Recent advances of application of optical imaging techniques for disease detection in fruits and vegetables: a review - Eh Teet, Sudau; Hashim, Norhashila (Elsevier BV, 2023)
Fruits and vegetables are among the agricultural products that enjoy a high demand in the market. However, the most critical challenge in the production of fruits and vegetables is disease infections which can lead to economic loss. The current assessment method of disease infection still relies on conventional methods and laboratory analysis. The conventional methods although simple and easy are laborious and have less accuracy while laboratory analysis is costly and time-consuming. Over the last two decades, optical imaging techniques have emerged and are gaining interest in the agricultural and food industries. These techniques offer easy, rapid, accurate, reliable as well as user-friendly sensing tools for the identification of quality and disease infection in agricultural products. The fundamental aspect in the techniques is the interaction of light with the tissue and the manipulation of light when interacting with a surface. The integration of edge computing along with artificial intelligence has also reshaped the technology to another level. The use of other agricultural technologies such as drones or robots enables real-time monitoring and efficient farm management. Thus, this paper reviews recent advances in the application of optical imaging techniques for disease detection in fruits and vegetables. This includes computer vision, multispectral imaging, hyperspectral imaging, biospeckle and thermal imaging. The feasibility of the optical imaging techniques is discussed. Challenges and considerations for future research are also highlighted. This review provides a new insight into the recent application of optical imaging which is not only beneficial for the agricultural and food industries but also to other relevant industries.