title: Unmanned Aerial Vehicle to Estimate Nitrogen Status of Turfgrasses.
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.
authors.affiliation: Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.
authors.forename: Lisa
authors.identifier: http://orcid.org/0000-0001-9749-2352
authors.initials: L
authors.lastname: Caturegli
authors.affiliation: Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.
authors.forename: Matteo
authors.initials: M
authors.lastname: Corniglia
authors.affiliation: Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.
authors.forename: Monica
authors.initials: M
authors.lastname: Gaetani
authors.affiliation: Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.
authors.forename: Nicola
authors.initials: N
authors.lastname: Grossi
authors.affiliation: Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.
authors.forename: Simone
authors.initials: S
authors.lastname: Magni
authors.affiliation: GLOBI Hi-Tech Srl, Genova, Italy.
authors.forename: Mauro
authors.initials: M
authors.lastname: Migliazzi
authors.affiliation: Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.
authors.forename: Luciana
authors.initials: L
authors.lastname: Angelini
authors.affiliation: Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Mazzoncini
authors.affiliation: Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.
authors.forename: Nicola
authors.initials: N
authors.lastname: Silvestri
authors.affiliation: Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Fontanelli
authors.affiliation: Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.
authors.forename: Michele
authors.initials: M
authors.lastname: Raffaelli
authors.affiliation: Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.
authors.forename: Andrea
authors.initials: A
authors.lastname: Peruzzi
authors.affiliation: Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Volterrani
mesh_terms: D009584:Nitrogen; D009747:Nutritional Physiological Phenomena; D006109:Poaceae; D058998:Remote Sensing Technology
chemical_list: D009584:Nitrogen