طبقه بندی تخم مرغ براساس کیفیت درونی به کمک بینایی کامپیوتر

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد دانشکده مهندسی زراعی و عمران روستایی، گروه مکانیک بیوسیستم، دانشگاه کشاورزی و منابع طبیعی رامین خوزستان

2 استادیار، دانشکره مهندسی زراعی و عمران روستایی، دانشگاه کشاورزی و منایع طبیعی رامین خوزستان

3 دانشکده علوم دامی و صنایع غذایی، دانشگاه کشاورزی و منابع طبیعی رامین خوزستان

چکیده

امروزه نگرانی در مورد کیفیت تخم­مرغ به‌طور پیوسته در حال افزایش است. تازگی تخم مرغ سهم عمده­ای در تعیین کیفیت تخم مرغ و محصولات آن دارد. در همین راستا به‌منظور دستیابی به بهره­وری و تولید بیش‌تر، ارزیابی کیفیت تخم مرغ از لحاظ ایمنی و تضمین کیفیت آن ضروری و مهم تلقی می­گردد. لذا هدف از این پژوهش طراحی و ساخت دستگاهی به‌منظور تعیین کیفیت داخلی تخم­مرغ به کمک بینایی ماشین در نظر گرفته شد. بدین منظور بررسی تعداد 210 عدد تخم­مرغ به مدت 30 روز در دما و رطوبت اتاق در قالب طرح کاملاً تصادفی مورد استفاده قرار گرفت و پارامترهای کیفی تخم­مرغ از قبیل وزن کلی تخم­مرغ، وزن زرده، سفیده و پوسته، مقاومت و ضخامت پوسته، واحد هاو به‌صورت مخرب و مساحت کیسه هوایی، و شاخص مساحت (D) به‌صورت غیر مخرب اندازه­گیری شدند. مطابق آنالیز آماری صورت گرفته مشخص گردید صفات وزن کلی تخم­مرغ، مقاومت و ضخامت پوسته، وزن زرده و پوسته و رنگ زرده به­عنوان پارامترهای کیفی تخم­مرغ تحت تأثیر زمان انبارمانی قرار نگرفتند (05/0p>)، ولی مساحت کیسه هوایی و پارامتر D به‌عنوان پارامترهای غیرمخرب، در سطح احتمال 5% به­طور معنی­داری روند افزایشی داشتند. هم‌چنین نتایج بررسی­ها نشان داد پارامترها و با افزایش زمان انبارمانی از 28/9 به 04/2 کاهش یافت (05/0p<). دقت طبقه­بندی با استفاده از داده­های غیر­مخرب با روش پارزن به میزان 17/84% محاسبه گردید. این مسأله نشان از توانایی سامانه پیشنهاد شده به‌منظور اندازه‌گیری طبقه­بندی تخم­مرغ­های با­کیفیت از بی­کیفیت را دارد.

کلیدواژه‌ها

عنوان مقاله [English]

Classification of Eggs Based on the Internal Quality Using of Computer Vision

نویسندگان [English]

  • Elham Nematinia 1
  • Saman Abdanan Mehdizadeh 2
  • Mohammad Reza Ghorbani 3
1 MSc student of Mechanics of Biosystems Engineering Department, Faculty of Agricultural Engineering and Rural Development, Ramin Agriculture and Natural Resources University of Khuzestan.
2 Assistant professor of Mechanics of Biosystems Engineering Department, Faculty of Agricultural Engineering and Rural Development, Ramin Agriculture and Natural Resources University of Khuzestan
3 Assistant Professor, Department of Animal Science, Faculty of Animal Science and Food Technology Ramin Agriculture and Natural Resources University of Khuzestan
چکیده [English]

Nowadays, concern about egg quality is growing steadily. Freshness makes a major contribution to the quality of egg and egg products. In this regard, in order to achieve both high efficiency and high productivity, eggs’ quality assessment is necessary to enhance safety and quality assurance. Therefore, the aim of this study was to design and fabricate a system to determine the internal quality of eggs using of machine vision. For this purpose, 210 eggs for 30 days were storted at room temperature and humidity in a completely randomized design and some quality parameters of eggs were measured (e.g. total weight of egg, yolk, albumen and eggshell weight, strength and thickness of the eggshell, Haugh unit as destructive parameters and air cell area, and area index (D) as non-destructive parameters). According to statistical analysis total weight of egg, strength and thickness of the shell, yolk and shell weight and yolk color as egg quality parameters were not affected by the storage time (p>0.05). But, the air cell area and the parameter D as non-destructive parameters, was increased significantly at the level of 5%. The results showed Haugh unit was decreased from 9.28 to 2.04 as storage time increased (p<0.05). Classification accuracy using non-destructive data with Parzen method was calculated 84.17%. This shows the ability of the proposed system to classify fresh eggs from unfreash ones with high accuracy.

کلیدواژه‌ها [English]

  • Egg
  • Image Processing
  • Haugh unit
  • Air cell area
  • Storage time
  • Parzen classification

مراجع

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فناوری‌های جدید در صنعت غذا
دوره 4، شماره 4
تیر 1396
صفحه 109-122

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سابقه مقاله

  • تاریخ دریافت: 02 اردیبهشت 1396
  • تاریخ بازنگری: 27 اردیبهشت 1396
  • تاریخ پذیرش: 24 تیر 1396

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