Comparison between red, green and blue images and near-infrared spectroscopy methods in the neutral detergent fiber (NDF) analysis

• Autores: Ospina R., Oscar, Anzola Vasquez, Hector José, Ayala D., Olber, Baracaldo M., Andrea, Arévalo C., Juan, Lozada W., Pedro
• Formato: artículo
• Fecha de Publicación: 2021
• Institución: Universidad Nacional Mayor de San Marcos
• Repositorio: Revistas - Universidad Nacional Mayor de San Marcos
• Lenguaje: español
• OAI Identifier: oai:ojs.csi.unmsm:article/17498
• Enlace del recurso: https://revistasinvestigacion.unmsm.edu.pe/index.php/veterinaria/article/view/17498
• Nivel de acceso: acceso abierto
• Materia: algorithm; drone; bromatological analysis; RGB; NDF; algoritmo; dron; análisis bromatológico; FDN

The aim of this study to the evaluate the precision of the Red, Green, Blue (RGB) image analysis algorithm included in the TaurusWebs V2017® software for calculating the percentage of neutral detergent fiber (NDF) in the dry matter of grasses, from images of the grasslands taken by a drone with RGB camera. The results were compared with NDF values calculated with near infrared spectroscopy (NIRS). Forty-two samples were taken for NIRS: 18 from grasses from the high tropics in Cundinamarca: kikuyu (Pennisetum clandestinum), velvet grass (Holcus lanatus) and reed canarian grass (Phalaris arundinacea) and 24 from the lower tropics in Tolima, Colombia: pangola (Digitaria decumbens), para (Brachiaria mutica), Bermuda grass (Cynodon dactylon) and silver grass (Bothriochloa pertusa). The results were compared against 180 evaluations made with the algorithm of the images of the same grasses where the samples were taken for NIRS. The Kendall and Spearman correlation tests were significant (p<0.05), with an association of rho = 0.81 for the Kruskal Wallis hypothesis test (p>0.05). There were no significant differences in NDF values under the two methodologies and according to the Wilcoxon test, the medians of DNF calculated by NIRS vs. those of the algorithm are the same. In conclusion, the information generated with the algorithm can be used for NDF analysis work in grasses.