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Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculenta Crantz)

Michael Gomez Selvaraj · Manuel Valderrama · Diego Guzman · Milton Valencia-Ortiz · Henry Ruiz · Animesh Acharjee

Research Square · 21 Feb 2020 · 10.21203/rs.2.24148/v1

Abstract

Abstract has not been obtained from indexed metadata or an accessible article page.

Code and data availability

The paper describes the CIAT Pheno-i web-based image analysis platform developed by the authors and used for this study's phenotyping, which is publicly accessible. However, no public deposit of the paper's phenotype datasets, UAV imagery, ML models, or analysis code is stated; supplementary files (ML model PDF, tables

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