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Abstract
To protect consumers from non-halal and shubha-halal foods, it is essential to authenticate chicken meat based on its
slaughtering process. The objective of the present study is to authenticate the halalness of chicken meat based on the slaughter
process. Untargeted metabolomics, utilizing UHPLC-HRMS combined with chemometrics, offers a selective and accurate method
for verifying the halal status of chicken meat based on the slaughter process. This approach identified 29 metabolite pr ofiles,
with creatine, carnosine, and 3-methylhistidine being the most prominent metabolites. Principal Component Analysis (PCA)
clearly distinguished the metabolic profiles of chicken meat slaughtered using different methods. Additionally, cluster analysis
effectively grouped chicken meat based on similarities in metabolite profiles. The correlation network revealed that 21 types of
metabolites are interrelated in the halal authentication process. Partial Least Squares Discriminant Analysis (PLS-DA) accurately
identified 13 potential biomarkers for halal authentication, including creatine, betaine, 2-amino-1,3,4-octadecanetriol, L-isoleucine,
L-phenylalanine, L-histidine, L-glutamic acid, L-glutathione, DL-glutamine, taurine, carnosine, and acetyl-L-carnitine. Overall,
untargeted metabolomics combined with UHPLC-HRMS and chemometrics represents a promising method for authenticating the
halal status of chicken meat, distinguishing between halal, non-halal, shubha-halal, and mixtures of halal with non-halal or
shubha-halal meat.
1. Introduction
Halal food, including meat, is important to various stakeholders because it can be consumed by both Muslims and non-Muslims
[1]. Chicken is one of the most widely consumed halal meats. The slaughtering process for chicken meat is categorized into three
types: halal, non-halal, and Shubha [2] Halal slaughter adheres to Sharia principles, involving the cutting of four channels: the
trachea, esophagus, jugular veins, and carotid arteries [3]. In contrast, non-halal chicken meat is not subjected to any cuts.
Shubha slaughter involves cutting only two channels: the trachea and esophagus [4]. There are differing opinions regarding the
status of Shubha slaughter. Some consider it halal, while others deem it non-halal [5]. The economic factors leading to the mixing
of halal chicken meat with non-halal or Shubha meat can be harmful to consumers, causing halal meat to be mislabeled as non-
halal or Shubha. Therefore, an analytical method is needed to authenticate the halal status of chicken meat based on the
slaughter process [6].
Various analytical methods for halal meat authentication have been widely reported. Ali et al.[7] demonstrated that FTIR and
UHPLC-TOF-MS can detect metabolites in both halal and non-halal chicken meat. Zahavi et al[8] explained that FTIR, GC-MS, and
UHPLC can reveal differences in neck-cutting techniques across various broiler chicken meats, affecting metabolite fingerprints.
Maritha et al [9] investigated the metabolite profiles of pork and beef using metabolomics methods. Surat et al.[10] showed that
metabolomics and proteomics can identify pork mixed with tuna meat. While these published methods are effective for
authenticating meat, there is a lack of methods specifically for Shubha meat authentication. Therefore, an alternative method is
needed to authenticate halal, non-halal, and Shubha chicken meat based on the slaughter process[11], [12].
Metabolites are products of gene expression influenced b y environmental factors [13]. Chicken meat, when slaughtered
according to halal, non-halal, and Shubha methods, involves severing a similar number of channels. This variation in the energy
required for metabolite formation leads to distinct metabolite profiles. Metabolite profiles are analyzed using metabolomics [14].
HPLC-HRMS is a powerful instrument for metabolomics, known for its high sensitivity and selectivity in separating
metabolites[15]. Given the complexity of metabolite data, chemometric analysis is essential for accurate authentication. Principal
Component Analysis (PCA) is used to group metabolites based on slaughter methods, distinguishing halal, non-halal, and Shubha
meat. Cluster analysis further refines the classification of metabolite pr operties according to the slaughter process. Partial Least
Squares Discriminant Analysis (PLS-DA) helps in identifying potential markers for determining meat authenticity[16].
Based on the previous description, it is crucial to authenticate the halal status of chicken meat based on the slaughter process to
protect consumers from inadvertently consuming non-halal or Shubha foods, which remain subjects of debate [17], [18].
Chemometric-based metabolomics offers a sensitive and selective method for halal authentication. This approach can detect
metabolite changes resulting from different slaughtering processes [19], [20]. The metabolite markers identified thr ough
chemometric analysis will serve as indicators for authenticating the halal status of chicken meat, distinguishing between halal,

