Banca de QUALIFICAÇÃO: VITÓRIA CÔRTES DA SILVA SOUZA DE OLIVEIRA

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : VITÓRIA CÔRTES DA SILVA SOUZA DE OLIVEIRA
DATE: 13/12/2022
TIME: 10:00
LOCAL: Departamento de Engenharia/IT
TITLE:

ESTIMATE OF BIOPHYSICAL ATTRIBUTES OF FORAGE TIFTON85 USING DIFFERENT LEVELS OF REMOTE SENSING

KEY WORDS:

forage crops, vegetation index; UAV; Spectroradiometer

PAGES: 37
BIG AREA: Ciências Agrárias
AREA: Engenharia Agrícola
SUMMARY:

With technological advances and the need to increase the efficiency of the production process, the Precision agriculture emerges as an alternative for better planning and management of production as it provides infinite benefits with good productivity, sustainability and economic development. In this sense, remote sensing techniques have been widely used instantly and at low cost, playing an important role in diagnostics such as productivity estimation and biophysical parameters. The objective of this research will be to evaluate the spectral responses of Tifton 85 grass at different growth stages and generate models capable of estimating forage attributes from remote sensing techniques. The experiment will be arranged in a completely randomized statistical design, with 5 nitrogen fertilization levels 0, 50, 100, 150 and 200 kg.ha^-1. The experiment will take place in a 45-day interval, with routine collections every 9 days (5 collection times). There will be 20 measurements in each range in each epoch of analysis. The tracks for each level of fertilization will be 10x100 m and a distance of 5.0 m between lanes, totaling an experimental area of 0.7 ha. in every season the following biophysical attributes will be collected in the field: o Leaf area index, plant height, chlorophyll content and biomass. Concomitantly, the spectral responses will be obtained through a spectroradiometer and UAV. Then the vegetation indices will be calculated related to the biophysical attributes of cultures aiming at the generation of estimation models. Simple linear regression will be performed to obtain models that allow estimating the attributes biophysical data from the IVs in a univariate way, a regression will also be performed by main components to generate estimation models of biophysical attributes from the IVs in multivariate form. In the case of biomass, the IVs obtained in each season will be related with the final biomass values, making it possible to generate prediction models. Wait at the end of project to generate models capable of estimating biophysical attributes and predicting the final biomass of the crop Tifton85 grass under different fertilization conditions based on spectral characteristics highlighting which level of remote sensing is most appropriate.

COMMITTEE MEMBERS:
Presidente - 2161955 - ANDERSON GOMIDE COSTA
Interno - 1050615 - MURILO MACHADO DE BARROS
Externo ao Programa - 1698763 - RICARDO VILAR NEVES - UFRRJ