Convolutional Neural Networks to Estimate Dry Matter Yield in a Guineagrass Breeding Program Using UAV Remote Sensing

Convolutional Neural Networks to Estimate Dry Matter Yield in a Guineagrass Breeding Program Using UAV Remote Sensing

Forage dry matter is the main source of nutrients in the diet of ruminant animals. Thus, this trait is evaluated in most forage breeding programs with the objective of increasing the yield. Novel solutions combining unmanned aerial vehicles (UAVs) and computer vision are crucial to increase the effi...

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Bibliographic Details
Main Authors: Gabriel Silva de Oliveira, José Marcato Junior, Caio Polidoro, Lucas Prado Osco, Henrique Siqueira, Lucas Rodrigues, Liana Jank, Sanzio Barrios, Cacilda Valle, Rosângela Simeão, Camilo Carromeu, Eloise Silveira, Lúcio André de Castro Jorge, Wesley Gonçalves, Mateus Santos, Edson Matsubara
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Sensors
Subjects:
deep learning
forage dry matter yield
high-throughput phenotyping
Brazilian pasture
Online Access:https://www.mdpi.com/1424-8220/21/12/3971

Internet

https://www.mdpi.com/1424-8220/21/12/3971

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