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Unmanned Aerial Vehicle to Estimate Nitrogen Status of Turfgrasses.

Authors :
Caturegli, Lisa
Corniglia, Matteo
Gaetani, Monica
Grossi, Nicola
Magni, Simone
Migliazzi, Mauro
Angelini, Luciana
Mazzoncini, Marco
Silvestri, Nicola
Fontanelli, Marco
Raffaelli, Michele
Peruzzi, Andrea
Volterrani, Marco
Source :
PLoS ONE. 6/24/2016, Vol. 11 Issue 6, p1-13. 13p.
Publication Year :
2016

Abstract

Spectral reflectance data originating from Unmanned Aerial Vehicle (UAV) imagery is a valuable tool to monitor plant nutrition, reduce nitrogen (N) application to real needs, thus producing both economic and environmental benefits. The objectives of the trial were i) to compare the spectral reflectance of 3 turfgrasses acquired via UAV and by a ground-based instrument; ii) to test the sensitivity of the 2 data acquisition sources in detecting induced variation in N levels. N application gradients from 0 to 250 kg ha-1 were created on 3 different turfgrass species: Cynodon dactylon x transvaalensis (Cdxt) ‘Patriot’, Zoysia matrella (Zm) ‘Zeon’ and Paspalum vaginatum (Pv) ‘Salam’. Proximity and remote-sensed reflectance measurements were acquired using a GreenSeeker handheld crop sensor and a UAV with onboard a multispectral sensor, to determine Normalized Difference Vegetation Index (NDVI). Proximity-sensed NDVI is highly correlated with data acquired from UAV with r values ranging from 0.83 (Zm) to 0.97 (Cdxt). Relating NDVI-UAV with clippings N, the highest r is for Cdxt (0.95). The most reactive species to N fertilization is Cdxt with a clippings N% ranging from 1.2% to 4.1%. UAV imagery can adequately assess the N status of turfgrasses and its spatial variability within a species, so for large areas, such as golf courses, sod farms or race courses, UAV acquired data can optimize turf management. For relatively small green areas, a hand-held crop sensor can be a less expensive and more practical option. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19326203
Volume :
11
Issue :
6
Database :
Academic Search Index
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
116388133
Full Text :
https://doi.org/10.1371/journal.pone.0158268