Abstract
B deficiency is one of the most limiting factors for the growth of Eucalyptus spp. in Brazil, especially in the cerrado region, where there is the greatest expansion of forest production of the species. Based on multi or hyperspectral sensors and digital image processing techniques, the application in diagnosis is fast, nondestructive and local in applications with plants. Our hypothesis is that the use of orbital sensors through the spectral bands is sensitive in the diagnosis of B deficiency or toxicity in adult Eucalyptus spp. in the Brazilian Cerrado region. The main objective of this study was to discriminate the adequate levels and boron deficiency from the supervised classification with the SAM algorithm in an area with Eucalyptus spp plantation. and to verify the performance of vegetation indices in distinguishing micronutrient. The experiment was carried out at Brejo Seco Farm in the rural zone of Baixa Grande do Ribeiro municipality (Cerrado biome) in Piauí State, Brazil. Eucalyptus clones MA-2000 (from controlled pollination between Eucalyptus urophylla x Eucalyptus tereticornis) trees that were ten years old were considered. This clone is adapted to the edaphic conditions of the region. The planting occurred without amendments or fertilizers, according to a 3 m × 3 m spacing with a density of approximately 1111 plants hectare−1. The orbital images used were those of the MSI/Sentinel-2 System/sensor with Level-1C, processed with values of reflectance at the top of the atmosphere (TOA). Deficiency classifications were then performed using the spectral angle mapping (SAM) algorithm and the vegetation indices NDVI, NDRE, EVI, CI, PRSI, CCCI, MTCI and HMSSI. Subsequently, a multivariate analysis of canonical variables was performed to verify the interrelationship between boron levels and each group of variables evaluated in the experiment. From these results, it is possible to discriminate levels of deficient and adequate boron in juvenile Eucalyptus spp. based on the wavelengths of the MSI/Sentinel-2 sensor system. Vegetation indices can be used to monitor boron levels, with the normalized difference vegetation index (NDVI) being the most efficient in discriminating adequate boron levels in Eucalyptus spp. plants.
Published Version
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