پیش‌بینی برخی ویژگی‌های کیفی میوۀ انار با استفاده از روش غیرزیانبار پردازش تصویر

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی سابق کارشناسی ارشد، دانشگاه علوم کشاورزی و منابع طبیعی ساری

2 استادیار، دانشگاه علوم کشاورزی و منابع طبیعی ساری

چکیده

روش­های غیرزیانبار پایدار اهمیت زیادی دارند، چراکه محصول مورد بررسی به چرخۀ عرضه و مصرف برگشته و نیز مشکلات روش­های زیانبار مانند وقت­گیری و پرهزینه بودن را ندارند. از سوی دیگر تنوع و فراوانی ویژگی­های کیفی محصولات کشاورزی، از دیگر دلایل توسعۀ روش­های غیرزیانبار به‌شمار می­آید. بنابراین در این پژوهش توانایی روش‌های پردازش تصویر به­منظور پیش­بینی ویژگی‌های کیفی مانند حجم، وزن، مواد جامد محلول کل، اسید قابل عیارسنجی (تیتراسیون)، فنل کل و فعالیت پاداکسندگی (آنتی­اکسیدانی) میوۀ سه رقم انار شامل زاغ یزدی، ملس یزدی و ملس اصفهان در طول فصل رشدی سال 1392 ارزیابی شد. میوه­ها در چهار مرحلۀ 50، 80، 110 و 140 روز پس از گلدهی گردآوری‌شده و از لحاظ ویژگی‌های رنگی و شیمیایی ارزیابی شدند. درنهایت مدل‌های واسنجی (کالیبراسیون) مربوط به داده‌های رنگی و اندازه‌گیری‌های شیمیایی تدوین شدند. نتایج به‌دست‌آمده نشان از اعتبارسنجی مدل­ها داشت، نسبت انحراف معیار در رقم ملس اصفهان برای وزن 3/2، حجم 52/2، مواد جامد محلول 8/1 و فعالیت پاداکسندگی 95/2 بود. همچنین مشخص شد که روند تغییرپذیری اسید قابل عیارسنجی و فنل کل با رنگ میوۀ انار در هیچ‌کدام از رقم‌های مورد بررسی ضریب همبستگی معنی­داری نداشت و توسط روش پردازش تصویر قابل پیش‌بینی نبود. درمجموع می­توان نتیجه گرفت که روش پردازش تصویر، روشی کارا و قابلیت بسیار قوی در تشخیص همزمان و سریع مرحله‌های بلوغ و همچنین وضعیت ویژگی­های کیفی میوۀ انار رقم ملس اصفهان دارد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

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

نویسندگان [English]

  • Ali Mirhosseini 1
  • Hossein Sadeghi 2
  • Hossein Moradi 2
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
چکیده [English]

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.

کلیدواژه‌ها [English]

  • Antioxidant activity
  • color changes
  • Malase Esfahan
  • ripening
  • standard deviation

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علوم باغبانی ایران
دوره 49، شماره 2
شهریور 1397
صفحه 443-451

فایل ها

سابقه مقاله

  • تاریخ دریافت: 31 شهریور 1394
  • تاریخ بازنگری: 16 تیر 1396
  • تاریخ پذیرش: 26 تیر 1396

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