Energy Flows Modeling and Economic Evaluation of Watermelon Production in Fars Province of Iran

محورهای موضوعی : Farming Systems

Sajad Rostami ¹ ( Assistant Professor, Department of Mechanics of Biosystem Shahrekord University )
Maryam Lotfalian ² ( Department of Mechanics of Biosystem Shahrekord University )
Bahram Hosseinzadeh ³ ( Department of mechanics of biosystem engineering, Shahrekord University )
مهدی قاسمی ورنامخستی ⁴ ( Assistant Professor, Department of Mechanics of Biosystem Shahrekord University )

تاریخ دریافت : 1395/08/04 تاریخ پذیرش : 1396/08/21 تاریخ انتشار : 1396/12/10

کلید واژه: Artificial Neural Networks, Conservation, Energy use efficiency, Mechanized,

چکیده مقاله :

This study aimed to evaluate the efficiency of energy consumption and economic analysis of different watermelon cultivation systems in Fars Province of Iran. Watermelon production systems were classified into five systems, namely, custom tillage (group 1), conservation tillage (group 2), traditional planting (group3), semi mechanized planting (group 4), and mechanized planting (group 5). Data were collected from 317 watermelon producers from different parts of the province through face to face interviews. Multi-Layer Perceptron artificial neural networks were used to model the energy flows of watermelon production. The results showed that the greatest energy consumption belonged to mechanized planting system with the value of 81317.72 MJha-1 and with the productivity of 0.61 kgha-1and energy use efficiency of 1.17. Clustering function with three inputs (human resources, machines and diesel fuel) showed that the difference between groups 2 and 4 is more than the other groups. The least energy consumption belonged to the conservative agriculture as78163.86 MJha-1and the energy productivity and energy use efficiency about 0.64 kgha-1 and 1.22, respectively. The results of energy modeling showed that an ANN model with 9-10-1 structure was determined to be optimal for energy flow modeling of this system. Generally, it was concluded that the artificial neural network models can be applicable to prognosticate the energy flows of watermelon production. From an economic point of view, the least net profit belonged to traditional planting with the value of 2618.14$, and the most net return belonged to mechanized planting with the value of 2752.88$/ha.

چکیده انگلیسی:

این مطالعه با هدف بررسی بهره‌وری انرژی مصرفی و آنالیز اقتصادی روش‌های مختلف کشت هندوانه در استان فارس، کشور ایران انجام شد. روش‌های تولید هندوانه به پنج گروه تقسیم شدند. این گروه‌ها عبارت بودند از: خاکورزی مرسوم (گروه 1)، کشاورزی حفاظتی (گروه 2)، پاشش کود مکانیزه (گروه 3)، کاشت نیمه مکانیزه (گروه 4) و کاشت تمام مکانیزه (گروه 5). داده‌ها از 317 نفر از تولید کننده‌های هندوانه از مناطق مختلف استان به صورت چهره به چهره جمع‌آوری شد. از شبکه‌های عصبی مصنوعی چند لایه برای مدل‌سازی جریان انرژی تولید هندوانه استفاده شد. نتایج نشان داد که بیشترین مصرف انرژی متعلق به روش کاشت تمام مکانیزه با ارزش MJ.ha-172/81317 و با بهره‌وری kg.ha-1 61/0 و کارایی مصرف انرژی 17/1 بوده است. نتایج خوشه‌بندی با سه ورودی (منابع انسانی، ماشین‌آلات و سوخت دیزل) نشان داد که تفاوت بین گروه‌های 2 و 4 بیشتر از گروه‌های دیگر است. کمترین مصرف انرژی نیز برای گروه کشاورزی حفاظتی به میزان MJ.ha-1 86/78163 ، با بهره‌وری kg.ha-1 64/0 و راندمان انرژی 22/1 برآورد شد. نتایج مدل‌سازی انرژی نشان داد که مدل ANN با ساختار 1-10-9 برای مدل‌سازی انرژی جریان انرژی این سیستم است. به طور کلی، نتیجه‌گیری شد که مدل‌های شبکه عصبی مصنوعی می­تواند برای پیش‌بینی جریان‌های انرژی هندوانه استفاده شود. از منظر اقتصادی نیز کمترین سود خالص متعلق به روش کاشت کاملاً سنتی به میزان 82784 هزار ریال در هکتار و بیشترین آن نیز متعلق به گروه کاشت تمام مکانیزه به میزان 87092 هزار ریال در هکتار محاسبه شد.

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