Analysis and Modeling of Yield, CO2 Emissions, and Energy for Basil Production in Iran using Artificial Neural Networks
محورهای موضوعی : Farm Managementسجاد رستمی 1 , سمیه چوبین 2 , بهرام حسین‌زاده سامانی 3 , زهرا اسمعیلی 4 , حماد ذرعی‌فروش 5
1 - گروه مهندسی مکانیک بیوسیستم، دانشگاه شهرکرد، شهرکرد، ایران
2 - گروه مهندسی مکانیک بیوسیستم، دانشگاه شهرکرد، شهرکرد، ایران
3 - گروه مهندسی مکانیک بیوسیستم، دانشگاه شهرکرد، شهرکرد، ایران
4 - گروه مهندسی مکانیک بیوسیستم، دانشگاه شهرکرد، شهرکرد، ایران
5 - گروه مهندسی مکانیزاسیون، دانشگاه گیلان، رشت، ایران
کلید واژه: Artificial Neural Networks, basil, energy flow, CO2,
چکیده مقاله :
The present study attempts to investigate the potential relationship between input energies, performance production of greenhouse basil, and greenhouse gases emitted from this product. The data were collected from 24 greenhouses using a questionnaire and verbal interaction with farmers. Results of the study showed that the total input energy and total output energy for basil production were 119,852.9 MJ/ha and 61,040 MJ/ha, respectively. The highest rate of energy consumption was related to electricity (52,200 MJ/ha), followed by plastic (23,220 MJ/ha) and chemical fertilizers (13,894 MJ/ha). The energy and productivity indices were estimated at 0.45 and 0.21, respectively, which indicated that the efficiency of energy in the agricultural sector was low. In addition, it was found that the pure energy index and total greenhouse gases emitted from basil production were equal to -722,706.9 and 9,595.6 kg (CO2), respectively. The highest emission of greenhouse gases was attributed to electricity (2,216 kg/CO2). Results of modeling proved that artificial neural networks can predict basil performance and CO2 emissions with a high degree of accuracy (R2=0.99 and MSE= 0.00023).
این مطالعه با هدف بررسی رابطه بین انرژی‌های ورودی و عملکرد تولید ریحان گلخانه‌ای و همچنین گازهای گلخانه‌ای انتشار یافته از این محصول انجام شد. داده‌ها از24 گلخانه به روش پرسشنامه‌ای و بصورت چهره به چهره با کشاورزان جمعآوری گردید. نتایج حاصل از این مطالعه نشان داد که انرژی ورودی کل 119852.9مگاژول بر هکتار وانرژی خروجی کل 61040مگاژول بر هکتار می‌باشد. بالاترین سهم از مصرف انرژی مربوط به الکتریسیته با 52200 مگاژول برهکتار و به دنبال آن پلاستیک با 23220 مگاژول بر هکتار و کودهای شیمیایی با 13894مگاژول بر هکتار قرار گرفتند. شاخص نسبت انرژی و بهره‌وری به ترتیب 45/. و21/. محاسبه شد که هر دو نشان می‌دهند کارایی انرژی در بخش کشاورزی پایین می‌باشد همچنین انرژی خالص 72706.9- برآورد شد و کل گازهای گلخانه‌ای منتشر شده از تولید ریحان 9595.6کیلوگرم معادل Co2 محاسبه شد. بیشترین انتشار گازهای گلخانه‌ای در این مطالعه مربوط به الکتریسیته با 2.216کیلوگرم معادل Co2بود. نتایج مدلسازی ثابت کرد که شبکه‌های عصبی مصنوعی می‌تواند عملکرد ریحان و انتشار گازهای گلخانه‌ایCo2 با درجه بالایی از دقت و صحت R2=0.99) و(MSE= 0.00023 پیش‌بینی کند.
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