@article{
 title = {Understanding the relationships between genetic and phenotypic structures of a collection of elite durum wheat accessions},
 type = {article},
 year = {2010},
 identifiers = {[object Object]},
 keywords = {DARWin,Genetic diversity,Genotype??environment interaction,Germplasm collection,Triticum turgidum},
 id = {6463cb1a-946c-3e03-bab1-e8ff2d85dbe3},
 created = {2015-06-26T23:34:17.000Z},
 file_attached = {true},
 profile_id = {4bd47098-4729-3735-aeb0-ff5f6da673d7},
 last_modified = {2015-07-07T21:13:54.000Z},
 read = {true},
 starred = {false},
 authored = {true},
 confirmed = {false},
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 abstract = {A collection of 191 durum wheat accessions representing Mediterranean Basin genetic diversity was grown in nine different environments in four countries, with productivities ranging from 0.99 to 6.78tha-1. The population breeding structure comprised eight genetic subpopulations (GSPs) using data derived from 97 evenly distributed SSR markers. The phenotypic structure was assessed: (i) from the mean values of six agronomic traits across environments (multivariate), and (ii) from data representing each trait in each environment (univariate). Mean daily maximum temperature from emergence to heading was significantly (P<0.05) and negatively associated to yield, accounting for 59% of yield variations. Significant but weak relationships were obtained between the genetic similarities among accessions and their overall agronomic performance (r=0.15, P<0.001), plant height (r=0.12, P<0.001), spike-peduncle length (r=0.06, P<0.01) and thousand kernel weight (r=0.03, P<0.05), suggesting a very low possibility of prediction of the agronomic performance based on random SSR markers. The percentage of variability (measured by sum of squares) explained by the environment varied between 76.3 and 98.5% depending on the trait, while that explained by genotypes ranged between 0.4 and 12.6%, and that explained by the GE interaction ranged from 1.1 to 12.5%. The clustering of the accessions based on multivariate phenotypic data offered the best explanation of genotypic differences, accounting for 30.3% (for yield) to 75.1% (for kernel weight) of the observed variation. The genotype×environment interaction was best explained by the phenotypic univariate clustering procedure, which explained from 28.5% (for kernel weight) to 74.9% (for days to heading) of variation. The only accessions that clustered both in the genetic dissimilarities tree and the tree obtained using Euclidean distances based on standardized phenotypic data across environments were those closely related to the CIMMYT hallmark founder 'Altar 84', the ICARDA accessions adapted to continental-dryland areas, and the landraces, suggesting that genetic proximity corresponded to agronomic performance in only a few cases. © 2010 Elsevier B.V.},
 bibtype = {article},
 author = {Royo, Conxita and Maccaferri, Marco and Álvaro, Fanny and Moragues, Marc and Sanguineti, Maria Corinna and Tuberosa, Roberto and Maalouf, Fouad and Moral, Luis F García del and Demontis, Andrea and Rhouma, Sayar and Nachit, Miloudi and Nserallah, Nasserlehaq and Villegas, Dolors},
 journal = {Field Crops Research}
}

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The population breeding structure comprised eight genetic subpopulations (GSPs) using data derived from 97 evenly distributed SSR markers. The phenotypic structure was assessed: (i) from the mean values of six agronomic traits across environments (multivariate), and (ii) from data representing each trait in each environment (univariate). Mean daily maximum temperature from emergence to heading was significantly (P<0.05) and negatively associated to yield, accounting for 59% of yield variations. Significant but weak relationships were obtained between the genetic similarities among accessions and their overall agronomic performance (r=0.15, P<0.001), plant height (r=0.12, P<0.001), spike-peduncle length (r=0.06, P<0.01) and thousand kernel weight (r=0.03, P<0.05), suggesting a very low possibility of prediction of the agronomic performance based on random SSR markers. The percentage of variability (measured by sum of squares) explained by the environment varied between 76.3 and 98.5% depending on the trait, while that explained by genotypes ranged between 0.4 and 12.6%, and that explained by the GE interaction ranged from 1.1 to 12.5%. The clustering of the accessions based on multivariate phenotypic data offered the best explanation of genotypic differences, accounting for 30.3% (for yield) to 75.1% (for kernel weight) of the observed variation. The genotype×environment interaction was best explained by the phenotypic univariate clustering procedure, which explained from 28.5% (for kernel weight) to 74.9% (for days to heading) of variation. The only accessions that clustered both in the genetic dissimilarities tree and the tree obtained using Euclidean distances based on standardized phenotypic data across environments were those closely related to the CIMMYT hallmark founder 'Altar 84', the ICARDA accessions adapted to continental-dryland areas, and the landraces, suggesting that genetic proximity corresponded to agronomic performance in only a few cases. © 2010 Elsevier B.V.","bibtype":"article","author":"Royo, Conxita and Maccaferri, Marco and Álvaro, Fanny and Moragues, Marc and Sanguineti, Maria Corinna and Tuberosa, Roberto and Maalouf, Fouad and Moral, Luis F García del and Demontis, Andrea and Rhouma, Sayar and Nachit, Miloudi and Nserallah, Nasserlehaq and Villegas, Dolors","journal":"Field Crops Research","bibtex":"@article{\n title = {Understanding the relationships between genetic and phenotypic structures of a collection of elite durum wheat accessions},\n type = {article},\n year = {2010},\n identifiers = {[object Object]},\n keywords = {DARWin,Genetic diversity,Genotype??environment interaction,Germplasm collection,Triticum turgidum},\n id = {6463cb1a-946c-3e03-bab1-e8ff2d85dbe3},\n created = {2015-06-26T23:34:17.000Z},\n file_attached = {true},\n profile_id = {4bd47098-4729-3735-aeb0-ff5f6da673d7},\n last_modified = {2015-07-07T21:13:54.000Z},\n read = {true},\n starred = {false},\n authored = {true},\n confirmed = {false},\n hidden = {false},\n abstract = {A collection of 191 durum wheat accessions representing Mediterranean Basin genetic diversity was grown in nine different environments in four countries, with productivities ranging from 0.99 to 6.78tha-1. The population breeding structure comprised eight genetic subpopulations (GSPs) using data derived from 97 evenly distributed SSR markers. The phenotypic structure was assessed: (i) from the mean values of six agronomic traits across environments (multivariate), and (ii) from data representing each trait in each environment (univariate). Mean daily maximum temperature from emergence to heading was significantly (P<0.05) and negatively associated to yield, accounting for 59% of yield variations. Significant but weak relationships were obtained between the genetic similarities among accessions and their overall agronomic performance (r=0.15, P<0.001), plant height (r=0.12, P<0.001), spike-peduncle length (r=0.06, P<0.01) and thousand kernel weight (r=0.03, P<0.05), suggesting a very low possibility of prediction of the agronomic performance based on random SSR markers. The percentage of variability (measured by sum of squares) explained by the environment varied between 76.3 and 98.5% depending on the trait, while that explained by genotypes ranged between 0.4 and 12.6%, and that explained by the GE interaction ranged from 1.1 to 12.5%. The clustering of the accessions based on multivariate phenotypic data offered the best explanation of genotypic differences, accounting for 30.3% (for yield) to 75.1% (for kernel weight) of the observed variation. The genotype×environment interaction was best explained by the phenotypic univariate clustering procedure, which explained from 28.5% (for kernel weight) to 74.9% (for days to heading) of variation. 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