Novel strategies for mitigating biotic and abiotic stresses for agricultural and environmental sustainbility

Fresh fruits and vegetables are susceptible to mechanical damage and physiological problems induced by static and dynamic forces acting on them during postharvest handling. Detecting these mechanical damages is critical to quality control in fresh produce processing and handling. The detection of bruises is primarily based on manual inspection, which is time-consuming and error-prone, particularly for early bruises. As a result, industries are looking for fast, non-destructive, and precise technology for fresh produce inspection along the postharvest value chain. Non-destructive imaging techniques have the ability to identify mechanical damage in real-time while overcoming the drawbacks of traditional methods which are tediousness, destructiveness, and time consumption. The application of imaging techniques including biospeckle imaging, computer vision, hyperspectral imaging, thermal imaging, and other imaging techniques for real-time and automated bruise detection is proposed in this chapter.

Fresh fruits and vegetables are susceptible to mechanical damage and physiological problems induced by static and dynamic forces acting on them during postharvest handling. Detecting these mechanical damages is critical to quality control in fresh produce processing and handling. The detection of bruises is primarily based on manual inspection, which is time-consuming and error-prone, particularly for early bruises. As a result, industries are looking for fast, non-destructive, and precise technology for fresh produce inspection along the postharvest value chain. Non-destructive imaging techniques have the ability to identify mechanical damage in real-time while overcoming the drawbacks of traditional methods which are tediousness, destructiveness, and time consumption. The application of imaging techniques including biospeckle imaging, computer vision, hyperspectral imaging, thermal imaging, and other imaging techniques for real-time and automated bruise detection is proposed in this chapter.