Broadacre Crop Yield Estimation Using Imaging Spectroscopy from Unmanned Aerial Systems (UAS): A Field-Based Case Study with Snap Bean

Broadacre Crop Yield Estimation Using Imaging Spectroscopy from Unmanned Aerial Systems (UAS): A Field-Based Case Study with Snap Bean

Accurate, precise, and timely estimation of crop yield is key to a grower’s ability to proactively manage crop growth and predict harvest logistics. Such yield predictions typically are based on multi-parametric models and in-situ sampling. Here we investigate the extension of a greenhouse study, to...

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Bibliographic Details
Main Authors: Amirhossein Hassanzadeh, Fei Zhang, Jan van Aardt, Sean P. Murphy, Sarah J. Pethybridge
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Remote Sensing
Subjects:
feature selection
hyperspectral imaging
machine learning
snap bean
unmanned aerial vehicle
yield modelling
Online Access:https://www.mdpi.com/2072-4292/13/16/3241

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