skin : 2 – 3 years , pig skin : up to 18 months)
 The collagen have a lesser degree of covalent bonding
 Type A gelatin – IEP : 7 – 9, nitrogen content : 18.5%

11. ii. Alkaline process
 Bovine hides or bones
 Not suitable for pig skin because it leads to
saponification of the fat content, making further
processing very difficult
 Type B gelatin – IEP : 4.6 – 5.4,
 nitrogen content : 18 %
 Fish gelatin can be conditioned using both acid and
alkali process.
GELATIN

12.  2 MAIN FUNCTIONAL PROPERTIES:
 GELLING PROPERTIES
 SURFACES EFFECTS PROPERTIES
 APPLICATION AREA:
 FOOD AND BEVERAGE , 29%
 NEUTRACEUTICALS, 25.80%
 PHARMACEUTICALS, 21%
 PHOTOGRAPHY, 13.50%
 COSMETICS, 5.50%
 OTHERS, 6 %
GELATIN
Food and
beverage, 29%
Neutraceuticals,
25.80%
Pharmaceuticals,
21%
Photography,
13.50%
Cosmetics,
5.50%
Others,
6.10%

13. AMINO ACIDS
ANALYSIS

14. AMINO ACIDS
 Containing an amine group, a carboxylic acid group, and a side-chain that
is specific to each amino acid.
 Basic elements are carbon, hydrogen, oxygen, and nitrogen
 The side-chain make an amino acid a weak acid or a weak base, a
hydrophilic if the side-chain is polar or a hydrophobic if it is non polar.
 Serve as the building blocks of proteins
 20 amino acids are naturally incorporated into polypeptides and are called
proteinogenic or standard amino acids and are encoded by the universal
genetic code.
 9 standard amino acids are called "essential" for humans

15. SAMPLE WEIGHT, 0.18 G
MIX WITH 5ML OF 6N HCL
(HEAT AT 110OC, 25 HRS)
COOLING DOWN THE MIXTURE
ADD IN 4 ML OF 2.5MM AABA (INTERNAL STD)
DILUTE TO 100 ML WITH DISTILLED WATER
FILTER 2 ML OF THE TEST SOLUTION USING
0.45 µM CELLULOSE ACETATE MEMBRANE
TAKE 10 µL OF THE ALIQUOT FOR DERIVATIZATION
(70 UL OF BORATE BUFFER &
20 UL OF ACCQ REAGENT)
HEAT SAMPLE AT 550C, FOR 10 MIN
INJECT 10 UL OF SAMPLE TO HPLC
EQUIPPED WITH FLUORESCENCE DETECTOR
AMINO ACID ANALYSIS
15
 INSTRUMENT CONDITIONS :
 Equipment - Waters® Alliance System (2695 separation module)
Waters® 2475 Multi-λ Fluorescence detector
(250 nm excitation, 395 nm emissions)
 HPLC Column – Waters AccQ•Tag amino acids analysis
( 3.9 mm X 150 mm i.d, 4 µm)
 Column temperature – 36OC
 Injection volume – 10 µl
 Flow rate – 1 ml/min
Gradient Elution : (A) AccQ•TagTM Eluent A, concentrate
(B) Deionised water
(C) Acetonitrile
 Dilution factor – 0.01
 Data acquisition – Waters EmpowerTM Pro software

16. DIPEPTIDE
HCl

18. OTHER DERIVATIZATION REAGENTS
Derivative reagents Effects
Phenylisothiocyanate (PITC) Rapid with high performance analysis but consists of multiple steps, time
consuming
Orthophthalaldehyde (OPA) Reacts only on primary amino acids
Dabsyl chloride Has large interfering peaks due to excess reagent
Dansyl chloride & fluoreny methy
chloroformate (FMOC-CL)
Can form multiple derivatives with selected amino acids
Accq fluor reagent Reacts with primary and secondary amines in a few seconds with little matrix
interference.
Both AMQ and AQC-derivatives amines have the same excitation maximum but
different in emission maximum which allowed for the selective detection of the
AQC-derivatives in the presence of a large excess of AMQ.
The optimized chromatographic conditions can be evaluated at sub-picomolar
detection limits within sub-microgram sample levels

19. Detection on primary and secondary amines

21. METHOD VALIDATION AND
MEASUREMENT OF
UNCERTAINTY
METHOD
DEVELOPMENT

22. Method is Specific
• Difference in RT <0.2
• Difference in % peak area
<1.5%
• Rs > 1.5 (most AA)

23. Amino acid Calibration in aqueous solution r2
Calibration in matrix solution r2
Hyp Y = 0.0033x - 0.0081 1.0000 Y = 0.0030x + 0.0262 0.9990
Asp Y = 0.0030x + 0.0262 0.9999 Y = 0.0026x + 0.0521 1.0000
Ser Y = 0.0045x + 0.0146 1.0000 Y = 0.0042x + 0.0115 1.0000
Glu Y = 0.0031x + 0.0625 0.9977 Y = 0.0031x + 0.0825 0.9999
Gly Y = 0.0049x - 0.0514 0.9973 Y = 0.0042x + 0.0715 0.9996
His Y = 0.0076x - 0.0264 0.9998 Y = 0.0068x + 0.0591 1.0000
Arg Y = 0.0073x - 0.0609 0.9997 Y = 0.0067x + 0.0518 0.9996
Thr Y = 0.0078x + 0.0132 0.9996 Y = 0.0086x - 0.0233 0.9997
Ala Y = 0.0076x - 0.0822 0.9969 Y = 0.0094x - 0.1149 0.9991
Pro Y = 0.0037x + 0.0174 0.9998 Y = 0.0035x + 0.0290 1.0000
Cys Y = 0.0008x + 0.0066 0.9999 Y = 0.0008x + 0.0043 1.0000
Tyr Y = 0.0076x - 0.0245 0.9981 Y = 0.0073x + 0.0026 0.9999
Val Y = 0.0115x + 0.0858 0.9997 Y = 0.0107x + 0.1141 0.9998
Met Y = 0.0112x + 0.0308 0.9994 Y = 0.0111x + 0.0317 0.9990
Lys Y = 0.0045x + 0.0879 0.9981 Y = 0.0053x + 0.0581 0.9988
Ile Y = 0.0160x + 0.1251 0.9996 Y = 0.0137x + 0.2119 1.0000
Leu Y = 0.0180x + 0.0602 0.9994 Y = 0.0180x + 0.0732 0.9996
Phe Y = 0.0212x + 0.0449 0.9998 Y = 0.0218x + 0.0793 1.0000
F-test: Residual variance are not different
t-test: The slopes are not different
23

24. VALIDATION : DETECTION AND
QUANTITATION LIMIT

25.  8 concentrations level (pmol/μl):
37.5, 50, 100, 250, 500, 1000,
1500 & 2000
 result (OLSM method) –
a) Regression accepted
b) non linear curve
c) working range unaccepted
 Action – Discard outliers.
-2.00
-1.50
-1.00
-0.50
0.00
0.50
0 500 1000 1500 2000
Arearatio
Concentration (pmol/ul)
ASP
Upper limit Lower limit yi -ý
OUTLIERS
-0.25
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
0.20
0.25
0 200 400 600 800 1000 1200
Arearatio
Concentration (pmol/ul)
ASP
Upper limit Lower limit yi -ý
 6 concentrations level (pmol/μl):
37.5, 50, 100, 250, 500, & 1000
 result (OLSM method) –
a) Regression accepted
b) Linearity accepted
c) working range accepted
 Action – Develop calibration curve
25

26. Amino acid Calibration equations r2
Hyp Y = 0.00453x - 0.1769 0.98
Asp Y = 0.00257x + 0.0879 0.99
Ser Y = 0.00486x - 0.0531 0.99
Glu Y = 0.0031x + 0.0538 0.99
Gly Y = 0.00635x - 0.2645 0.97
His Y = 0.00936x - 0.2810 0.99
Arg Y = 0.00841x - 0.1206 1.00
Thr Y = 0.00861x - 0.1080 0.99
Ala Y = 0.0071x + 0.0137 0.98
Pro Y = 0.0037x + 0.0061 1.00
Cys Y = 0.0009x - 0.0155 0.99
Tyr Y = 0.0095x - 0.3066 0.98
Val Y = 0.0118x + 0.0236 0.99
Met Y = 0.0125x - 0.1791 0.99
Lys Y = 0.0039x + 0.1709 0.98
Ile Y = 0.0165x + 0.0114 0.99
Leu Y = 0.0184x - 0.0090 0.99
Phe Y = 0.0284x - 1.0510 0.98
y = 0.0026x + 0.0893
r² = 0.985
0.00
0.50
1.00
1.50
2.00
2.50
3.00
-100 100 300 500 700 900 1100
Arearatio
Concentration (pmol/µl)
ASP
Working range : 37.5 – 1000 pmol/μl
26

27.  Method precision : CV < 10%
 r value :
difference between 2 values should be
lower than or equal to r
Method trueness (recovery) : average 99
% determined
: range ≈ 64 – 111 %
: IQC spiking ≈ 250 pmol/µl
27

28. ESTIMATING UNCERTAINTIES FOR
AMINO ACIDS IN GELATIN

29. CHEMOMETRICS

30. ‘The science of relating measurements made on a chemical system or process to the state of
the system via application of mathematical or statistical methods.’
(International Chemometrics Society)
‘The chemical discipline that uses mathematical and statistical methods, (a) to design or select
optimal measurement procedures and experiments, and (b) to provide maximum chemical
information by analyzing chemical data.’
Journal of Chemometrics (Wiley) and
Chemometrics and Intelligent Laboratory Systems (Elsevier).

