Table 2. Overview of analytical methods and technologies for detecting the mislabelling issue

Non-compliance concern	Meat/meat product	Method/technology	Summary of findings	Reference
Mislabelling	Prepacked meat products (beef and poultry) include sausages, cold-cut meats, cooked whole muscle meats, breaded products, meatballs, and ground meats. Sausages, cold-cut meats, cooked whole muscle meats, breaded products, meatballs, and ground meats.	Multiplex polymerase chain reaction (PCR)	- Utilized species-specific primers for meat species identification.- Identified a high mislabeling rate of 78.3% in the samples.	Chuah et al. (2016)
	Packaged food	Optical Character Recognition (OCR) technology	- OCR technology employed for character recognition on halal product packaging.- Front-end system utilized mobile device camera.- Communication with back-end system facilitated through web service technology.- Application successfully identified halal products based on label information.	Yuniarti et al. (2017)
	Packaged food	Deep learning technology: convolutional neural networks (CNNs)	- CNNs employed for non-halal composition detection in packaged foods via image processing.- Identification of non-halal compositions involved combining characters into words and comparing with a list.- Segmentation process significantly influenced accuracy, resulting in 50% overall word accuracy.- Main error linked to incorrect segmentation.	Fadhilah et al. (2018)