Comparación de métodos no destructivos para estimar el área foliar de Cinchona officinalis L. mediante procesamiento digital de imágenes Comparison of non-destructive methods for estimating the leaf area of Cinchona officinalis L. using digital image processing
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Cinchona officinalis es una importante especie vegetal, fue el único tratamiento para la malaria durante más de tres siglos. El objetivo de este estudio fue comparar la precisión de cuatro métodos no destructivos de procesamiento digital de imágenes (LeafArea y tres algoritmos de ImageJ) para estimar el área foliar de plantaciones jóvenes de C. officinalis en dos condiciones de establecimiento: macizo forestal y franjas de enriquecimiento. Se fotografiaron hojas a 8 cm de distancia utilizando un smartphone de 24 MP y se procesaron con los métodos evaluados. El análisis estadístico incluyó diagramas de caja y bigotes, correlación de Pearson y prueba de Friedman. Los resultados mostraron que los métodos M3 y M4 de ImageJ presentaron la mayor precisión (r = 0,99), sin diferencias significativas entre ellos, y con sobreestimaciones detectadas en M1 y M2. Se concluye que M3 y M4 son opciones rápidas, de bajo costo y alta precisión para el monitoreo foliar de C. officinalis en campo.
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