Qualitative Analysis of Apple Fruit during Storage using Magnetic Resonance Imaging
Journal Title: Journal of Agricultural Machinery - Year 2025, Vol 15, Issue 1
Abstract
Magnetic resonance imaging (MRI) is a non-destructive technique for determining the quality of fruits which, with different protocols, shows the density and structure of hydrogen atoms in the fruit in which it is placed. This study compared MRI images of healthy and bruised apple flesh tissues, both with and without pests, using various protocols to identify the best one. For this purpose, magnetic resonance imaging (MRI) using two protocols: T1 (Spin-lattice relaxation time) and T2 (Spin-spin relaxation time), was carried out on 200 apple fruits that were loaded during storage. The loading of fruits was performed at four levels: 150, 300, 450, and 600 N in a quasi-static manner, and then stored for periods of 25, 50, and 75 days at 4 °C. At the end of each storage period, imaging was carried out. Then, the contrast of T1 and T2 images of healthy and bruised tissue of apple fruit with and without pests using ImageJ software was determined. It was concluded that the healthy tissue of apple fruit without pests was clearer in T1 images than in T2 images. It has also been seen that the bruised area of fruits without pests in T2 images is more recognizable than in T1 images.
Authors and Affiliations
R. Khodabakhshian,R. Baghbani,
Keywords
Related Articles
- EP ID EP760024
- DOI https://doi.org/10.22067/jam.2024.87861.1243
- Views 31
- Downloads 0
Reliability evaluation and analysis of sugarcane 7000 series harvesters in sugarcane harvesting
Introduction: The performance of agricultural machines depends on the reliability of the equipment used, the maintenance efficiency, the operation process, the technical expertise of workers, etc. As the size and complex...
The Effect of Urea Fertilization Method and Moisture Content at Harvest Time on Mechanical Properties of Dried Corn
Mechanical properties of grain are influenced by various factors including soil nutrients and grain moisture content at harvest time. In order to reduce mechanical losses, the design of different processing operations sh...
Prediction Model for Wheat Grain Losses in Header of Simulator by Using Dimensional Analysis Approach
Introduction One of the problems which considered in recent years for grain harvesting is loss of wheat during production until consumption and tenders the offers for prevention of its especially in harvesting times by c...
Modeling the Effective Parameters on Accuracy of Soil Electrical Conductivity Measurement Systems Using RBF Neural Network
Introduction Presently, the loss of ground water levels and the increase in dissolved salts have given importance to the determination of salinity and the management of their variations in irrigated farms. Soil electrica...
Prediction of lateral surface, volume and sphericity of pomegranate using MLP artificial neural network
Introduction: Fast and accurate determination of geometrical properties of agricultural products has many applications in agricultural operations like planting, cultivating, harvesting and post-harvesting. Calculations r...