Application of machine learning approach on halal meat authentication principle, challenges, and prospects: A review.

Meat is a source of essential amino acids that are necessary for human growth and development, meat can come from dead, alive, Halal, or non-Halal animal species which are intentionally or economically (adulteration) sold to consumers. Sharia has prohibited the consumption of pork by Muslims. Because of the activities of adulterators in recent times, consumers are aware of what they eat.

Next Generation Sequencing-based DNA metabarcoding for animal species profiling in fish feed.

The expansion of worldwide aquaculture has been accompanied by extensive growth in the fish feed industry. However, improper labelling of many commercially available fish feeds has raised security and safety concerns over the species' origin of the ingredients. The inclusion of ruminants-derived ingredients in fish feed is prohibited according to EU legislation while porcine inclusion in fish feed has been a great concern among Muslim farmers.

The characteristics and roles of antimicrobial peptides as potential treatment for antibiotic-resistant pathogens: a review.

The emergence of antibiotic-resistant bacteria has become a significant and ever-increasing threat to global public health, increasing both morbidity and mortality rates, and the financial burden on health services. Infection by drug-resistant bacteria is anticipated to contribute to the demise of almost 10 million people by the year 2050 unless a competent and effective response is devised to engage with this issue. The emergence and spread of resistance are commonly caused by the excessive or inappropriate use of antibiotics and substandard pharmaceuticals.

Discrimination of Malaysian stingless bee honey from different entomological origins based on physicochemical properties and volatile compound profiles using chemometrics and machine learning.

Identification of honey origin based on specific chemical markers is important for honey authentication. This study is aimed to differentiate Malaysian stingless bee honey from different entomological origins (Heterotrigona bakeri, Geniotrigona thoracica and Tetrigona binghami) based on physicochemical properties (pH, moisture content, ash, total soluble solid and electrical conductivity) and volatile compound profiles. The discrimination pattern of 75 honey samples was observed using Principal Component Analysis (PCA), Hierarchical Clustering Analysis (HCA), Partial Least Square-Discriminant Analysis (PLS-DA), and Support Vector Machine (SVM).