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Assessing biophysical variable parameters of bean crop with hyperspectral measurements
Ferraz Câmara Monteiro, Priscylla; Angulo Filho, Rubens; Cândido Xavier, Alexandre; Otávio Câmara Monteiro, Rodrigo.
Affiliation
  • Ferraz Câmara Monteiro, Priscylla; USP ESALQ Depto. de Engenharia de Biossistemas.
  • Angulo Filho, Rubens; USP ESALQ Depto. de Engenharia de Biossistemas.
  • Cândido Xavier, Alexandre; UFES Depto. de Engenharia Rural.
  • Otávio Câmara Monteiro, Rodrigo; USP ESALQ Depto. de Engenharia de Biossistemas.
Sci. agric ; 69(2)2012.
Article in En | LILACS-Express | VETINDEX | ID: biblio-1497265
Responsible library: BR68.1
ABSTRACT
Recently high spectral resolution sensors have been developed, which allow new and more advanced applications in agriculture. Motivated by the increasing importance of hyperspectral remote sensing data, the need for research is important to define optimal wavebands to estimate biophysical parameters of crop. The use of narrow band vegetation indices (VI) derived from hyperspectral measurements acquired by a field spectrometer was evaluated to estimate bean (Phaseolus vulgaris L.) grain yield, plant height and leaf area index (LAI). Field canopy reflectance measurements were acquired at six bean growth stages over 48 plots with four water levels (179.5; 256.5; 357.5 and 406.2 mm) and tree nitrogen rates (0; 80 and 160 kg ha-1) and four replicates. The following VI was analyzed OSNBR (optimum simple narrow-band reflectivity); NB_NDVI (narrow-band normalized difference vegetation index) and NDVI (normalized difference index). The vegetation indices investigated (OSNBR, NB_NDVI and NDVI) were efficient to estimate LAI, plant height and grain yield. During all crop development, the best correlations between biophysical variables and spectral variables were observed on V4 (the third trifoliolate leaves were unfolded in 50 % of plants) and R6 (plants developed first flowers in 50 % of plants) stages, according to the variable analyzed.
Key words
Full text: 1 Database: VETINDEX Language: En Journal: Sci. agric Year: 2012 Document type: Article
Full text: 1 Database: VETINDEX Language: En Journal: Sci. agric Year: 2012 Document type: Article