A novel, non-destructive approach for real-time detection of starch gelatinization using YOLO-based deep learning models

Md. Fahad Jubayer; Mahmud Hasan; Md Khurram Monir Rabby; Md. Mozammel Hoque; Md. Masudur Rahman; Md Abdur Rashid Sarker

doi:10.1039/d6fb00010j

A novel, non-destructive approach for real-time detection of starch gelatinization using YOLO-based deep learning models

Sustainable Food Technology 2026 Open access

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Authors: Md. Fahad Jubayer, Mahmud Hasan, Md Khurram Monir Rabby, Md. Mozammel Hoque, Md. Masudur Rahman, Md Abdur Rashid Sarker

DOI: 10.1039/d6fb00010j

Cited by: 1

References: 54

Abstract

This research proposes a novel, non-destructive, vision-based approach for real-time detection of starch gelatinization using YOLO models to overcome the limitations of traditional methods, which are manual and subjective for industrial control.

Fields of Study & Subjects

Food composition and properties COVID-19 diagnosis using AI Nutritional Studies and Diet

Publication details

Journal / source: Sustainable Food Technology
Publisher: Royal Society of Chemistry (RSC)
Volume: 4
Issue: 4
Pages: 4295–4318
Publication date: 1 January 2026
Language: EN

References 54