بررسی و پیش‌بینی میزان بخش‌های اثر زیست‌محیطی در پرورش ماهیان گرم‌آبی استان گیلان با استفاده از روش‌ سامانه‌ی استنتاج عصبی-فازی تطبیقی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشیار گروه مهندسی ماشین‌های کشاورزی، دانشکده مهندسی و فناوری کشاورزی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران، کرج.

2 دانشجوی دکتری مکانیزاسیون کشاورزی، دانشکده مهندسی زراعی و عمران روستایی، دانشگاه علوم کشاورزی و منابع طبیعی خوزستان، اهواز

3 استادیار گروه مهندسی ماشین‌های کشاورزی، دانشکده مهندسی و فناوری کشاورزی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران، کرج

چکیده

در سال­های اخیر ارزیابی چرخه حیات به ابزار مناسبی جهت بررسی و تعیین میزان اثرات زیست­محیطی در تولیدات کشاورزی و صنایع غذایی تبدیل گردیده است؛ به طوری که در بسیاری از کشورها از آن به عنوان ابزاری برای تصمیم­گیری­های کلان در برنامه­­ریزی تولیدات کشاورزی استفاده می­شود. با در نظر گرفتن ماهی به‌ عنوان تأمین­کننده­ی بخش مهمی از پروتئین مورد نیاز بشر، پژوهشی بر روی بررسی شاخص­های زیست­محیطی (بخش­های اثر) در سامانه­ی تولید ماهیان ‌‌‌‌‌گرم­آبی در استان گیلان انجام گرفت. اطلاعات مربوط به میزان تولید نهاده­های مصرفی (انتشارات غیر مستقیم) و مصرف آن­ها در استخرها (انتشارات مستقیم) از طریق 57 پرسش‌نامه‌­ی نمونه­گیری شده و پایگاه داده­ای اکواینونت جمع­آوری گردید. نتایج نرمال­سازی بخش­های اثر  نشان داد که شاخص‌های مسمومیت آب­های آزاد، اسیدی شدن و مسمومیت آب­های سطحی بیشترین مقادیر آلاینده­های زیست­محیطی را به ترتیب با مقادیر 7-10×17/5، 7-10×95/1، 7-10×98/0 به خود اختصاص داد­ه­اند. انتشارات ناشی از تولید نهاده‌ی الکتریسیته (انتشارات غیر مستقیم) و آلاینده­های منتشر شده از مصرف سه نهاده­ی الکتریسیته، کودهای شیمیایی و کود دامی (انتشارات مستقیم) بیشترین سهم از میزان آلایندگی را بر روی شاخص­های مذکور داشتند. همچنین مقایسه­ی نتایج روش­های طراحی انفیس نشان داد که روش خوشه‌بندی فازی 8 خوشه‌ای­ نسبت به روش­های جداسازی شبکه­ای و خوشه­بندی کاهشی، با دقت بالاتر و خطای کمتری قادر به پیش­بینی مقادیر بخش­های اثر زیست­محیطی می­باشد. 

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Investigating and Predicting the Amount of Environmental Impact in Breeding Warm Water Fish in Guilan Province using Comparative Neuro-Fuzzy Inductive Inference System

نویسندگان [English]

  • Asadollah Akram 1
  • behzad elhami 2
  • Majid Khanali 3
1 Associate Prof., Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran.
2 PhD. Student of Agricultural Mechanization, Department of Agricultural Machinery Engineering, Agriculture Science and Natural Resources University of Ahvaz
3 Assistant Prof., Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran.
چکیده [English]

In recent years, life cycle assessment (LCA) approach is turned to be a useful tool for investigating and determining the environmental impacts of agricultural products and food industry, so that in most countries, it is used as a tool for decision-making in agricultural production planning. Considering the fish as an important part of the human protein required, an investigation was carried out on the environmental indicators (impact categories) in the system of warm water production in Guilan province. Data related to the production value of inputs (indirect emissions) and their’s consumption (direct emissions) in ponds were collected using sampled questionnaire and Ecoinvent database. The results of normalization showed that marine aquatic ecotoxicity (MAET), acidification (AC) and Freshwater Aquatic Ecotoxicity (FAET) have the highest amount of environmental pollutants as 5.17×10-7, 1.95×10-7 and 0.98×10-7, respectively. Emissions resulting from the production of electricity (direct emissions) and pollutants released from the use of electricity, chemical fertilizers and manure (indirect emissions) have the highest share of pollution on these indicators. Also, the comparison of the results of ANFIS design methods showed that the fuzzy C-means method with 8 clusters, with higher accuracy and less error, was able to predict the values of environmental impact categories.

کلیدواژه‌ها [English]

  • Life Cycle Assessment
  • fuzzy C-meansو Final Environmental Index
  • Marine Aquatic Ecotoxicity

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