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AI-powered detection and quantification of post-harvest physiological deterioration (PPD) in cassava using YOLO foundation models and K-means clustering

Crossref DOI link: https://doi.org/10.1186/s13007-024-01309-w

Published Online: 2024-11-23

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Ayalde, Daniela Gómez

Londoño, Juan Camilo Giraldo

Mosquera, Audberto Quiroga

Melendez, Jorge Luis Luna

Gimode, Winnie

Tran, Thierry

Zhang, Xiaofei

Selvaraj, Michael Gomez
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Text and Data Mining valid from 2024-11-23

Version of Record valid from 2024-11-23
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Article History

Received: 15 August 2024

Accepted: 20 November 2024

First Online: 23 November 2024

Declarations

:

: Not applicable.

: All authors agreed to publish this manuscript.

: The authors confirm that all necessary permissions for root collection and imaging were obtained in compliance with regulations. The species used are not endangered.

: The authors declare no competing interests.

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