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Remote Sens. 2016, 8(12), 973; doi:10.3390/rs8120973

Analysis of Vegetation Indices to Determine Nitrogen Application and Yield Prediction in Maize (Zea mays L.) from a Standard UAV Service

1
Department of Field Crops and Forest Science, Agrotecnio Center, University of Lleida, Av. Rovira Roure 191, Lleida 25198, Spain
2
Research Group in AgroICT and Precision Agriculture, Agrotecnio Center, University of Lleida, Av. Rovira Roure 191, Lleida 25198, Spain
*
Author to whom correspondence should be addressed.
Academic Editors: Jose Moreno, Clement Atzberge and Prasad S. Thenkabail
Received: 31 August 2016 / Revised: 8 November 2016 / Accepted: 21 November 2016 / Published: 24 November 2016
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Abstract

The growing use of commercial unmanned aerial vehicles (UAV) and the need to adjust N fertilization rates in maize (Zea mays L.) currently constitute a key research issue. In this study, different multispectral vegetation indices (green-band and red-band based indices), SPAD and crop height (derived from a multispectral compact camera mounted on a UAV) were analysed to predict grain yield and determine whether an additional sidedress application of N fertilizer was required just before flowering. Seven different inorganic N rates (0, 100, 150, 200, 250, 300, 400 kg·N·ha−1), two different pig slurry manure rates (Ps) (150 or 250 kg·N·ha−1) and four different inorganic-organic N combinations (N100Ps150, N100Ps250, N200Ps150, N200Ps250) were applied to maize experimental plots. The spectral index that best explained final grain yield for the N treatments was the Wide Dynamic Range Vegetation Index (WDRVI). It identified a key threshold above/below 250–300 kg·N·ha−1. WDRVI, NDVI and crop height showed no significant response to extra N application at the economic optimum rate of fertilization (239.8 kg·N·ha−1), for which a grain yield of 16.12 Mg·ha−1 was obtained. This demonstrates their potential as yield predictors at V12 stage. Finally, a ranking of different vegetation indices and crop height is proposed to overcome the uncertainty associated with basing decisions on a single index. View Full-Text
Keywords: maize; nitrogen; multispectral vegetation indices; crop height; UAV maize; nitrogen; multispectral vegetation indices; crop height; UAV
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Maresma, Á.; Ariza, M.; Martínez, E.; Lloveras, J.; Martínez-Casasnovas, J.A. Analysis of Vegetation Indices to Determine Nitrogen Application and Yield Prediction in Maize (Zea mays L.) from a Standard UAV Service. Remote Sens. 2016, 8, 973.

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