درجه‌بندی بصری گوجه‌فرنگی گیلاسی پوشش‌دار شده با ژل آلوئه‌ورا حاوی روغن شاهدانه با روش‌های تجزیه و تحلیل مولفه‌های اصلی، شبکه عصبی مصنوعی و سیستم استنتاج تطبیقی عصبی- فازی

نویسندگان
گروه علوم و مهندسی صنایع غذایی، دانشکده کشاورزی، دانشگاه زنجان، زنجان 38791- 45371، ایران
چکیده
در پژوهش حاضر، در قدم اول تاثیر پوشش ژل آلوئه‌ورا (75 درصد حجمی/حجمی) حاوی غلظت‌های مختلف از روغن شاهدانه (1-5 درصد حجمی/حجمی) بر برخی از ویژگی‌های فیزیکی‌و‌شیمیایی گوجه‌فرنگی گیلاسی حین دوره نگهداری در دمای محیط بررسی گردید. نتایج به دست آمده حاکی از توانایی روغن شاهدانه جهت بهبود ویژگی‌های فیزیکی‌و‌شیمیایی گوجه‌فرنگی گیلاسی حین دوره نگهداری می‌باشد هرچند اختلاف معنی‌داری بین سطوح 3 و 5 درصد مشاهده نگردید (05/0p>). تغییر شیب در روند تغییرات شاخص رسیدگی برای نمونه پوشش‌دار شده با ژل آلوئه‌ورا 75 درصد در روز 12 و برای نمونه پوشش‌دار شده با ژل آلوئه‌ورا 75 درصد حاوی 3 درصد روغن شاهدانه در روز 16 رخ داد. با استفاده از یک سامانه پردازش تصویر نیز تغییرات نمونه‌های پوشش‌دار شده بر اساس خصیصه‌های رنگی و بافت حاصل از تصویر بررسی و به روش‌های مختلف درجه‌بندی شدند. نتایج حاکی از آن است که روش‌های تجزیه و تحلیل مولفه‌های اصلی و شبکه عصبی مصنوعی توانستد گوجه‌فرنگی گیلاسی را به دو درجه سالم و معیوب تقسیم نماید که روش شبکه عصبی مصنوعی با کمک خصیصه‌های بافتی نمونه‌ها را با صحت بالاتری درجه‌بندی نمود (41/97 درصد). روش انفیس نسبت به دو روش دیگر قدرت تشخیصی بالاتری داشت و توانست با صحت درجه‌بندی معادل 96/98 درصد نمونه‌ها را به سه درجه سالم، درجه دو و غیرقابل مصرف درجه‌بندی نماید.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Visual grading of cherry tomatoes coated with aloe vera gel containing hemp seed oil using principal component analysis, artificial neural network and adaptive neuro-fuzzy inference system methods

نویسندگان English

Ali Ganjloo
Mohsen Zandi
Mandana Bimakr
Samaneh Monajem
Department of Food Science and Engineering, Faculty of Agriculture, University of Zanjan, Zanjan 45371-38791, Iran
چکیده English

In the present study, in the first step, the effect of Aloe vera gel (75% v/v) coating containing different concentrations of hemp seed oil (1-5% v/v) on some physicochemical properties of cherry tomatoes during storage at room temperature was investigated. The results revealed the ability of hemp seed oil to improve the physicochemical properties of cherry tomatoes during storage, although no significant difference was observed between 3 and 5% levels of hemp seed oil (p> 0.05). Slope change in the ripening index trend occurred for A. vera gel (75% v/v) coated sample on day 12 and for A. vera gel containing 3% hemp seed oil coated sample on day 16. Using an image processing system, the changes of the coated samples were evaluated based on the color statistical and color texture features extracted from the images and were graded through different procedures. The results showed that the principal component analysis (PCA) and artificial neural network (ANN) methods were able to divide the cherry tomatoes into intact and blemished grades which the ANN method was graded samples using color texture features with higher accuracy (97.41%). The adaptive neuro-fuzzy inference system (ANFIS) method had higher diagnostic power than the other two methods and was able to grade the samples into three grades including intact, grade 2 and unusable with accuracy of 98.96%.

کلیدواژه‌ها English

Image processing
Cherry tomato
Ripening index
Fuzzy Logic
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