Applications of artificial intelligence (AI) in managing food quality and ensuring global food security

The food industry uses artificial intelligence (AI) to enhance food quality and security while proposing significant capital savings and resource optimization. Additionally, understanding machine learning (ML) techniques is essential for their effectiveness. Therefore, the gap lies in examining how industrial automation plays a crucial role in successfully implementing this new technology. To address this gap, this review explores AI’s potential to significantly enhance food safety by creating a more transparent supply chain management system. Therefore, the primary focus is exploring potential AI applications, such as artificial neural networks (ANN) and convolutional neural networks (CNN), for detecting food and agricultural product quality. The primary goal of utilizing these AI applications is to reduce human intervention and effort. These methodologies have advantages and disadvantages regarding theoretical knowledge and model interpretation.

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Publication Details

Journal
CyTA - Journal of Food
Published
2024-09-09
DOI
https://doi.org/10.1080/19476337.2024.2393287
Citations
61
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
32.24
Controls
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article

Applications of artificial intelligence (AI) in managing food quality and ensuring global food security

Kodjo Théodore Gnedeka, Sana Noreen, Hassan Mehmood, Ali Ikram et al.
61 citations
CyTA - Journal of Food
Big Data and Business Intelligence
32.24
article

Applications of artificial intelligence (AI) in managing food quality and ensuring global food security

Kodjo Théodore Gnedeka, Sana Noreen, Hassan Mehmood, Ali Ikram, Areeba Rasheed, Muhammad Tayyab Arshad
article en
61 citations

Abstract

The food industry uses artificial intelligence (AI) to enhance food quality and security while proposing significant capital savings and resource optimization. Additionally, understanding machine learning (ML) techniques is essential for their effectiveness. Therefore, the gap lies in examining how industrial automation plays a crucial role in successfully implementing this new technology. To address this gap, this review explores AI’s potential to significantly enhance food safety by creating a more transparent supply chain management system. Therefore, the primary focus is exploring potential AI applications, such as artificial neural networks (ANN) and convolutional neural networks (CNN), for detecting food and agricultural product quality. The primary goal of utilizing these AI applications is to reduce human intervention and effort. These methodologies have advantages and disadvantages regarding theoretical knowledge and model interpretation.

CyTA - Journal of FoodVol. 22(1)
University of Lahore (PK), University of Lomé (TG)
Zero hunger
Openalex Percentile: Top 0%
Big Data and Business Intelligence
32.24
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