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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

stimation of leaf nitrogen levels in sugarcaneusing hyperspectral model

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Author(s):
da Silva Barros, Pedro Paulo [1] ; Fiorio, Peterson Ricardo [2] ; de Melo Dematte, Jose Alexandre [3] ; Martins, Juliano Araujo [4] ; Montezano, Zaqueu Fernando [5] ; Ferreira Dias, Fabio Luis [6]
Total Authors: 6
Affiliation:
[1] Univ Fed Uberlandia UFU, Fac Engn Civil, Campus Monte Carmelo, BR-38500000 Monte Carmelo, MG - Brazil
[2] Univ Sao Paulo, Dept Engn Biossistemas, Escola Super Agr Luiz de Queiroz, Piracicaba, SP - Brazil
[3] Univ Sao Paulo, Escola Super Agr Luiz de Quciroz, Dept Ciencia Solo, Piracicaba, SP - Brazil
[4] Inst Fed Mato Grosso IFMT, Campus Sorriso, Sorriso, MT - Brazil
[5] Innovak Global, Campinas, SP - Brazil
[6] Inst Agron Campinas IAC, Campinas, SP - Brazil
Total Affiliations: 6
Document type: Journal article
Source: Ciência Rural; v. 52, n. 7 2022.
Web of Science Citations: 0
Abstract

Sugarcane is a good source of renewable energy and helps reduce the emission of greenhouse gases. Nitrogen has a critical role in plant growth: therefore,estimating nitrogen levels is essential. and remote sensing can improve fertilizer management. This field study selects wavelengths from hyperspectral data on a sugarcane canopy to generate models for estimating leaf nitrogen concentrations. The study was carried out in the municipalities of Piracicaba, Jau, and Santa Maria da Serra, state of Sao Paulo, in the 2013/2014 growing season. The experiments were carried out using a completely randomized block design with split plots (three sugarcane varieties per plot {[}variety SP 81-3250 was common to all plots] and four nitrogen concentrations {[}0, 50, 100, and 150 kgha(-1)] per subplot) and four repetitions. The wavelengths that best correlated with leaf nitrogen were selected usingsparse partial least square regression. The wavelength regionswere combinedby stepwise multiple linear regression. Spectral bands in the visible (700-705 nm), red-edge (710-720 nm). near-infrared (725, 925, 955, and 980 nm). and short-wave infrared (1355, 1420, 1595, 1600, 1605, and 1610 nm) regions were identified. The R-2 and RAISE of the model were 0.50 and 1.67 g.kg(-1), respectively. The adjusted R-2 and RAISE of the models for Piracicaba, Jau, and Santa Maria were 0.31 (unreliable) and 1.30 g.kg(-1), 0.53 and 1.96 g.kg(-1), and 0.54 and /.46 g.kg(-1), respectively. Our results showed that canopy hyperspectral reflectance can estimate leaf nitrogen concentrations and manage nitrogen application in sugarcane. (AU)

FAPESP's process: 13/22435-9 - Hyperspectral data use for prediction of leaf nitrogen content in sugarcane
Grantee:Peterson Ricardo Fiorio
Support Opportunities: Program for Research on Bioenergy (BIOEN) - Regular Program Grants
FAPESP's process: 08/56147-1 - Nitrogen nutrition of sugarcane with fertilizers or diazotrophic bacteria
Grantee:Heitor Cantarella
Support Opportunities: Program for Research on Bioenergy (BIOEN) - Thematic Grants