Optimizing nitrogen estimates in common bean canopies throughout key growth stages via spectral and textural data from unmanned aerial vehicle (UAV) multispectral imagery.

CASTILHO, D.; MADARI, B. E.; CARVALHO, M. da C. S.; FERREIRA, M. E.; DIOGO CASTILHO, UNIVERSIDADE FEDERAL DE GOIÁS; BEATA EMOKE MADARI, CNPAF; MARIA DA CONCEICAO SANTANA CARVALHO, CNPAF; MANUEL EDUARDO FERREIRA, UNIVERSIDADE FEDERAL DE GOIÁS.

Optimizing nitrogen estimates in common bean canopies throughout key growth stages via spectral and textural data from unmanned aerial vehicle (UAV) multispectral imagery.

2025

CASTILHO, D. | MADARI, B. E. | CARVALHO, M. da C. S. | FERREIRA, M. E. | DIOGO CASTILHO, UNIVERSIDADE FEDERAL DE GOIÁS; BEATA EMOKE MADARI, CNPAF; MARIA DA CONCEICAO SANTANA CARVALHO, CNPAF; MANUEL EDUARDO FERREIRA, UNIVERSIDADE FEDERAL DE GOIÁS.

This study evaluates the integration of multispectral and texture data from UAV imagery to estimate leaf nitrogen content (LNC) in common bean across different growth stages. Our models were developed using data from a single location over two seasons; thus, broader validation is needed across diverse environmental conditions and cultivars.

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