Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield: Supplementary Methods

Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield: Supplementary Methods

This is the supplementary methods of "Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield" published in Crop Science · May 2017, DOI: 10.2135/cropsci2017.01.0007. It includes the raw data in R format and the R-code for the analysis.

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Bibliographic Details
Main Authors: Fernando Aguate, Samuel Trachsel, Lorena González-Pérez, Juan Burgueño, José Crossa, Mónica Balzarini, David Gouache, Matthieu Bogard, Gustavo de los Campos
Published: CIMMYT Research Data & Software Repository Network 2016
Subjects:Agricultural Sciences, Maize, Bayesian prediction, Yield prediction, High-throughput phenotyping, Hyperspectral image analysis,
Online Access:https://hdl.handle.net/11529/10972
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Summary:This is the supplementary methods of "Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield" published in Crop Science · May 2017, DOI: 10.2135/cropsci2017.01.0007. It includes the raw data in R format and the R-code for the analysis.

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