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Delineating site-specific management zones for precision agriculture

Published online by Cambridge University Press:  08 May 2015

H. U. FARID ,
A. BAKHSH ,
N. AHMAD ,
A. AHMAD  and
Z. MAHMOOD-KHAN
H. U. FARID*
Affiliation:
Department of Agricultural Engineering, Bahauddin Zakriya University, Multan, Pakistan
A. BAKHSH
Affiliation:
Department of Irrigation and Drainage, University of Agriculture, Faisalabad, Pakistan
N. AHMAD
Affiliation:
Per Mer Ali Shah Arid Agriculture University, Rawalpindi, Pakistan
A. AHMAD
Affiliation:
Department of Agronomy, University of Agriculture, Faisalabad, Pakistan
Z. MAHMOOD-KHAN
Affiliation:
Department of Agricultural Engineering, Bahauddin Zakriya University, Multan, Pakistan
*
*To whom all correspondence should be addressed. Email: farid_vjr@yahoo.com
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Summary

Delineating site-specific management zones within fields can be helpful in addressing spatial variability effects for adopting precision farming practices. A 3-year (2008/09 to 2010/11) field study was conducted at the Postgraduate Agricultural Research Station, University of Agriculture, Faisalabad, Pakistan, to identify the most important soil and landscape attributes influencing wheat grain yield, which can be used for delineating management zones. A total of 48 soil samples were collected from the top 300 mm of soil in 8-ha experimental field divided into regular grids of 24 × 67 m prior to sowing wheat. Soil and landscape attributes such as elevation, % of sand, silt and clay by volume, soil electrical conductivity (EC), pH, soil nitrogen (N) and soil phosphorus (P) were included in the analysis. Artificial neural network (ANN) analysis showed that % sand, % clay, elevation, soil N and soil EC were important variables for delineating management zones. Different management zone schemes ranging from three to six were developed and evaluated based on performance indicators using Management Zone Analyst (MZA V0·1) software. The fuzziness performance index (FPI) and normalized classification entropy NCE indices showed minimum values for a four management zone scheme, indicating its appropriateness for the experimental field. The coefficient of variation values of soil and landscape attributes decreased for each management zone within the four management zone scheme compared to the entire field, which showed improved homogeneity. The evaluation of the four management zone scheme using normalized wheat grain yield data showed distinct means for each management zone, verifying spatial variability effects and the need for its management. The results indicated that the approach based on ANN and MZA software analysis can be helpful in delineating management zones within the field, to promote precision farming practices effectively.

Information

Type
Crops and Soils Research Papers
Information
The Journal of Agricultural Science , Volume 154 , Issue 2 , March 2016 , pp. 273 - 286
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Copyright
Copyright © Cambridge University Press 2015 

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