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Fenotipado de alto rendimiento de raíces de maíz mediante análisis de imágenes digitales

Universidad Nacional de Colombia
Universidad Nacional de Colombia
Corporación Colombiana de Investigación Agropecuaria [AGROSAVIA]
combinación de métodos maíz mejoramiento rasgos radiculares REST

Resumen

La investigación reciente sobre la arquitectura radicular del maíz ha experimentado avances significativos, pero aún se requieren otros estudios enfocados en la optimización de los métodos para lograr una adquisición eficiente y precisa de los datos sobre la arquitectura radicular. Por lo anterior, el objetivo de esta investigación fue evaluar la eficacia del uso de imágenes digitales para el fenotipado de raíces de maíz (Zea mays L.). Se llevaron a cabo experimentos de campo en dos localidades de Antioquia, Colombia, en 2019 y 2020, para analizar variables de arquitectura de raíces de 12 genotipos de maíz. Se emplearon dos metodologías: fenotipado manual y análisis de imágenes digitales y se estimaron los coeficientes de correlación de Pearson entre variables. Por otra parte, se utilizó el análisis de componentes principales (ACP) para descubrir patrones en el conjunto de datos multivariantes. Los resultados del ACP indicaron correlaciones entre el diámetro derivado del software REST (r = 0,94) y el diámetro radicular medido manualmente. El ángulo radicular derecho e izquierdo medido manualmente se correlacionó con el ángulo radicular derivado de la imagen en r = 0,92 y 0,88, respectivamente, y la longitud radicular en r = 0,62. El ACP destacó que el método digital explicó la mayor proporción de variación en áreas radiculares y diámetros, mientras que el método manual dominó en variables de ángulo radicular. Estos hallazgos ofrecen un método optimizado para el fenotipado de la arquitectura radicular del maíz mediante un protocolo que se puede adoptar en análisis automáticos para la adquisición precisa de imágenes relacionadas con ángulos, longitudes y diámetros de raíces de maíz.

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