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Machine Learning Integrates Multispectral Phenotyping and Ionic Signatures to Reveal Stage‐Specific Drought Resilience in Cotton.

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Title: Machine Learning Integrates Multispectral Phenotyping and Ionic Signatures to Reveal Stage‐Specific Drought Resilience in Cotton.
Authors: Cisse, El‐Hadji Malick1 (AUTHOR) kosmosofmalick@gmail.com, Gajanayake, Bandara1 (AUTHOR), Mathur, Sonal1 (AUTHOR), Chang, Christine Yao‐Yun1 (AUTHOR), Fleisher, David1 (AUTHOR), Fultz, Lisa1 (AUTHOR), Timlin, Dennis1 (AUTHOR), Mitra, Alakananda1 (AUTHOR), Reddy, Vangimalla1 (AUTHOR) vangimalla.reddy@usda.gov
Source: Plant, Cell & Environment. Aug2026, Vol. 49 Issue 8, p4846-4849. 4p.
Database: Environment Complete
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DbLabel: Environment Complete
An: 195289761
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PubType: Academic Journal
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  Data: <searchLink fieldCode="JN" term="%22Plant%2C+Cell+%26+Environment%22">Plant, Cell & Environment</searchLink>. Aug2026, Vol. 49 Issue 8, p4846-4849. 4p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eih&AN=195289761
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        Value: 10.1111/pce.70474
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      – Code: eng
        Text: English
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      – TitleFull: Machine Learning Integrates Multispectral Phenotyping and Ionic Signatures to Reveal Stage‐Specific Drought Resilience in Cotton.
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              Text: Aug2026
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              Y: 2026
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            – TitleFull: Plant, Cell & Environment
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