Vegetation indices in the prediction of biomass and grain yield of white oat under irrigation levels

Author:

Coelho Anderson Prates1,Rosalen David Luciano1,Faria Rogério Teixeira de1

Affiliation:

1. Universidade Estadual Paulista, Brasil

Abstract

ABSTRACT Vegetation indices are widely used to indicate the nutritional status of crops, as well as to estimate their harvest yield. However, their accuracy is influenced by the phenological stage of evaluation and the index used. The present study aimed to evaluate the accuracy of the Normalized Difference Vegetation Index (NDVI) and Inverse Ratio Vegetation Index (IRVI) in the prediction of grain yield and biomass of white oat cultivated under irrigation levels, besides indicating the best phenological stage for evaluation. The irrigation levels consisted of 11 %, 31 %, 60 %, 87 % and 100 % of the maximum evapotranspiration, with four replicates. The mean values for NDVI and IRVI were determined using an active terrestrial sensor, at four phenological stages (4, 8, 10 and 10.5.4). The white oat grain yield and biomass may be estimated with a high precision using the NDVI and IRVI. The NDVI was more accurate than the IRVI. The grain yield estimate was more accurate from the flag leaf sheath appearance stage (10), whereas, for the biomass, the best estimate was for the kernel watery ripe stage (10.5.4).

Publisher

FapUNIFESP (SciELO)

Subject

Agronomy and Crop Science

Reference37 articles.

1. Crop evapotranspiration: guidelines for computing crop water requirements;ALLEN R. G.,1998

2. Köppen's climate classification map for Brazil;ALVARES C. A.;Meteorologische Zeitschrift,2013

3. Identifying influential data and sources of collinearity: regression diagnostics;BELSLEY D. A.,1980

4. Forecasting crop yield using remotely sensed vegetation indices and crop phenology metrics;BOLTON D. K.;Agricultural and Forest Meteorology,2013

5. Estimativa do potencial produtivo em trigo utilizando sensor óptico ativo para adubação nitrogenada em taxa variável;BREDEMEIER C.;Ciência Rural,2013

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