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Document type:
Zeitschriftenaufsatz 
Author(s):
Genze, Nikita; Bharti, Richa; Grieb, Michael; Schultheiss, Sebastian J.; Grimm, Dominik G. 
Title:
Accurate machine learning-based germination detection, prediction and quality assessment of three grain crops 
Abstract:
Background Assessment of seed germination is an essential task for seed researchers to measure the quality and performance of seeds. Usually, seed assessments are done manually, which is a cumbersome, time consuming and error-prone process. Classical image analyses methods are not well suited for large-scale germination experiments, because they often rely on manual adjustments of color-based thresholds. We here propose a machine learning approach using modern artificial neural networks with re...    »
 
Journal title:
Plant Methods 
Year:
2020 
Journal volume:
16 
Journal issue:
Covered by:
Web of Science 
Reviewed:
ja 
Language:
en 
Publisher:
Springer Science and Business Media LLC 
E-ISSN:
1746-4811 
Status:
Verlagsversion / published 
Date of publication:
01.12.2020