Izadora de Cássia Mesquita da Cunha

Izadora de Cássia Mesquita da Cunha

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Izadora de Cássia Mesquita da Cunha

Federal Rural University of the Amazon (UFRA), Capitão Poço, Brazil

Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 April 2025 in Plant Stress
Verified
Journal Article
Open access
ASAna Vitória Reina da Silva
Ana Vitória Reina da Silva
ICIzadora de Cássia Mesquita Cunha
Izadora de Cássia Mesquita Cunha
TPThierry Pellegrinetti
Thierry Pellegrinetti
EBEduardo Henrique Marcandalli Boleta
Eduardo Henrique Marcandalli Boleta
LZLuis Felipe Guandalin Zagatto
Luis Felipe Guandalin Zagatto
LMLucas William Mendes
Lucas William Mendes

12 September 2024 in Agricultural Research
Verified
Journal Article
Closed access
PDF file
JSJAMILE DO NASCIMENTO SANTOS
JAMILE DO NASCIMENTO SANTOS
ICIzadora de Cássia Mesquita da Cunha
Izadora de Cássia Mesquita da Cunha
ONOdailson Rodrigues Do Nascimento
Odailson Rodrigues Do Nascimento
FRFlavio Henrique Santos Rodrigues
Flavio Henrique Santos Rodrigues
LCLuiz Antonio Soares Cardoso
Luiz Antonio Soares Cardoso
FOFábio Oliveira
Fábio Oliveira

24 April 2026 in Journal of the Indian Society of Remote Sensing
Verified
Journal Article
Open access
PDF file
DNDo Nascimento
Do Nascimento
OROdailson Rodrigues
Odailson Rodrigues
LCLuiz Antonio Soares Cardoso
Luiz Antonio Soares Cardoso
EFEric Ferreira
Eric Ferreira
EVEric Victor
Eric Victor
FOFábio Oliveira
Fábio Oliveira
Remote Sensing enables the acquisition of planting information through the spatial resolution of multispectral images obtained from Remotely Piloted Aircraft (RPA) in situ. This study aimed to evaluate the application of agricultural gypsum in citrus orchards using precision agriculture tools and image-based analysis. Multispectral images were acquired at three flight altitudes (80, 100, and 120 m) to assess their influence on canopy area delineation and the Normalized Difference Vegetation Index (NDVI). The experimental design consisted of five gypsum application rates (0.0, 0.6, 1.2, 1.8, and 2.4 t ha⁻ 1 ) applied to a citrus orchard located in Capitão Poço, Pará, Brazil. The variables analyzed were NDVI – derived from near-infrared and red reflectance bands – and canopy area, extracted from vector polygons of tree crowns. The results showed that the 0.6 t ha⁻ 1 dose yielded the greatest canopy area. Additionally, flights at 80 m altitude provided higher spatial resolution, enabling more precise delineation of citrus canopies. This enhanced detail supports improved vegetation monitoring, emphasizing the advantage of higher spatial resolution in precision agriculture.