AI-Driven Innovations in Meat Quality and Safety: Applications, Challenges, and Future Directions

Emrobowansan Monday Idamokoro

doi:10.3844/ajbbsp.2025.420.427

Article Details

AI-Driven Innovations in Meat Quality and Safety: Applications, Challenges, and Future Directions

Authors:

Emrobowansan Monday Idamokoro

Publisher:

Science Publications

Journal:

American Journal of Biochemistry and Biotechnology Vol.21 Issue 3, pp.420-427

Document Type:

Article

Publication Date:

1/2026

Document Language:

English

Document ID (Org No.):

2001397627

pISSN:

1558-6332

DOI:

10.3844/ajbbsp.2025.420.427

Keywords:

Abstract:

 Artificial Intelligence (AI) is revolutionizing the meat sector by improving efficiency, accurateness, as well as sustainability in meat production, quality evaluation, and safety control. The conventional systems of meat inspection, handling, and processing are usually time consuming, labour-intensive, prone to contamination during handling and often susceptible to human errors. The use of artificial intelligence to drive technologies, including Deep Learning (DL), Machine Learning (ML), and computer vision have transformed the industry by making available automated, data-driven answers that enhance decision-making, boost meat production processes, as well as guarantee to a large extent food safety with reduced contaminations in meat. AI-powered imaging procedures enable fast and precise meat quality evaluation by assessing several features including meat marbling, colour, and tenderness. Advanced biosensors and spectroscopy tools integrated with AI algorithms have greatly enhanced contamination detection, permitting real-time detection and identification of antibiotic filtrates, microbial pathogens, and spoilage during meat processing. In addition, AI-induced automation and robotics are reforming meat handling, reducing waste, as well as improving worker safety in the meat industry. From the perspective of supply chain supervision, extrapolative analytics and block-chain incorporation together with AI have contributed to the enhancement of traceability, logistics effectiveness, and demand forecasting. Regardless of these advancements in meat processing with AI, challenges including high operation costs, data accessibility, and ethical concerns poses some barriers to the extensive adoption of AI in the meat industry. It is suggested that future investigations should centre on cost-effective AI solutions, enhanced data regularization, as well as the integration of emergent technologies including the Internet of Things (IoT) with block-chain to build a more sustainable as well as transparent meat sector. This review highpoints the transformative role of artificial intelligence in the meat sector as well as give future suggestions for safeguarding quality, efficiency, and safety the production of meat/ meat products.

Article Details

AI-Driven Innovations in Meat Quality and Safety: Applications, Challenges, and Future Directions

Authors:

Emrobowansan Monday Idamokoro

Publisher:

Science Publications

Journal:

American Journal of Biochemistry and Biotechnology Vol.21 Issue 3, pp.420-427

Document Type:

Article

Publication Date:

1/2026

Document Language:

English

Document ID (Org No.):

2001397627

pISSN:

1558-6332

DOI:

10.3844/ajbbsp.2025.420.427

Artificial Intelligence

Machine Learning

Meat Science

Food Safety

Automation

Supply Chain Optimization

Issues

Article Details

AI-Driven Innovations in Meat Quality and Safety: Applications, Challenges, and Future Directions

Authors: Emrobowansan Monday Idamokoro

Publisher: Science Publications

Journal: American Journal of Biochemistry and Biotechnology Vol.21 Issue 3, pp.420-427

Document Type: Article

Publication Date: 1/2026

Document Language: English

Document ID (Org No.): 2001397627

pISSN: 1558-6332

DOI: 10.3844/ajbbsp.2025.420.427

Artificial Intelligence

Machine Learning

Meat Science

Food Safety

Automation

Supply Chain Optimization

Issues

Authors:

Emrobowansan Monday Idamokoro

Publisher:

Science Publications

Journal:

American Journal of Biochemistry and Biotechnology Vol.21 Issue 3, pp.420-427

Document Type:

Article

Publication Date:

1/2026

Document Language:

English

Document ID (Org No.):

2001397627

pISSN:

1558-6332

DOI:

10.3844/ajbbsp.2025.420.427