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non-halal, and Shubha types. This research aims not only to safeguard consumers but also to provide a valuable reference for
halal regulators in verifying the halal status of chicken meat based on the slaughter process.
2. Material and Methods
2.1 Chemicals
Methanol, water, formic acid, and acetonitrile for LC-MS grade were all high-performance chemical reagents (Merck, Germany)
and chicken meat from local market.
2.2 Extraction of metabolites from chicken meat.
Chicken meat is slaughtered by certified halal butchers. The slaughter process is carried out using 3 methods, namely halal, non-
halal, and Shubha. Halal slaughter is performed by cutting the traca, esophagus, jugular vein, and carotid artery. Shubha slaughter
is performed by cutting the trace and esophagus. Non-halal meat is not slaughtered. After slaughtering, chicken feathers are first
cleaned using running water, before meat is taken for extraction.
The meat sample (50 mg) was placed in a microcentrifuge tube containing 1 mL of methanol, vortexed for 30 seconds, and
sonicated for 30 minutes at room temperature. The sample was then centrifuged at 1,400 x g for 5 minutes to separate the
supernatant. The supernatant was collected and filter ed using a 0.22 µm PTFE filter . The metabolites were stored in vials at -20°C
before being analyzed. We performed this process on meat slaughtered in accordance with halal, non-halal, Shubha, mixed halal
with non-halal, and mixed halal with Shubha practices.
2.3 Metabolomics analysis using UHPLC-HRMS
The instruments used in the metabolomics approach were UHPLC (Ultra High-Performance Liquid Chromatography) and Q
Exactive (Thermo Scientific, USA) fr om the Advanced Research Laboratory of IPB University. The UHPLC conditions included a
C18 Accusor (Thermo Scientific, USA) 100 x 2.1 mm x 1.5 µm (par ticle size) stationary phase. The mobile phase consisted of
mobile phases A and B. Mobile phase A was 0.1% formic acid in water, and mobile phase B was 0.1% formic acid in methanol.
The gradient for the mobile phase in the metabolomics analysis was as follows: 0–16 minutes: 5% B to 90% B, 17–20 minutes:
90% B, 10% A, 20–25 minutes: 5% B, 95% A. The flow r ate was 0.3 µL/min, the temperature was 40°C, and the injection volume
was 3 µL. The data were read at m/z mass intervals of 66.7-1,000 m/z. Spectral fragments were obtained at a resolution of
17,500 − 75,000 Hz. The obtained metabolite spectra were further matched with Discover Compound data, and the process was
replicated three times.
2.4 Chemometrics analysis
The statistical analysis of the metabolite compounds was conducted using one-way ANOVA with MetaboAnalyst 6.0
(https://www.metaboanalyst.ca/). If the results were significant (P < 0.05), chemometric analysis was performed. The
chemometric analyses conducted included Principal Component Analysis (PCA), cluster analysis, and Partial Least Squares
Discriminant Analysis (PLS-DA) using MetaboAnalyst 6.0 (https://www.metaboanalyst.ca/). Three replicates were set for each
sample.
3. Results and Discussion
3.1 Untargeted metabolomics
Visually, halal-slaughtered meat is whiter and cleaner compared to meat from the Shubha method, while chicken meat
slaughtered non-halal appears darker. Metabolomics analysis identified 100 metabolites. Of these, 29 metabolites had an m/z
value exceeding 70. An m/z value greater than 70 indicates accurate compound detection and helps remove low-concentration
metabolites from complex samples, thereby allowing more metabolites to be detected [21]. Several metabolites were identified
because UHPLC-HRMS is an instrument with excellent sensitivity, capable of separating metabolites into ESI
+
and ESI
−
[22]. The
detection of metabolite separation occurs due to the breakdown of complex compounds into smaller fragments in ESI + and ESI-,

