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Ability of in situ canopy spectroscopy to differentiate genotype by environment interaction in wheat

Abstract
In recent years, the application of remote sensing techniques is gaining a growing interest and importance in agriculture. Researchers often combine data from near-infrared and red spectral bands according to their specific objectives. These types of combinations present the disadvantage of lack of sensitivity due to using a single or limited group of bands. In this work on-farm canopy spectral reflectance (CSR) data, composing of ten spectral bands (SBs) [ver mas...]
In recent years, the application of remote sensing techniques is gaining a growing interest and importance in agriculture. Researchers often combine data from near-infrared and red spectral bands according to their specific objectives. These types of combinations present the disadvantage of lack of sensitivity due to using a single or limited group of bands. In this work on-farm canopy spectral reflectance (CSR) data, composing of ten spectral bands (SBs) plus four spectral vegetation indices (SVIs), is considered in a joint manner to set up a methodology capable to identify genotype by environment interaction (GxE) in wheat. Spectral data are analysed over five wheat genotypes grown in five different environments. Historically breeders have recognized the potentially negative implications of GxE in selection and cultivar deployment and have focused on developing tools and resources to quantify it. We propose to perform a statistical batch processing, applying two-way analysis of variance to multiple spectral data, with genotype and environment as fixed factors. Results prove that this methodology performs well in both directions, capturing differences between genotypes within a single environment, and between environments for a single genotype, representing a step forward to converting spectral data into knowledge for the subject of GxE. [Cerrar]
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Author
Arias, Claudia;   Montero Bulacio, Enrique;   Rigalli, Nicolás;   Romagnoli, Martín;   Curin, Facundo;   Gonzalez, Fernanda Gabriela;   Otegui, María Elena;   Portapila, Margarita;  
Fuente
International Journal of Remote Sensing 42 (10) : 3660–3680, (March 2021)
Date
2021-03
Editorial
Taylor & Francis
URI
http://hdl.handle.net/20.500.12123/8955
https://www.tandfonline.com/doi/abs/10.1080/01431161.2021.1875148
DOI
https://doi.org/10.1080/01431161.2021.1875148
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pdf
Tipo de documento
artículo
Palabras Claves
Trigo; Wheat; Genotipos; Genotypes; Interacción Genotipo Ambiente; Genotype Environment Interaction; Pergamino, Buenos Aires;
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Excepto donde se diga explicitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
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