Predicting Dry Pea Maturity Using Machine Learning and Advanced Sensor Fusion with Unmanned Aerial Systems (UASs)

Predicting Dry Pea Maturity Using Machine Learning and Advanced Sensor Fusion with Unmanned Aerial Systems (UASs)

Maturity is an important trait in dry pea breeding programs, but the conventional process predominately used to measure this trait can be time-consuming, labor-intensive, and prone to errors. Therefore, a more efficient and accurate approach would be desirable to support dry pea breeding programs. T...

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Bibliographic Details
Main Authors: Aliasghar Bazrafkan, Harry Navasca, Jeong-Hwa Kim, Mario Morales, Josephine Princy Johnson, Nadia Delavarpour, Nadeem Fareed, Nonoy Bandillo, Paulo Flores
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Remote Sensing
Subjects:
peas phenotyping
machine learning
LIDAR
high-throughput plant phenotyping
multispectral indices
Online Access:https://www.mdpi.com/2072-4292/15/11/2758

Internet

https://www.mdpi.com/2072-4292/15/11/2758

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