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Delineation of management zones based on the Rasch model in an olive orchard

Published online by Cambridge University Press:  01 June 2017

F.J. Rebollo ,
F.J. Moral ,
C. Campillo ,
J.R. Marques da Silva ,
J.M. Serrano  and
J.M. Pérez-Rodríguez
F.J. Rebollo*
Affiliation:
Departamento de Expresión Gráfica, Escuela de Ingenierías Agrarias, Universidad de Extremadura. Avda. Adolfo Suárez s/n, 06007 Badajoz, Spain
F.J. Moral
Affiliation:
Departamento de Expresión Gráfica, Escuela de Ingenierías Industriales, Universidad de Extremadura. Avenida de Elvas s/n, 06006 Badajoz, Spain
C. Campillo
Affiliation:
Centro de Investigaciones Científicas y Tecnológicas de Extremadura (CICYTEX), Junta de Extremadura. 06187 Guadajira, Badajoz, Spain
J.R. Marques da Silva
Affiliation:
Departamento de Engenharia Rural, Instituto de Ciências Agrárias e Ambientais Mediterrânicas (ICAAM), Escola de Ciências e Tecnologia, Universidade de Évora, Apartado 94, 7002-554 Évora, Portugal
J.M. Serrano
Affiliation:
Departamento de Engenharia Rural, Instituto de Ciências Agrárias e Ambientais Mediterrânicas (ICAAM), Escola de Ciências e Tecnologia, Universidade de Évora, Apartado 94, 7002-554 Évora, Portugal
J.M. Pérez-Rodríguez
Affiliation:
Centro de Investigaciones Científicas y Tecnológicas de Extremadura (CICYTEX), Junta de Extremadura. 06187 Guadajira, Badajoz, Spain
*
† E-mail: frebollo@unex.es
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Abstract

The probabilistic Rasch model is used to get objective measures of production potential at some locations of an olive orchard located in Badajoz, southwestern Spain. Nine soil properties (soil apparent electrical conductivity, clay, sand, and silt content, organic matter, total nitrogen, available phosphorous and potassium, and cation exchange capacity), taken at 40 locations in the field, were considered and, after being integrated in the model, a ranking of all locations according to the soil production potential and the influence on the production potential of each individual soil property were determined. Moreover, those soil samples or properties which had any anomaly where highlighted; this information can be necessary to conduct site-specific treatments, leading to a more cost-effective and sustainable field management. Additionally, estimates using geostatistical algorithms were utilised to map soil production potential and to delineate with a rational basis the management zones in the field.

Keywords

predictive mapprobabilistic modelsoil production.
Type
Data analysis and Geostatistics
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 610 - 614
Copyright
© The Animal Consortium 2017 

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