SYNOPSIS   

The global surge in food demand, expected to nearly double by 2050, poses major challenges for food quality, safety, and resource efficiency. Artificial intelligence (AI) and digital technologies are revolutionizing postharvest agricultural practices by enabling accurate, non-destructive assessment of food quality across the supply chain. Tools such as hyperspectral imaging, electronic tongue and nose, and machine learning algorithms automate monitoring, analysis, and classification, reducing human error and enhancing consistency. These AI-powered systems support predictive analytics, efficient resource use, and rapid hazard detection, leading to improved hygiene, reduced waste, and lower operational costs. User-friendly interfaces facilitate real-time decision-making for producers and processors, promoting traceability and sustainability. As digital transformation accelerates, stakeholders in agriculture and food industries benefit from greater efficiency and resilience. The ongoing adoption of AI is crucial for achieving global food security and fostering sustainable, high-quality food systems for a growing population.


BIODATA OF SPEAKER

Associate Professor Ir. Dr. Norhashila Hashim, from Universiti Putra Malaysia, specializes in postharvest and agricultural process engineering. She has led 14 research projects, securing over USD 750,000 in grants, and published 150+ journal articles, 1 book, 2 edited books, 12 books chapters, and 18 intellectual properties. Her acclaimed research has earned her the UPM Vice Chancellor Fellowship, MSAE Award, SEARCA Professorial Chair, and multiple innovation medals. A recognized thought leader, she serves as a keynote speaker, editorial board member, and consultant. She is a Professional and Chartered Engineer, AFETD Chair (IEM), and MSAE member, advancing agricultural engineering and sustainability.