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resulting in small molecules that are easily detected. Metabolites are the result of gene expression in environments with small
molecular weights, making UHPLC-HRMS highly appropriate for metabolomics analysis. Chromatogram results for ESI
+
and ESI
−
are presented in Figs. 1 and 2.
In the untargeted metabolomics analysis, creatine, carnosine, and 3-methylhistidine were the most abundant metabolites in
chicken meat slaughtered using halal, non-halal, Shubha, halal mixed with Shubha, and halal mixed with non-halal methods. The
highest creatine content was found in chicken meat slaughtered using halal, Shubha, and non-halal methods. Creatine levels in
halal-Shubha mixed chicken were higher than in halal-non-halal mixed chicken. Differences in creatine levels can be attributed to
the energy required to form different metabolites. In the process of slaughtering non-halal chicken, less energy is produced,
resulting in fewer metabolites formed.[7]. Creatine is a compound synthesized from three amino acids: arginine, glycine, and
methionine. Creatine functions to prevent liver cirrhosis, indicating that higher creatine levels have a better impact on health.
Mixed chicken meat with halal and shubha, and halal and non-halal methods, does not have a greater creatine content than meat
slaughtered in a purely halal manner. Chicken meat slaughtered in a halal manner has a better health impact compared to meat
slaughtered in non-halal, shubha, or mixed methods.[23].
Carnosine is the highest metabolite in chicken meat slaughtered non-halal and the lowest in meat slaughtered halal. Carnosine
levels in halal-shubha mixtures are higher than in halal-non-halal mixtures. Carnosine is a compound synthesized from dipeptides,
which are low-molecular-weight hydrophilic antioxidants that act directly, although they can also affect the antiradical protection
system of organisms. High carnosine levels can reduce antiradical protection in the body; thus, chicken meat slaughtered non-
halal can reduce antiradicals in the body[24]. 3-Methylhistidine is the highest metabolite in meat slaughtered using halal methods
and the lowest in chicken meat slaughtered using shubha methods. 3-Methylhistidine is a compound that can be a biomarker of
meat proteins to identify increased muscle degradation or poor muscle protein turnover. In shubha-slaughtered chicken meat, the
level of 3-methylhistidine is the lowest because the cutting of the duct is only in two parts, resulting in very few metabolites
produced in this muscle. In halal-slaughtered chicken meat, the 3-methylhistidine level is the highest, indicating high turnover of
muscle proteins. Halal-slaughtered chicken has a more positive impact on health compared to shubha.[25].
In the analysis of untargeted metabolomics, UHPLC-HRMS demonstrates not only selectivity but also good precision, as
evidenced by the consistent detection of creatine, carnosine, and 3-methylhistidine in large quantities. Metabolites consistently
detected in meat can serve as markers for halal authentication. The results of untargeted metabolomics have shown that chicken
meat slaughtered using halal, non-halal, shubha, or mixed methods appears different. However, to authenticate halal status,
chemometric analysis is needed. The metabolite profiles of chicken meat slaughtered using halal, non-halal, Shubha, halal mixed
with shubha, and non-halal mixed methods are presented in Table 1.

