HairNet2: deep learning to quantify cotton leaf hairiness, a complex genetic and environmental trait

HairNet2: deep learning to quantify cotton leaf hairiness, a complex genetic and environmental trait

Abstract Background Cotton accounts for 80% of the global natural fibre production. Its leaf hairiness affects insect resistance, fibre yield, and economic value. However, this phenotype is still qualitatively assessed by visually attributing a Genotype Hairiness Score (GHS) to a leaf/plant, or by u...

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Bibliographic Details
Main Authors: Moshiur Farazi, Warren C. Conaty, Lucy Egan, Susan P. J. Thompson, Iain W. Wilson, Shiming Liu, Warwick N. Stiller, Lars Petersson, Vivien Rolland
Format: Article
Language:English
Published: BMC 2024-03-01
Series:Plant Methods
Subjects:
Deep learning
Neural network
Machine learning
Phenotyping
Trichome
Cotton
Online Access:https://doi.org/10.1186/s13007-024-01149-8

Internet

https://doi.org/10.1186/s13007-024-01149-8

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