Vol. 10, Issue 12 (2021)

Author(s):
K Bhavya Sree, R Sathish and M Sampath Kumar

Abstract:
Ensuring the quality of fruits is a critical aspect of the horticultural supply chain, influencing consumer satisfaction, shelf-life, and market value. Traditional methods of fruit quality assessment are often destructive, time-consuming, and subjective, limiting their scalability and reliability. In recent years, advanced imaging techniques have emerged as powerful tools for non-destructive, rapid, and accurate evaluation of both external and internal fruit attributes. This review provides a comprehensive overview of cutting-edge imaging technologies—including hyperspectral imaging, thermal imaging, X-ray computed tomography, magnetic resonance imaging, and 3D vision systems—highlighting their principles, applications, and performance in assessing key quality parameters such as ripeness, firmness, defects, and internal composition. The integration of artificial intelligence and machine learning algorithms for image analysis is also discussed, offering insights into the development of automated, intelligent fruit inspection systems. Challenges, limitations, and future research directions are explored, emphasizing the role of interdisciplinary innovation in advancing precision agriculture and postharvest technology.