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Table 1
Metabolite profiles of chicken meat slaughtered in halal, non-halal, shubha, halal mixture with Shubha, and halal mixture with non-
halal.
No
 
Name FormulaRT
[min]
m/zHalal
(Area
Average)
Shubha
(Area
Average)
Non-
Halal
(Area
Average)
Mix
Halal-
Shubha
(Area
Average)
Mix
Halal-
Non
Halal
(Area
Average)
1  Creatine (a) C4 H9
N3 O2
1,085 99,68,E + 095,E + 097,E + 098,E + 094,E + 09
2  Carnosine C9 H14
N4 O3
1,012 91,35,E + 083,E + 086,E + 084,E + 082,E + 08
3  3-Methylhistidine C7 H11
N3 O2
1,008 83,35,E + 085,E + 085,E + 085,E + 083,E + 08
4  L-Isoleucine C6 H13
N O2
1,644 96,41,E + 081,E + 083,E + 083,E + 089,E + 07
5  Betaine C5 H11
N O2
1,117 92,83,E + 088,E + 072,E + 082,E + 081,E + 08
6  2-Amino-1,3,4-
octadecanetriol
C18
H39 N
O3
15,19384,37,E + 072,E + 082,E + 082,E + 082,E + 08
7  L-Phenylalanine C9 H11
N O2
2,435 97,69,E + 077,E + 072,E + 082,E + 087,E + 07
8  L-Histidine C6 H9
N3 O2
1,002 98 2,E + 081,E + 082,E + 082,E + 081,E + 08
9  Hypoxanthine C5 H4
N4 O
1,138 99,11,E + 088,E + 071,E + 082,E + 086,E + 07
10 L-(+)-Arginine C6 H14
N4 O2
1,022 83,81,E + 089,E + 071,E + 082,E + 085,E + 07
11 Poly THF n8: C32
H66 O9:
25,80188,31,E + 081,E + 081,E + 082,E + 081,E + 08
12 Taurine C2 H7
N O3 S
1,063 73,31,E + 082,E + 071,E + 086,E + 077,E + 07
13 DL-Carnitine C7 H15
N O3
1,061 99,11,E + 089,E + 071,E + 081,E + 085,E + 07
14 L-Phenylalanine C9 H11
N O2
2,757 95,84,E + 072,E + 063,E + 063,E + 061,E + 06
15 DL-Glutamine C5 H10
N2 O3
1,055 91,58,E + 072,E + 071,E + 086,E + 075,E + 07
16 Creatine C4 H9
N3 O2
1,084 81,98,E + 079,E + 079,E + 077,E + 076,E + 07
17 L-Glutamic acid C5 H9
N O4
1,063 93,88,E + 072,E + 076,E + 077,E + 073,E + 07
18 Acetylcholine C7 H15
N O2
1,098 72,67,E + 072,E + 078,E + 074,E + 073,E + 07
19 Taurine C2 H7
N O3 S
1,061 90,96,E + 071,E + 078,E + 073,E + 074,E + 07
20 L-Tyrosine C9 H11
N O3
1,537 85 4,E + 072,E + 077,E + 077,E + 072,E + 07

