Improving Accuracy of Herbage Yield Predictions in Perennial Ryegrass with UAV-Based Structural and Spectral Data Fusion and Machine Learning

Improving Accuracy of Herbage Yield Predictions in Perennial Ryegrass with UAV-Based Structural and Spectral Data Fusion and Machine Learning

High-throughput field phenotyping using close remote sensing platforms and sensors for non-destructive assessment of plant traits can support the objective evaluation of yield predictions of large breeding trials. The main objective of this study was to examine the potential of unmanned aerial vehic...

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Bibliographic Details
Main Authors: Joanna Pranga, Irene Borra-Serrano, Jonas Aper, Tom De Swaef, An Ghesquiere, Paul Quataert, Isabel Roldán-Ruiz, Ivan A. Janssens, Greet Ruysschaert, Peter Lootens
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Remote Sensing
Subjects:
high-throughput field phenotyping (HTFP)
pasture
forage
RGB sensor
multispectral sensor
close remote sensing
Online Access:https://www.mdpi.com/2072-4292/13/17/3459

Internet

https://www.mdpi.com/2072-4292/13/17/3459

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