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Spatial analysis to support geographic targeting of genotypes to environments

Crop improvement efforts have benefited greatly from advances in available data, computing technology, and methods for targeting genotypes to environments. These advances support the analysis of genotype by environment interactions (GEI) to understand how well a genotype adapts to environmental cond...

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Detalles Bibliográficos
Autores principales: Hyman, Glenn, Hodson, Dave, Jones, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3600773/
https://www.ncbi.nlm.nih.gov/pubmed/23515351
http://dx.doi.org/10.3389/fphys.2013.00040
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author Hyman, Glenn
Hodson, Dave
Jones, Peter
author_facet Hyman, Glenn
Hodson, Dave
Jones, Peter
author_sort Hyman, Glenn
collection PubMed
description Crop improvement efforts have benefited greatly from advances in available data, computing technology, and methods for targeting genotypes to environments. These advances support the analysis of genotype by environment interactions (GEI) to understand how well a genotype adapts to environmental conditions. This paper reviews the use of spatial analysis to support crop improvement research aimed at matching genotypes to their most appropriate environmental niches. Better data sets are now available on soils, weather and climate, elevation, vegetation, crop distribution, and local conditions where genotypes are tested in experimental trial sites. The improved data are now combined with spatial analysis methods to compare environmental conditions across sites, create agro-ecological region maps, and assess environment change. Climate, elevation, and vegetation data sets are now widely available, supporting analyses that were much more difficult even 5 or 10 years ago. While detailed soil data for many parts of the world remains difficult to acquire for crop improvement studies, new advances in digital soil mapping are likely to improve our capacity. Site analysis and matching and regional targeting methods have advanced in parallel to data and technology improvements. All these developments have increased our capacity to link genotype to phenotype and point to a vast potential to improve crop adaptation efforts.
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spelling pubmed-36007732013-03-19 Spatial analysis to support geographic targeting of genotypes to environments Hyman, Glenn Hodson, Dave Jones, Peter Front Physiol Plant Science Crop improvement efforts have benefited greatly from advances in available data, computing technology, and methods for targeting genotypes to environments. These advances support the analysis of genotype by environment interactions (GEI) to understand how well a genotype adapts to environmental conditions. This paper reviews the use of spatial analysis to support crop improvement research aimed at matching genotypes to their most appropriate environmental niches. Better data sets are now available on soils, weather and climate, elevation, vegetation, crop distribution, and local conditions where genotypes are tested in experimental trial sites. The improved data are now combined with spatial analysis methods to compare environmental conditions across sites, create agro-ecological region maps, and assess environment change. Climate, elevation, and vegetation data sets are now widely available, supporting analyses that were much more difficult even 5 or 10 years ago. While detailed soil data for many parts of the world remains difficult to acquire for crop improvement studies, new advances in digital soil mapping are likely to improve our capacity. Site analysis and matching and regional targeting methods have advanced in parallel to data and technology improvements. All these developments have increased our capacity to link genotype to phenotype and point to a vast potential to improve crop adaptation efforts. Frontiers Media S.A. 2013-03-18 /pmc/articles/PMC3600773/ /pubmed/23515351 http://dx.doi.org/10.3389/fphys.2013.00040 Text en Copyright © 2013 Hyman, Hodson and Jones. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
spellingShingle Plant Science
Hyman, Glenn
Hodson, Dave
Jones, Peter
Spatial analysis to support geographic targeting of genotypes to environments
title Spatial analysis to support geographic targeting of genotypes to environments
title_full Spatial analysis to support geographic targeting of genotypes to environments
title_fullStr Spatial analysis to support geographic targeting of genotypes to environments
title_full_unstemmed Spatial analysis to support geographic targeting of genotypes to environments
title_short Spatial analysis to support geographic targeting of genotypes to environments
title_sort spatial analysis to support geographic targeting of genotypes to environments
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3600773/
https://www.ncbi.nlm.nih.gov/pubmed/23515351
http://dx.doi.org/10.3389/fphys.2013.00040
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