31. • Was coined by Svante Wold (Swede) and Bruce R. Kowalski (American) in 1972.
• Early applications involving multivariate classification of analytical chemical
datasets.
• Current developments :–
a) involving very complex datasets (metabolomics or proteomics).
b) new application that are biologically driven and emerging a new interface
between chemometrics and bioinformatics
c) forensics (the use of chemical and spectroscopy information to determine
the origins of samples)
d) pharmaceuticals ( multivariate image analysis)
e) chemical engineering
f) thermal analysis (materials)

32. Basic Statistics, Signal Processing, Factorial Design, Calibration, Curve Fitting,
Factor Analysis, Detection, Pattern Recognition and Neural Networks

33. PATTERN RECOGNITION (PR)
Exploratory
Data Analysis
(EDA)
Principal
Components
Analysis (PCA)
Factor Analysis
(FA)
Unsupervised PR
(detect similarities)
Cluster Analysis
Supervised PR
(Classification)
Discriminant
Analysis
SIMCA
PLS
K Nearest
Neighbours
Multiway PR
Tucker3
Models
PARAFAC
Unfolding

34. • Is a subset to an exploratory data analysis (EDA) that aims to determine
underlying information from multivariate raw data.
• It is a technique that will reduce the dimensionality of a data set consisting
of a large number of interrelated variables and transform it to a new set of
uncorrelated variables called principal components (PCs).
• The variations present in the original data were retained as much as possible
to build up groups of orthogonal axes representing the PCs.
• Data pre-treatment such as centering and normalization technique was
performed to facilitate the process of differentiation among samples by
reducing the variation of the variables in the data.

35.  The raw data were imported to Unscrambler X software version 9.7.
 Data matrix (X) is in the form of an (m x n) containing the responses for the n variables in
each of the m samples.
 Concepts in PCA:
i. rank the data matrix - identify the amino acids that are significantly present in all
gelatins (n variables)
ii. PCA transforms the original data matrix into a number of principal components (PCs)
or a new co-ordinate system (axes)
iii. The axes are located in the centre of the data points.
iv. The first PC lies along the direction of the maximum variances of the data while the
second PC lies along the direction of the second highest variances and the process
continues up to certain PCs where the total variances have been accounted.
v. The linear function of new variables constructed by separate PC is uncorrelated and
having an orthogonal properties.
vi. The variation is expressed in percentage under a number of successive PCs.
vii. The remaining percentage number is usually represented by error or noise.

36. • In matrix terms (chemical factors) : X = C.S + E
• In PCA terms : X = T .P + E
X is the original data matrix
S = p is a matrix consisting of the spectra of
each compound ; LoadingsC =T is a matrix consisting of the elution
profiles of each compound; Scores
E is an error matrix (the same size as X)
Each scores matrix consists of a series of column vectors and each loadings
matrix consist a series of row vectors

37. S
A
M
P
L
E
S
,
m
VARIABLES, n
The PCA will decompose the variation of the data matrix (X) into scores (T), loadings (P)
and a residuals matrix (E)

38. i. Eigenvalue - The amount of variation explained by each PC. Expressed as a percentage of the
overall sum of squares of the entire data matrix.
ii. Eigenvector – provides the weight to the new variables and defined the direction on to which
data can be projected.
iii. Hotelling’s T2 ellipse - identify the accepted data points within 95% of confidence limits. These
data points are lying inside the ellipse. The remaining 5% are the rejected data that lie outside the
ellipse
iv. Scores plot - identify the samples groupings, outliers and other strong patterns in the data
v. Loading plot - interprets the relationships among variables that contribute to the effects of
sample grouping in the score plots.
vi. Correlation loadings plot - consisting of two ellipse, explaining the 50% (inner circle) and 100%
(outer circle) of explained variance limits.
vii. Influence plot – measure the distance of each point (sample) from the centre data point (a
grouping data) or the PC model. Detect outliers.
viii. Explained variance plot - measures the distance of variables from its mean value and cause
variation in the data. The variation is expressed in percentage under a number of successive PCs.

40. Porcine
Bovine
Fish
Porcine
Bovine
Fish

43. at 0.1, 1, 5, 10, 30, 40%
(w/w)
Porcine
Bovine
Porcine
Fish
EXPECTATION

44. CONTAMINATION:
0.1%(W/W)

45. CONTAMINATION:
0.1,5,10,30&40%(w/w)
Bovine gelatin
Porcine gelatin
Fish gelatin

46. PUBLICATIONS

47. PUBLICATIONS
Accepted by JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS –
on 8th July 2016
Estimation Of Uncertainty From Method Validation Data:
Application To A Reverse-phase High-performance Liquid Chromatography
Method For The Determination Of Amino Acids In Gelatin Using 6-aminoquinolyl-
N-hydroxysuccinimidyl Carbamate Reagent

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