Deep learning based high-throughput phenotyping of chalkiness in rice exposed to high night temperature

Deep learning based high-throughput phenotyping of chalkiness in rice exposed to high night temperature

Abstract Background Rice is a major staple food crop for more than half the world’s population. As the global population is expected to reach 9.7 billion by 2050, increasing the production of high-quality rice is needed to meet the anticipated increased demand. However, global environmental changes,...

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Bibliographic Details
Main Authors: Chaoxin Wang, Doina Caragea, Nisarga Kodadinne Narayana, Nathan T. Hein, Raju Bheemanahalli, Impa M. Somayanda, S. V. Krishna Jagadish
Format: Article
Language:English
Published: BMC 2022-01-01
Series:Plant Methods
Subjects:
Rice grain chalkiness detection
Image segmentation
Convolutional neural networks
Gradient-weighted class activation mapping
High night temperature
Online Access:https://doi.org/10.1186/s13007-022-00839-5

Internet

https://doi.org/10.1186/s13007-022-00839-5

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