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بررسی کیفیت گوشت و روغن مصرف شده در ناگت مرغ با استفاده از بینی الکترونیکی و پردازش تصویر | ||
| مهندسی بیوسیستم ایران | ||
| دوره 54، شماره 2، تیر 1402، صفحه 1-14 اصل مقاله (1.37 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijbse.2023.363744.665517 | ||
| نویسندگان | ||
| حافظ ازگلی1؛ سید سعید محتسبی* 2؛ سلیمان حسین پور3؛ محمد حسین پور زرنق1 | ||
| 1گروه مهندسی ماشینهای کشاورزی، دانشکدگان کشاورزی و منابع طبیعی دانشگاه تهران، دانشگاه تهران، کرج، ایران | ||
| 2استاد، گروه مهندسی ماشینهای کشاورزی، دانشکده مهندسی و فناوری کشاورزی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران | ||
| 3دانشیار، گروه مهندسی ماشینهای کشاورزی، دانشکدگان کشاورزی و منابع طبیعی دانشگاه تهران، دانشگاه تهران، کرج، ایران | ||
| چکیده | ||
| ناگت مرغ یک محصول فراوریشده از گوشت مرغ است و به دلیل عطر، طعم و رنگ خاص آن مورد توجه مصرفکنندگان است. گوشت سالم از فاکتورهای مهم کیفی ناگت هستند. در فرایند تولید، محصول به مدت 1 دقیقه با دمای 185 درجه سلسیوس و به شکل عمیق سرخشده و به همین دلیل سلامت روغن مصرفی اثر معنی‌داری بر سلامت مصرف‌کننده دارد. در این تحقیق برای اولین بار با استفاده از روش‌های خودکار و غیر مخرب بویایی الکترونیکی و بینایی ماشین کیفیت گوشت و روغن مصرف شده در ناگت مرغ بررسی شد. ویژگی سلامت گوشت (سالم و فاسد) و روغن مصرفی (سالم و سوخته) به‌عنوان شاخص کیفیت در نظر گرفته شد. پس از سرخ کردن تیمارها، روغن اضافی از نمونه‌ها گرفته‌شده، سپس نمونه‌ها عکس‌برداری شده و با ماشین بویایی مورد ارزیابی قرار گرفتند. در این تحقیق مقادیر بهینه پارامترهای مهم در سامانه بویایی الکترونیکی از جمله زمان‌های مورد نیاز جهت تشخیص بو و پاک کردن آن از سنسورها تعیین شده و همچنین اثر پاسخ هر حسگر بررسی شد. برای تحلیل و طبقه‌بندی داده‌ها روش تحلیل مؤلفه اصلی (PCA)، تحلیل تفکیک خطی (LDA) و شبکه عصبی مصنوعی (ANN) استفاده شدند. نتایج تحلیل داده‌های هر دو سامانه بینایی و بویایی مشابهت داشتند و تفکیک سلامت گوشت و روغن با دقت بالای 90 درصد انجام شد. نتایج ارزیابی بخش سامانه ماشین بویایی با نتایج سامانه ماشین بینایی همخوانی داشته است و می‌توان از ترکیب دو روش در برآورد ویژگی‌های رنگ و عطر ناگت مرغ استفاده کرد. | ||
| کلیدواژه‌ها | ||
| تحلیل تفکیک خطی؛ تحلیل مؤلفه اصلی؛ ماشین بویایی؛ ماشین بینایی؛ کیفیت روغن | ||
| عنوان مقاله [English] | ||
| Investigating meat and oil quality in chicken nuggets using electronic nose and image processing techniques | ||
| نویسندگان [English] | ||
| Hafez Ozgoli1؛ Seyed Saeid Mohtasebi2؛ Soleiman Hosseinpour3؛ Mohammad Hosseinpour-Zarnaq1 | ||
| 1Department of Agricultural Machinery Engineering, Faculty of Agriculture, School of Agriculture & Natural Resources, University of Tehran, Karaj, Iran | ||
| 2Professor, Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran | ||
| 3Associate Professor, Department of Agricultural Machinery Engineering, Faculty of Agriculture, School of Agriculture & Natural Resources, University of Tehran, Karaj, Iran | ||
| چکیده [English] | ||
| Chicken nugget is a popular processed form of chicken meat. Nugget’s special flavor and color are interesting for consumers. Healthy meat is an important quality factor of nuggets. In the production process, the nugget is deeply fried for 1 minute at 185 °C. So, oil quality has an important effect on the final quality and healthy aspects. In this research, for the first time, the meat and oil quality used in chicken nuggets was checked using automatic and non-destructive techniques including an electronic nose (E-nose) and machine vision system. Meat health (healthy and spoiled) and consumed oil (healthy and burnt) were considered quality indicators. After frying, the excess oil was removed, and then the samples were subjected to machine vision and electronic nose systems for quality evaluations. In this research, the optimum of important parameters in the E-nose and the required times for sensing and removing the odor were determined. Also, the sensors' response was investigated. Principal component analysis (PCA), linear discriminant analysis (LDA) and artificial neural network (ANN) were used to analyze and classify the data. The accuracy results of both machine vision and electronic nose systems were similar and healthy meat and healthy oil classes were detected with up to 90 % accuracy. The evaluation results of the E-nose were similar to the machine vision system. Therefore, the combination of the two methods can be used in the measurement of color and smell characteristics. | ||
| کلیدواژه‌ها [English] | ||
| Electronic nose, linear discriminant analysis, Machine vision, Oil quality, Principal component analysis | ||
| مراجع | ||
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