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Monitoring crop N status by using red edge-based indices

Published online by Cambridge University Press:  01 June 2017

J. González-Piqueras ,
H. Lopez-Corcoles ,
S. Sánchez ,
J. Villodre ,
V. Bodas ,
I. Campos ,
A. Osann  and
A. Calera
J. González-Piqueras*
Affiliation:
GIS and Remote Sensing Group. Instituto de Desarrollo Regional. Universidad de Castilla-La Mancha. Campus Universitario SN. Albacete, Spain
H. Lopez-Corcoles
Affiliation:
Instituto Técnico Agronómico Provincial (ITAP) and FUNDESCAM, Avda. Gregorio Arcos 19, 02005 Albacete, Spain
S. Sánchez
Affiliation:
GIS and Remote Sensing Group. Instituto de Desarrollo Regional. Universidad de Castilla-La Mancha. Campus Universitario SN. Albacete, Spain
J. Villodre
Affiliation:
GIS and Remote Sensing Group. Instituto de Desarrollo Regional. Universidad de Castilla-La Mancha. Campus Universitario SN. Albacete, Spain
V. Bodas
Affiliation:
Aliara Agrícola S.L. Calle Matadero 11. 45600. Talavera de La Reina (Toledo). Spain.
I. Campos
Affiliation:
GIS and Remote Sensing Group. Instituto de Desarrollo Regional. Universidad de Castilla-La Mancha. Campus Universitario SN. Albacete, Spain
A. Osann
Affiliation:
GIS and Remote Sensing Group. Instituto de Desarrollo Regional. Universidad de Castilla-La Mancha. Campus Universitario SN. Albacete, Spain
A. Calera
Affiliation:
GIS and Remote Sensing Group. Instituto de Desarrollo Regional. Universidad de Castilla-La Mancha. Campus Universitario SN. Albacete, Spain
*
† E-mail: [email protected]
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Abstract

Intensive agriculture has the objective to increase nutrients use efficiency. Nitrogen (N) is a key nutrient for crops and the estimations of crop N status allow adjusting the fertilization levels to crop requirements, while reducing the environmental costs and optimizing the benefits for farmers. In this work the N status of wheat in a commercial plot has been monitored, varying the N supply taking into account the variability of the soil. The N content in the cover has been monitored simultaneously by sampling at field level and by using vegetation indices based on reflectance in the red-edge band. The results of the field campaign along a crop growth cycle show that the REP, MTCI, AIVI and CCCI calculated from narrow spectral bands show good linear correlations (R2>0.93) with respect to N content (g·m−2). These indices are stable when passing to broad bands as the case of Sentinel 2 with R2>0.9.

Keywords

Nitrogenred-edgevegetation indexchlorophyll
Type
Precision Nitrogen
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. 338 - 342
Copyright
© The Animal Consortium 2017 

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