Prediction of some pomegranate fruit quality characteristics by non-destructive image processing technique

Document Type : Full Paper


1 Foermer M.Sc. Student, Department of Horticulture, Sari University of Agricultural Sciences and Natural Resources, Iran

2 Assistant Professor, Department of Horticulture, Sari University of Agricultural Sciences and Natural Resources, Iran


Non-destructive methods are very important in agriculture because the tested product can return to the market process, and also they don’t have the problems of destructive methods such as time-consuming and cost. On the other hand, diversity and abundance of quality characteristics of agricultural products are considered as the other reasons for the development of non-destructive methods. Therefore, in this study the ability of the image processing method in order to predict the quality characteristics such as volume, weight, total soluble solids, titrable acid, total phenolic and antioxidant activity of three Zaghe Yazdi, Malase Yazdi and Malase Esfahan cultivars of pomegranate fruit during 2013 growth season, was investigated. Samples were collected at four stages of 50, 80, 110 and 140 days after full bloom and then the color and chemical characteristics were evaluated. Finally, the calibration models related to colorimetric data and chemical measurements were prepared.Results of validation of models showed that in Malase Esfahan cultivar, the standard deviation ratio was 2.3, 2.52, 1.8 and 2.95 for weight, volume, total soluble solids and antioxidant activity, respectively. Moreover, it was found that the changes of titratable acid and total phenolic had no significant correlation coefficient with the color of pomegranate fruit and there were not predictable by image processing technique.  Overall, it can be concluded that the image processing technique is an efficient method and has a very strong potential for simultaneous and rapid detection of maturity stages and also to detect the status of qualitative characteristics in pomegranate fruit cv. Malase Esfahan.


Main Subjects

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