Abstract
ABSTRACT Remote sensing applications in agriculture are presented as a very promising reality, but research is still needed for the correct use of spectral data. The objective of this study was to evaluate the spectral-temporal patterns of eleven wheat cultivars (Triticum aestivum L.). The experiment was conducted in Cascavel, PR, in the year 2014. With the help of the GreenSeeker and FieldSpec 4 terrestrial sensors, spectral signatures were determined and the temporal profiles of the Normalized Difference Vegetation Index (NDVI) were created. Statistical differences between wheat cultivars were analysed using analysis of variance (ANOVA) and Scott-Knott test. Grain yields obtained with INSEY (In-Season Estimate of Yield) factors were correlated. NDVI normalized by degree-days accumulated from the Feekes growth stages 2 and 8 showed to be more consistent in the estimation of grain yield, explaining approximately 70% of the variation. At the Feekes stage 10.1, wheat cultivars presented different spectral patterns in the near and medium infrared bands. This suggests that these spectral bands can be used to differentiate wheat cultivars.
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