توسعه و ارزیابی سامانه غیر‌مخرب تلفیقی امواج فراصوت، سنجش مقاومت و رنگ سنجی برای تعیین ویژگی‌های بافتی فیله ماهی قزل‌آلای رنگین کمان Oncorhynchus mykiss)) در طول دوره نگهداری در یخچال

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجو دکتری بخش مهندسی مکانیک بیوسیستم دانشگاه شیراز

2 بخش مهندسی بیوسیستم، دانشگاه شیراز

3 بخش مهندسی منابع طبیعی و محیط زیست، دانشگاه شیراز

4 خش علوم و صنایع غذایی و گروه پژوهشی فرآوری آبزیان ، دانشگاه شیراز

5 دانشیار ، بخش مهندسی بیوسیستم، دانشگاه شیراز

10.22104/jift.2020.4026.1944

چکیده

در این پژوهش توانایی سامانه تلفیقی غیرمخرب امواج فراصوت، سنجش مقاومت الکتریکی و رنگ سنجی برای تعیین کیفیت فیله ماهی‌ قزل‌آلا طی مدت نگهداری (12 روز) با تعیین ویژگی‌های بافتی (سختی، شکنندگی، چسبناکی، قابلیت ارتجاعی، صمغی بودن و قابلیت جویدن) مورد بررسی و ارزیابی قرار گرفت. هم زمان آزمایش‌های فیزیکی، مکانیکی، شیمیایی و حسی روی فیله‌ها انجام شد. عملکرد روش‌های شبکه عصبی و ماشین‌ بردار پشتیبان برای پیش‌بینی و مدل‌سازی خصوصیات بافتی مورد مقایسه قرار گرفتند. در هریک از مدل‌ها خصوصیات فیزیکی به عنوان ورودی و خصوصیات بافتی به عنوان خروجی در نظر گرفته شده و مدل‌سازی‌ها انجام گرفت. نتایج نشان داد در پیش‌بینی شاخص‌های سختی، شکنندگی و قابلیت ارتجاعی روش ماشین بردار پشتیبان و در شاخص‌های چسبناکی، صمغی بودن و قابلیت جویدن، روش شبکه عصبی توانمندی بیشتری برای مدل‌سازی ویژگی های بافتی را دارا بودند، به طوری که ریشه میانگین مربعات خطا (RMSE) شاخص‌های سختی، شکنندگی، چسبناکی، قابلیت ارتجاعی، صمغی بودن و قابلیت جویدن به ترتیب برابر 114/0، 025/0، 015/0، 015/0، 044/0 و 171/0 و ضریب همبستگی آنها نیز به ترتیب برابر 993/0، 985/0، 992/0، 961/0، 995/0 و 995/0 است. بنابراین سامانه پیشنهادی غیرمخرب در ترکیب با روش‌های هوش مصنوعی به عنوان ابزاری غیرمخرب و کارآمد برای پایش و کنترل کیفیت در طول نگهداری فیله ماهی قزل‌آلا ارائه می‌شود.

چکیده تصویری

توسعه و ارزیابی سامانه غیر‌مخرب تلفیقی امواج فراصوت، سنجش مقاومت و رنگ سنجی برای تعیین ویژگی‌های بافتی فیله ماهی قزل‌آلای رنگین کمان Oncorhynchus mykiss)) در طول دوره نگهداری در یخچال

تازه های تحقیق

  • توسعه و ارزیابی سامانه ای که هم غیرمخرب باشد و هم اینکه به صورت ترکیبی و تلفیق چند روش فیزیکی می باشد.
  • استفاده از دو روش برای پیش بینی (شبکه عصبی مصنوعی و ماشین بردار پشتیبان) و مقایسه عملکرد آنها.
  • تعیین ویژگی های بافتی محصولات غذایی با استفاده از روش های مرسوم، هم زمان بر بوده و هم مخرب، اما استفاده از روش های فیزیکی استفاده شده در این مقاله در کمترین زمان ممکن و بیشترین دقت قادر است که ویژگی های بافتی ماهی  را پیش بینی کند.   

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Development and Evaluation of Integrated Non-Destructive Ultrasound, Resistance and Colorimetric System for Determination of Texture Properties of Rainbow Trout Fillet (Oncorhynchus mykiss) During Refrigeration

نویسندگان [English]

  • hasan safiyari 1
  • Seyed Mehdi Nassiri 2
  • Mahmood Naseri 3
  • Marzieh Moosavi-Nasab 4
  • Abdolabbas Jafari 5
2 Biosystems Engineering Department Shiraz University Shiraz, Iran
3 Department of Natural Resources and Environmental Engineering, Shiraz University, Shiraz, Iran.
4 Department of Food Science & Technology, Shiraz University, Shiraz, Iran.
5 Department of Biosystems Engineering, Shiraz University, Shiraz, Iran.
چکیده [English]

In this research, the ability of the integrated non-destructive system including ultrasound, electrical resistance measurements and colorimetric assays to predict the textural properties (hardness, brittleness, viscosity, elasticity, guminess and chewiness) of trout fillets were evaluated. For this purpose, fillets were stored for 12 days at refrigerator temperature and then examined at interval times. At the same time physical, mechanical, chemical and sensory tests were performed on the fillets. The performance of neural network and support vector machine methods for predicting and modeling tissue properties were compared. In each model, physical properties were considered as inputs and textural properties as outputs and modeling was performed. The results showed that in the prediction of hardness, fragility and elasticity of the support vector machine and in the viscous, resin and chewability indices, the neural network method had more capability to model the texture properties, so that the root mean square error (RMSE) Hardness, fragility, viscosity, elasticity, gum and chewability indices were equal to 0.144, 0.025, 0.015, 0.015, 0.044 and 0.171 respectively and their correlation coefficients were equal 0.993, 0.985, 0.992, 0.961, 0.995 and 0.995. Therefore, the proposed non-destructive system in combination with artificial intelligence methods showed promises as a non-destructive and efficient tool for monitoring and quality control during trout fillet storage.

کلیدواژه‌ها [English]

  • Non-destructive
  • Rainbow trout (Oncorhynchus mykiss)
  • Texture properties
  • Ultrasound
  • Resistance
  • colorimetric
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