%0 Journal Article %T Application of Magnetic Resonance Imaging (MRI) as a safe & Application of Magnetic Resonance Imaging (MRI) as a safe & non-destructive method for monitoring of fruit & vegetable in postharvest period %J Iranian Journal of Medical Physics %I Mashhad University of Medical Sciences %Z 2345-3672 %A Fatemi, Hamideh %A Safaeian layen, Ghorban %A Azizi, Majid %A Feyzi laein, Ali %D 2018 %\ 12/01/2018 %V 15 %N Special Issue-12th. Iranian Congress of Medical Physics %P 256-256 %! Application of Magnetic Resonance Imaging (MRI) as a safe & Application of Magnetic Resonance Imaging (MRI) as a safe & non-destructive method for monitoring of fruit & vegetable in postharvest period %K magnetic resonance imaging %K Fruit %K Vegetable %K Post-harvest %R 10.22038/ijmp.2018.12892 %X To investigate and control quality, one must be able to measure quality-related attributes. Quality of produce encompasses sensory attributes, nutritive values, chemical constituents, mechanical properties, functional properties and defects. MRI has great potential for evaluating the quality of fruits and vegetables. The equipment now available is not feasible for routine quality testing. The image and resolution produced by MRI is quite detailed and can detect tiny changes of structures within the body. For some procedures, contrast agents, such as gadolinium, are used to increase the accuracy of the images. MRI additionally quality, can even examine the histology, histochemistry and structural characteristics of samples. He also mentioned that MRI is used as an on-line sensor in postharvest sorting and processing situations. The equipment now available is not feasible for routine quality testing; however, costs and capabilities are rapidly improving. Each sensor method is based on the measurement of a given constituent or property; therefore, its ability to measure overall quality is only as good as the relationship of that constituent or property to quality as defined for a particular purpose. Improved statistical methods for combining the inputs from several measurements into classification algorithms    are being developed %U