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No
 
Name FormulaRT
[min]
m/zHalal
(Area
Average)
Shubha
(Area
Average)
Non-
Halal
(Area
Average)
Mix
Halal-
Shubha
(Area
Average)
Mix
Halal-
Non
Halal
(Area
Average)
21 Inosine C10
H12 N4
O5
1,141 99,26,E + 073,E + 074,E + 077,E + 072,E + 07
22 Acetyl-L-carnitine C9 H17
N O4
1,134 99,26,E + 072,E + 075,E + 072,E + 072,E + 07
23 L-Tyrosine C9 H11
N O3
1,144 88,83,E + 072,E + 076,E + 076,E + 072,E + 07
24 L-Glutathione (reduced)C10
H17 N3
O6 S
1,139 98,36,E + 079,E + 064,E + 073,E + 072,E + 07
25 4-Oxoproline C5 H7
N O3
1,166 96,94,E + 071,E + 075,E + 073,E + 072,E + 07
26 4-
Dodecylbenzenesulfonic
acid (a)
C18
H30 O3
S
8,611 98,86,E + 059,E + 052,E + 072,E + 062,E + 06
27 4-
Dodecylbenzenesulfonic
acid (b)
C18
H30 O3
S
12,41 97,22,E + 076,E + 055,E + 055,E + 056,E + 05
28 DL-Tryptophan (a) C11
H12 N2
O2
5,002 95,52,E + 072,E + 075,E + 075,E + 072,E + 07
29 DL-Tryptophan (b) C11
H12 N2
O2
5,365 94,91,E + 073,E + 052,E + 075,E + 053,E + 05
3.2 Principal component analysis
The results of the significant test using ANO VA, which met the significance v alue of p < 0.05, identified 29 metabolites, followed
by chemometric analysis. The metabolite with the highest significance v alue is L-histidine, and the lowest significant v alue is
creatine. The highest significance indicates that L-histidine had the lar gest difference in levels between chicken meat slaughtered
using halal, non-halal, shubha, and mixed methods, while creatine had the lowest difference in levels. Significant v alues can be
used as an initial screening to identify differential metabolites in each type of meat before conducting chemometric analysis [26],
[27].
The first chemometric analysis performed was Principal Component Analysis (PCA). The results of the PCA analysis show that
chicken meat slaughtered using halal, non-halal, shubha, and mixed methods can be grouped based on their metabolic profiles.
PCA was used for halal authentication. Maritha et al. used PCA to authenticate pork and beef based on lipid profiles[28]. Sutra et
al. explained that PCA could identify pork in food products.[29]. Roman et al. reported that PCA can authenticate the origin of
meatballs from pork and lard [30]. PCA is a type of unsupervised chemometric analysis used to assess various predetermined
sample classes[31]. In this study, the sample classes were halal, non-halal, shubha, halal and non-halal mixtures, and halal
mixtures with shubha [32]. PCA can be used to authenticate the halal status of chicken meat according to the slaughter process.
The PCA plot scores of chicken meat based on the slaughter process and the metabolites with the highest and lowest
significance v alues are presented in Fig. 1.
3.3 Cluster analysis
The second chemometric analysis performed was cluster analysis using a heatmap. The results of the cluster analysis using a
heatmap showed that chicken meat slaughtered using halal, non-halal, Shubha, halal mixed with shubha, and non-halal mixed

