Citas bibligráficas
Oré, G., Vásquez, A. (2021). Desarrollo de un equipo electrónico/computacional orientado a extraer información de interés para el diagnóstico de Mildiu en plantaciones de quinua de la costa peruana basado en procesamiento digital de imágenes [Tesis, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/654958
Oré, G., Vásquez, A. Desarrollo de un equipo electrónico/computacional orientado a extraer información de interés para el diagnóstico de Mildiu en plantaciones de quinua de la costa peruana basado en procesamiento digital de imágenes [Tesis]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2021. http://hdl.handle.net/10757/654958
@misc{renati/394137,
title = "Desarrollo de un equipo electrónico/computacional orientado a extraer información de interés para el diagnóstico de Mildiu en plantaciones de quinua de la costa peruana basado en procesamiento digital de imágenes",
author = "Vásquez García, Alexis",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2021"
}
This thesis proposes a portable and ergonomic equipment that allows the capture of images of quinoa crops and, through an effective processing method, detect the segments where the plant is affected by Mildew disease (represented by a particular yellowing on the leaves) in order to obtain a numerical result that represents that effect. The realization of this project solves the main problem of the qualitative analysis on which the client is based for the diagnosis of the disease since it will offer a quantitative solution for the identification and measurement of crop damage that provides the agronomist with a vital data to be able to Supply the appropriate dose of herbicide to the plantations and obtain a better quality product. This work is based on two segmentation processes: first, from the original image captured, the segmentation of vegetation over the environment was carried out using the L*a*b color model, two-dimensional histogram, filtering and binarization; and, secondly, from the image resulting from the first process, the segmentation of yellowing on the vegetation was carried out using the two-dimensional histogram, filtering, binarization and eccentricity properties models. For validation, 50 images of a quinoa crop from INIA - Lima Headquarters were taken, which were processed through the equipment developed and verified by the specialist agronomist. Finally, Cohen’s Kappa index was used to compare the results where a result of 0.789 was obtained.
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