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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 | ||
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