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methods could be effectively clustered. This indicates that the metabolites in each category have similar properties. The results
of cluster analysis can be used to authenticate the halal status of chicken meat based on the slaughter process. Several studies
have demonstrated the effectiveness of cluster analysis for halal authentication [33], [34]. Hindmarsh et al. used cluster analysis
to detect pork in beef meatballs and successfully separated non-halal meat from meatball mixtures [35]. They also used cluster
analysis to differentiate dog meat from beef meatballs. Cluster analysis is a chemometric method that can authenticate the halal
status of chicken meat based on the slaughter process and can accurately cluster meat even when mixed.
The results of the cluster analysis were followed by correlation network analysis to determine whether the metabolites were
interrelated. The correlation network analysis revealed that 21 metabolites were correlated with each other. Correlation networks
are also used to identify metabolites in non-halal and halal mixtures with shubha [36]. Rohani used correlation networks to predict
the outcomes of halal authentication [37]; thus, the results of this study can also be used to predict the metabolites associated
with halal status in chicken meat based on the slaughter process. The metabolites that correlate with chicken meat slaughtered
using halal, non-halal, Shubha, halal and non-halal mixtures, and halal mixtures with shubha are presented in Fig. 4
3.4 Partial least squares discriminant analysis
The third chemometric analysis performed was Partial Least Squares Discriminant Analysis (PLS-DA), which was used to classify
and predict metabolites that determine the halal status of chicken meat based on the slaughter process. The results of PLS-DA
showed that halal, non-halal, and shubha chicken meat, as well as halal and non-halal mixtures and halal mixtures with shubha,
could be effectively clustered. The loading plot from the PLS-DA analysis indicated that the metabolites are interrelated [38] The
markers that determine the halal status of chicken meat according to the slaughter process are presented in the VIP score
results. Based on the VIP score of 13, the metabolites that are significant for determining the halal status of chicken meat are
creatine, betaine, 2-amino-1,3,4-octadecanetriol, L-isoleucine, L-phenylalanine, L-histidine, L-glutamic acid, L-glutathione, DL-
glutamine, taurine, carnosine, and acetyl-L-carnitine, with an accuracy value of 0.85333. This accuracy value was used to confirm
that these metabolites are reliable for determining the halal status of chicken meat. The results of the PLS-DA analysis were
accurate, with the best accuracy value exceeding 0.7.
Several publications have explained that PLS-DA is used as a marker to determine halal status in various products. Surat et al.
reported that PLS-DA successfully detected three potential peptide markers—HPGDFGADAQGAMSK, HDPSLLPWTASYDPGSAK,
and FFESFGDLSNADAVMGNPK—from myoglobin, carbonic anhydrase 3, and beta-hemoglobin to detect pork in tuna[39] Irawadi
et al. used PLS-DA to predict the concentration of pork oil added to tuna oil, which can be used to authenticate the halal status of
the oil[40] PLS-DA is a standardized chemometric analysis method with good accuracy and precision for halal authentication,
including determining the halal status of chicken meat based on the slaughter process. The loading plot and VIP score from the
PLS-DA analysis are presented in Fig. 5.
4. Conclusion
Untargeted metabolomics using UHPLC-HRMS can selectively and accurately authenticate the halal status of chicken meat
based on the slaughter process. This method detected 29 different metabolites in chicken meat slaughtered using halal, non-
halal, shubha, halal and non-halal mixtures, and halal mixtures with shubha methods. Creatine, carnosine, and 3-methylhistidine
were identified as the highest metabolites, and variations in their levels can impact health when consuming the meat. Chicken
meat slaughtered in a halal manner shows the best health potential compared to meat slaughtered using non-halal, Shubha, or
mixed methods. PCA effectively demonstrates differences in the metabolic profiles of chicken meat based on the slaughter
method. Cluster analysis can group chicken meat according to the similarity of its metabolite properties. The correlation network
analysis indicates that 21 metabolites are interrelated in the halal authentication process. PLS-DA accurately predicts 13
potential metabolites as halal authentication markers, including creatine, betaine, 2-amino-1,3,4-octadecanetriol, L-isoleucine, L-
phenylalanine, L-histidine, L-glutamic acid, L-glutathione, DL-glutamine, taurine, carnosine, and acetyl-L-carnitine. The untargeted
metabolomics analysis method using UHPLC-HRMS, combined with chemometrics, presents a promising alternative for
authenticating the halal status of chicken meat based on its slaughter process (halal, non-halal, shubha, halal mixed with non-
halal, and halal mixed with shubha).

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Declarations
Acknowledgements 
The authors would like to thank the scientific suppor t from Universitas PGRI Madiun and Advance Research Laboratory of IPB
University, Indonesia.
Credit authorship contribution statement:
Vevi Maritha, Avip Kurniawan, and Rudi Heryanto: Investigation, Data curation, and writing of the original draft. Rudi Heryanto, Puri
Ratna Kartini, Firman Rezaldi, and Nur Ihda Farikhatin Nisa : Data curation. Vevi Maritha: Methodology and Conceptualization.
Alice Rivera and Mohammad Yuwono : Supervision, Writing review & editing.
Conflicts of Interest: The authors declare no conflict of inter est.
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Figures

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Figure 1
Chromatogram of Halal, Non-Halal, and Shubha Slaughtered Chicken Meat on ESI
+

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Figure 2
Chromatogram of Halal, Non-Halal, and Shubha Slaughtered Chicken Meat on ESI
-

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Figure 3
Score plot principle component analysis of chicken meat based on slaughter process (halal, non-halal, shubha, and mixed) and
metabolites with the highest and lowest significant v alues.
Figure 4
Correlation networks between metabolites that affect the tallness of chicken meat based on the slaughter process.

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Figure 5
Loading plot dan VIP scores, which are metabolites that distinguish halal, non-halal, shubha, and mixed chicken meat based on
the slaughter process.