دانشگاه علوم کشاورزی و منابع طبیعی گرگان

 آمار

تعداد نشریات13
تعداد شماره‌ها641
تعداد مقالات6,678
تعداد مشاهده مقاله9,127,382
تعداد دریافت فایل اصل مقاله8,582,749
Gholipoor, M., Emamgholizadeh, S., Hassanpour, H., Shahsavani, D., Shahoseini, H., Baghi, M., Karimi, A.. (1391). The optimization of root nutrient content for increased sugar beet productivity using an artificial neural network. , 6(4), 429-442. doi: 10.22069/ijpp.2012.758
M. Gholipoor; S. Emamgholizadeh; H. Hassanpour; D. Shahsavani; H. Shahoseini; M. Baghi; A. Karimi. "The optimization of root nutrient content for increased sugar beet productivity using an artificial neural network". , 6, 4, 1391, 429-442. doi: 10.22069/ijpp.2012.758
Gholipoor, M., Emamgholizadeh, S., Hassanpour, H., Shahsavani, D., Shahoseini, H., Baghi, M., Karimi, A.. (1391). 'The optimization of root nutrient content for increased sugar beet productivity using an artificial neural network', , 6(4), pp. 429-442. doi: 10.22069/ijpp.2012.758
Gholipoor, M., Emamgholizadeh, S., Hassanpour, H., Shahsavani, D., Shahoseini, H., Baghi, M., Karimi, A.. The optimization of root nutrient content for increased sugar beet productivity using an artificial neural network. , 1391; 6(4): 429-442. doi: 10.22069/ijpp.2012.758

The optimization of root nutrient content for increased sugar beet productivity using an artificial neural network

International Journal of Plant Production
مقاله 3، دوره 6، شماره 4، دی 2012، صفحه 429-442    اصل مقاله (203.84 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22069/ijpp.2012.758
نویسندگان
M. Gholipoor* 1؛ S. Emamgholizadeh2؛ H. Hassanpour3؛ D. Shahsavani4؛ H. Shahoseini1؛ M. Baghi2؛ A. Karimi1
1Department of Crop Sciences, Shahrood University of Technology, Shahrood, Iran.
2Department of Water and Soil Sciences, Shahrood University of Technology, Shahrood, Iran.
3Department of Electrical Engineering, Shahrood University of Technology, Shahrood, Iran.
4Department of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran.
چکیده
Conventional procedures are inadequate for optimizing the concentrations of
nutrients to increase the sugar yield. In this study, an artificial neural network
(ANN) was used to optimize the Ca, Mg, N, K and Na content of the storage root
to increase sugar yield (Y) by increasing both sugar content (SC) and root yield
(T). Data from three field experiments were used to produce a wide range of
variation in nutrient content, SC and T. In the training phase of the ANN, R2 was
0.91 and 0.94 for SC and T, respectively. The high R2 values obtained
demonstrating the ability of the ANN to predict SC and T. The obtained optimum
values were 0.37%, 0.35%, 0.97%, 4.67 (meq/100 g) and 0.33% for Ca, Mg, N, K
and Na, respectively. Optimization increased the potential Y by 17%.
کلیدواژه‌ها
Keywords: Artificial neural network؛ Nutrient content؛ Optimization؛ Sugar beet
آمار
تعداد مشاهده مقاله: 2,824
تعداد دریافت فایل اصل مقاله: 1,927


سامانه مدیریت نشریات علمی. طراحی و پیاده سازی از سیناوب