en public specific letter to the editor <div style="text-align: justify;"><span style="font-size:11pt"><span style="background:white"><span style="line-height:115%"><span calibri="" style="font-family:"><span new="" roman="" style="font-family:" times=""><span style="color:black"><span style="letter-spacing:-.1pt">The global food industry faces increasing pressure to ensure high standards of safety, sustainability, and consumer satisfaction </span></span></span><span new="" roman="" style="font-family:" times=""><span style="color:black"><span style="letter-spacing:-.1pt"></span></span></span><span new="" roman="" style="font-family:" times=""><span style="color:black"><span style="letter-spacing:-.1pt">(Marzban and Sadeghi-Nodoushan, 2025)</span></span></span><span new="" roman="" style="font-family:" times=""><span style="color:black"><span style="letter-spacing:-.1pt">. As expectations grow, traditional food quality assurance methods struggle to keep pace with the complexity and scale of modern production </span></span></span><span new="" roman="" style="font-family:" times=""><span style="color:black"><span style="letter-spacing:-.1pt"></span></span></span><span new="" roman="" style="font-family:" times=""><span style="color:black"><span style="letter-spacing:-.1pt">(Marzban<i> et al.</i>, 2023)</span></span></span><span new="" roman="" style="font-family:" times=""><span style="color:black"><span style="letter-spacing:-.1pt">. Artificial intelligence (AI) emerged as a revolutionary force, reshaping the way food quality is monitored, assessed, and controlled </span></span></span><span new="" roman="" style="font-family:" times=""><span style="color:black"><span style="letter-spacing:-.1pt"></span></span></span><span new="" roman="" style="font-family:" times=""><span style="color:black"><span style="letter-spacing:-.1pt">(Marzban<i> et al.</i>, 2023)</span></span></span><span new="" roman="" style="font-family:" times=""><span style="color:black"><span style="letter-spacing:-.1pt">. By integrating AI-driven technologies, manufacturers and regulatory bodies can enhance efficiency, minimize risks, and implement predictive solutions that were once considered unattainable </span></span></span><span new="" roman="" style="font-family:" times=""><span style="color:black"><span style="letter-spacing:-.1pt"></span></span></span><span new="" roman="" style="font-family:" times=""><span style="color:black"><span style="letter-spacing:-.1pt">(Emami and Marzban, 2023)</span></span></span><span new="" roman="" style="font-family:" times=""><span style="color:black"><span style="letter-spacing:-.1pt">.</span></span></span><span new="" roman="" style="font-family:" times=""><span style="letter-spacing:-.1pt"></span></span></span></span></span></span><br> <br> &nbsp;</div> Artificial intelligence, food quality assurance, sensory evaluation, predictive analytics, sustainability 166 168 http://jnfs.ssu.ac.ir/browse.php?a_code=A-10-123-41&slc_lang=en&sid=1 Ameneh Marzban 0000-0002-8111-3319 No Department of Health in Disasters and Emergencies, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran Payam Emami 0000-0001-8180-8607 No Department of Emergency Medical Sciences, Faculty of Paramedical Sciences, Kurdistan University of Medical Sciences, Sanandaj, Iran Mohsen Dowlati mohsendowlati.69@gmail.com 0000-0002-1892-7539 Yes Health Management and Economics Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran