| Full text | |
| Author(s): |
Pedro Paulo da Silva Barros
[1]
;
Peterson Ricardo Fiorio
[2]
;
José Alexandre de Melo Demattê
[3]
;
Juliano Araújo Martins
[4]
;
Zaqueu Fernando Montezano
[5]
;
Fábio Luis Ferreira Dias
[6]
Total Authors: 6
|
| Affiliation: | [1] Universidade Federal de Uberlândia (UFU). Faculdade de Engenharia Civil. Campus de Monte Carmelo - Brasil
[2] Universidade de São Paulo (USP). Departamento de Engenharia de Biossistemas. Escola Superior de Agricultura “Luiz de Queiroz”, - Brasil
[3] Universidade de São Paulo (USP). Departamento de Ciência do Solo. Escola Superior de Agricultura “Luiz de Queiroz” - Brasil
[4] Instituto Federal de Mato Grosso (IFMT). Campus Sorriso - Brasil
[5] Innovak Global - Brasil
[6] Instituto Agronômico de Campinas (IAC) - Brasil
Total Affiliations: 6
|
| Document type: | Journal article |
| Source: | Ciência Rural; v. 52, n. 7 2021-11-29. |
| Abstract | |
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, Jaú, and Santa Maria da Serra, state of São 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 R² and RMSE of the model were 0.50 and 1.67 g.kg-1, respectively. The adjusted R² and RMSE of the models for Piracicaba, Jaú, 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 1.46 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: | 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 |
| 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 |