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Pedotransfer functions based on nearest neighbour and neural networks approach to estimate available water capacity of shrink-swell soils

Indian Agricultural Research Journals

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Title Pedotransfer functions based on nearest neighbour and neural networks approach to estimate available water capacity of shrink-swell soils
 
Creator Patil, Nitin Gorakh
CHATURVEDI, ARUN
 
Subject Available water capacity
Clay soils
K nearest neighbour
Neural networks
Pedotransfer functions
VG function
 
Description Point pedotransfer functions (PTF) were developed by nearest neighbour (kNN) algorithm as an alternative to widely used artificial neural networks (ANN) for prediction of field capacity, permanent wilting point, and available water capacity of the seasonally impounded clay soils in central India using the available dataset. They were compared with parametric PTFs to estimate Van Genuchten parameters. Basic soil properties (texture, bulk density and organic carbon content) were related to the properties of interest. The root mean square error (RMSE) in predictions of the three properties (FC, PWP, AWC) by kNN PTFs ranged from 0.0237 to 0.0279 m3/m3with an average of 0.0265 m3/m3. The ANN PTFs performed relatively better with average RMSE 0.0223 m3/m3 and a range of 0.0141 to 0.0295 m3/m3. Magnitude of RMSE was relatively higher in VG parametric PTFs (0.032 m3/m3) followed by kNN (0.0237 m3/m3) and ANN (0.0223 m3/m3) PTFs. kNN algorithm provided viable alternative to neural regression with additional benefit of flexibility in appending reference database.
 
Publisher Indian Council of Agricultural Research
 
Date 2012-01-03
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier https://epubs.icar.org.in/index.php/IJAgS/article/view/13867
10.56093/ijas.v82i1.13867
 
Source The Indian Journal of Agricultural Sciences; Vol. 82 No. 1 (2012); 35–8
2394-3319
0019-5022
 
Language eng
 
Relation https://epubs.icar.org.in/index.php/IJAgS/article/view/13867/6888
 
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