استخراج مؤثرترین طول موج‏های طیف تخم‏مرغ با استفاده از الگوریتم ژنتیک و طبقه‏بندی آن‏ها با روابط رگرسیونی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشگاه رامین خوزستان

2 دانشگاه تربیت مدرس

3 دانشگاه شهید بهشتی تهران

چکیده

پتانسیل روش طیف‏سنجی عبوری (1100-nm200) به‏منظور ارزیابی کیفیت داخلی (تازگی) تخم‏مرغ سالم و دست‏نخورده در طول انبارداری در دمای  oC730 و رطوبت 425درصد بررسی شد. تعداد یک‏صد تخم‏مرغ برای اندازه‏گیری تازگی و جمع‏آوری طیف در طول زمان ذخیره‏سازی (تا 30 روز) استفاده شدند. دو مدل رگرسیونی میانHU   [1] و ضریب زرده (YC[2]) نسبت به زمان ذخیره‏سازی به ترتیب با ضریب همبستگی 86/0و 96/0 توسعه داده شد. معادلات ذکرشده حاکی از افت شدید کیفیت تخم‏مرغ در خلال نگهداری در این شرایط است. علاوه بر این، روشی برای به‏دست‏آوردن ویژگی‏های طول موج براساس الگوریتم‏های ژنتیکی شرح و بسط داده شد. این روش توانایی حل مشکل استخراج مؤثرترین اطلاعات از ماتریس داده‏های ابعدی بالا[3] را دارد. معادلات رگرسیونی با داده‏های خام و ویژگی‏های استخراج‏شده با الگوریتم‏ ژنتیک، با پردازش‏های گوناگون (SNV، MSC، FFT، و همچنین مشتقات اول و دوم)، به‏دست آمد. نتایج نشان داد که معادلات رگرسیونی براساس الگوریتم‏ ژنتیک و پردازش SNV و MSC می‏تواند طیف‏ها را در سه گروه طبقه‏بندی کند در حالی‏که با یکبار مشتق‏گیری، هر طیف روزانه می‏تواند در گروهی مجزا قرار گیرد.



[1] .Haugh unit


[2] .Yolk Coefficient


[3]. High Dimensional Data

کلیدواژه‌ها

عنوان مقاله [English]

Extraction of most effective wavelength of egg spectra using genetic algorithm and classifying using regression equations

چکیده [English]

The potential of Vis-IR (400–1100 nm) transmittance method to assess the internal quality (freshness) of intact chicken egg during storage at a temperature of 307 oC and 25% 4 relative humidity was investigated. One hundred chicken egg samples were used for measuring its freshness and spectral collection during egg storage times (up to 30 days). Two correlation models between Haugh unit (HU) and the yolk coefficient (YC) versus the storage time were developed with the correlation coefficients of 0.86, 0.96, respectively. The latter equations showed in that aforementioned conditions egg quality decreased dramatically. Furthermore, the method has developed to acquire the wavelength features based on genetic algorithm (GA). It can solve the problem of the effective information extraction from the high-dimensional data matrix. Regression equations were developed by raw and according to the wavelength features were acquired, respectively basing on different preprocessing (SNV, MSC, FFT, as well as 1st and 2nd derivations). The result indicated that regression equations based on GA and preprocessing SNV and MSC could classify egg’s spectra in three groups while by 1st derivation preprocessing, each daily spectrum could allocate each of them into separated groups.

کلیدواژه‌ها [English]

  • egg quality
  • Regression equation
  • Genetic Algorithm

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سابقه مقاله

  • تاریخ دریافت: 06 مهر 1392
  • تاریخ بازنگری: 15 دی 1393
  • تاریخ پذیرش: 17 اسفند 1393

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