Abstract
Careful monitoring of an agricultural area has great importance for the managing of three main objectives (economics, society, environment) of sustainable agriculture. Understanding of site specific factors influencing yield will make valuable contributions to these objectives for effective decision-making on the beneficial use of soil resources. On the other hand, easy measuring levels without expensive should be developed for determining of more precise relationships among the site specific factors. In this study, simulations of spatial variability of organic matter contents of soils on the vineyard area were made using the model of Artificial Neural Networks (ANN). ANN is modeling method which is improved by the inspiration of brain physiology of human beings. The method is generally successful in issues such as model selection and classification. For this aim, topsoil (0–30 cm), subsoil (30–60 cm) and plant samples based on a 20×20 m grids were collected from the plots under the vineyard plants. The study area was modeled with 5 meters period, and generally non linear organic matter value of soil has been modeled by using ANN. A program was build by C++ programming language to solve data by ANN method. As a result, the coefficient of variance (C.V.), kurtosis and skewness values revealed that considerable spatial variability occurred in organic matter contents of soils. Hence, uniform nitrogen (N) fertilizer managements based on an average soil organic matter level will result in increasing unequal soil N distribution and unbalanced plant N consumption. Hence, simulation results showed very good agreement with the measured results. It has been figured out that ANN based modeling will be alternative for other modeling methods. It has also been revealed that the problems for intensive soil samplings depending on site specific variability could be decreased by using the model of ANN. It will be valuable for the sustainability of agro-ecosystems, and more realistic crop nutrition modeling and decision support on farm applications.
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© 2009 Tsinghua University Press, Beijing and Springer-Verlag Berlin Heidelberg
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Karaman, M.R., Dursun, M., Karkacier, O., Şahin, S. (2009). Simulation of Spatial Variability of Organic Matter on the Vineyard Area Using the Model of Artificial Neural Networks. In: Cao, W., White, J.W., Wang, E. (eds) Crop Modeling and Decision Support. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01132-0_33
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