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3 November 2005 Application of artificial neural network on analyzing relationship between soil spatial distribution information and crop yield
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Proceedings Volume 6043, MIPPR 2005: SAR and Multispectral Image Processing; 60432J (2005) https://doi.org/10.1117/12.655016
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China
Abstract
The artificial neutral network is a type of large-scale nonlinear parallelism system, capable of identifying causal relationships between complex variables. This paper presented the relationships between the winter wheat yield and the soil spatial distribution information, including water content, organic matter, total nitrogen, alkali-hydrolysable nitrogen, rapidly available phosphorus and potassium, by training 50 tested soil samples in the back-propagation neutral network of topological structure 6:9:1. After verifying the model by the remaining 13 samples, the results show that the soil water content and alkali-hydrolysable nitrogen are linear to the crop yield, the total nitrogen, organic matter and rapidly available potassium are respectively multinomial to it and that the rapidly available phosphorous is of the exponential relationship with the crop yield.
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Yong He, Yun Zhang, Shujuan Zhang, and Hui Fang "Application of artificial neural network on analyzing relationship between soil spatial distribution information and crop yield", Proc. SPIE 6043, MIPPR 2005: SAR and Multispectral Image Processing, 60432J (3 November 2005); https://doi.org/10.1117/12.655016
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