Table 3. Overview of analytical methods and technologies for detecting the adulteration

Non-compliance concern	Meat/meat products	Analytical method/technology		Summary of findings	Reference
Adulteration	Detection of rat meat in beef meatball	Molecular spectroscopy-based methods	Fourier transform infrared spectroscopy (FTIR)	- Spectral data from 3,100–800 cm–1 used for analysis.- Beef and rat meatballs differentiated using linear discriminant analysis.- Lipid composition differences revealed by FTIR spectra.	Lestari et al. (2022)
	Identification of chicken, chevon, beef and donkey meat		Nuclear magnetic resonance (NMR)	- Identified 37 metabolites in cow, goat, donkey, and chicken muscle using 1H-NMR.- Lactate, creatine, and 10 other metabolites distinguished white (chicken) from red meat (chevon, beef, donkey).- Inosine, uracil, carnosine, and 3 others differentiated chevon, beef, and donkey.	Akhtar et al. (2021)
	Detection of Pork in beef sausages		Near-infrared spectroscopy (NIR)	- Three methods for multivariate analysis were established: laboratory, fiber optic probe, and on-site.- Laboratory and fiber optic setups detected meat and fat adulteration down to 10%.- On-site setup detected meat adulteration effectively and fat adulteration up to 20% (quartz cuvettes) or 40% (polymer packaging).	Schmutzler et al. (2015)
	Identification of pork fat with other fats		Fluorecents light spectroscopy	- The developed method could effectively distinguish between pure pork, a mixture of pork, and samples without any pork based on the analyzed spectrum patterns.	Islam et al. (2021)
	Detection of rat and wild boar meat in beef meat	Chormatography-based methods	Gas chormatography (GC)	Annotated potential metabolites marker:- Beef class: dimethylfulvene- Rat class: benzyl alcohol- Wild boar class: 1,3,5-cycloheptatriene- Mixture of beef and rat class: benzaldehyde, 3-ethyl- Mixture of beef and wild boar class: 2,6-dimethyldecane	Amalia et al. (2022)
	Detection of horse and pork in highly processed food		High performance liquid chromatography (HPLC)	- Identified stable marker peptides for thermal processing of meat products.- Enabled to detecti of pork or horse at low concentrations (0.24% concentration) in beef matrix.- Developed a rapid 2-minute extraction protocol for protein extraction from processed food.	von Bargen et al. (2014)
	Detection of pork in Pangasius hypopthalmus meat (PHM)		Liquid chromatography (LC)	- Authentic and adulterated PHM were reliably distinguished (R>0.95 and Q>0.5).- Identified PC(o-18:0/18:2(9Z,12Z)) as a potential metabolite marker and dimyristoylphosphatidylcholine as a potential marker for PHM.- Myoglobin and β-hemoglobin peptides were identified as pork indicators.	Windarsih et al. (2022)
	Identification of pork, beef, and chicken			- A chemometrics-assisted shotgun proteomics approach using PCA and orthogonal partial least squares discriminant analysis (OPLS-DA) was employed to identify peptide markers.- Glu-C endoproteinase was used for peptide identification.- Peptide specificity was validated through in vitro analysis.	Yuswan et al. (2018)
	Identification of chicken, beef, and pork sausages	Polymerase chain reaction (PCR)-based methods	Simplex and multiplex-PCR	- Cytochrome Oxidase SubUnit I primers were effective in identifying bovine, porcine, and chicken DNA in sausages with a high sensitivity of 0.001 ng/μL.	Boyrusbianto et al. (2023)
	Detection of dog, pork, and rat meat in beef meatball		Simplex-, duplex-, and multiplex-PCR	- Multiplex-PCR with 12S rRNA gene primers could detect bovine, dog, pig, and rat species in beef meatballs in one reaction.	Cahyadi et al. (2020)
	Identification of pig meat and fat from other animals		PCR-RFLP (restriction fragment length polymorphisms)	- The cyt b PCR-RFLP species identification assay exhibited excellent results for detecting pig meat and fat.	Aida et al. (2005)
	Detection of pork in processed meat products			- The assay was able to detect 0.0001 ng of swine DNA in pure formats and 0.01% (w/w) spiked pork in extensively processed ternary mixtures of pork, beef, and wheat flour.	Ali et al. (2011)
	Pork adulterated in raw and cooked sausages		PCR-QIAxcel capillary electrophoresis	- PCR-QIA procedure efficiently differentiated targeted DNA fragments, even at low levels (0.01% pork/meat: w/w).	Barakat et al. (2014)
	Detection of dog meat in beef meatball		Real time-PCR	- Real-time PCR using Cyt b-55 primer detected dog meat DNA at concentrations as low as 0.25 ng/mL, equivalent to 1% of dog meat in beef meatballs.	Manalu et al. (2019)
	Identification of pork DNA in meat (beef and chicken) extracts		SYBR green I-real-time PCR	- The assay was able to achieve a low detection limit of 0.1 ng of porcine DNA.	Farrokhi and Jafari Joozani (2011)
	Detection of wild boar meat in beef meatball		Species-specific PCR	- The q-PCR assay with CYTBWB2-wb primers successfully detected wild boar meat DNA at low concentrations of 5 pg/μL.	Aina et al. (2019)
	Identification of cat, dog, pork, monkey, and rat meat			- The assay detected 0.01–0.02 ng of DNA from raw dog, pig, monkey, and rat meats and 1% of probable meatball constituents.	Ali et al. (2015)
	Detection of pork meat in beef, mutton, and chicken		qPCR (quantitative PCR)	- The assay showed high sensitivity and a low detection limit of 2.7 ng/μL for total DNA from pork meat.	Wu et al. (2021)
	Identification of porcine in meat products		qPCR and doplet digital PCR (ddPCR)	- QPCR and ddPCR exhibited comparable linearity (r2=0.9971 and 0.9998, respectively).- While detection limits were similar, ddPCR demonstrated superior sensitivity at low DNA concentrations.	Nuraeni et al. (2023)
	Identification of pork in raw beef, and chicken meat, and a mixture of processed meat	Nanotechnology	Gold nanoparticles (GNPs)	- Developed an electrochemical DNA biosensor using GNP-DNA probe bioconjugates on SPCE-Gold.- Optimized biosensor using 40 μL of 153 μg/mL bioconjugates, 20-minute immobilization, and 60-minute hybridization.	Hartati et al. (2019)
	Identification of beef, pork, rabbit, and chicken meat profile and meat powder	Differential scanning calorimetry (DSC)-		- DSC was used to verify the halal status of beef and its byproducts.- The results showed an endothermic peak for each.	Nugrahani and Aditya (2023)
	Detection of pork in beef floss	Immunoassays-based methods	Enzyme-linked immunosorbent assay (ELISA)	- ELISA was more effective than conventional PCR for intensely heated product samples.- Processed meat products might contain inhibitory chemicals that can affect species identification.	Aprilia et al. (2022)
	Detection of pork in meat extract		Molecularly imprinted polymer nanogels (MIP-NGs)	- Developed a rapid PSA detection system using nanogels and antibodies.- Analysis time under 30 minutes.- Effective in detecting 0.01 wt% pork adulteration in halal meat.	Cheubong et al. (2023)
	Identification of pork meat and pork sausages from beef, mutton, and chicken meats and sausages	Electronic nose		- Combining electronic nose technology, GCMS-HS analysis, and PCA for halal verification purposes gave the samples a good separation with 67% of the total variance.	Nurjuliana et al. (2011)
	Identification of beef and pork meat			- The classification results showed a high accuracy of 98.10% in detecting beef and pork using the optimized support vector machine.	Sarno et al. (2020)