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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2013
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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. |
format | Online Article Text |
id | pubmed-3600773 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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