9,801 to 9,810 of 12,530 Results
Feb 14, 2018 -
An informational view of accession rarity and allele specificity in germplasm banks for management and conservation
R Data - 81.7 MB -
MD5: ffec764128374e86a73b31e57a33a533
AllDataHexaploid.bin. A table in RData format, readable by R through the function *load*. It has a dimension 41052 x 7987. The column allele_id is the SNP allele id, and the remaining 7986 columns are hexaploid wheat accessions. The numbers in the cells are allele frequencies. Th... |
Feb 14, 2018 -
An informational view of accession rarity and allele specificity in germplasm banks for management and conservation
Unknown - 5.8 MB -
MD5: 256a7c0e69ebd16cc88b80d6fea8e6cb
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Feb 14, 2018 -
An informational view of accession rarity and allele specificity in germplasm banks for management and conservation
Tabular Data - 64.1 MB - 7988 Variables, 4126 Observations - UNF:6:v+RWYoZQ/W6oh+hfVGd6uQ==
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Plain Text - 8.7 KB -
MD5: 413f53b5dc5025c54e048d7a805e9d0a
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Feb 7, 2018 - CIMMYT Research Data
Molnar, Terence; Fuentes, Mario, 2018, "Evaluation of Maize Landraces and Related Pre-breeding Materials for Tar Spot Resistance in 2015", https://hdl.handle.net/11529/10847, CIMMYT Research Data & Software Repository Network, V1, UNF:6:J9ZYZVx1huHrIdQM9mgyMA== [fileUNF]
This study provides phenotypic data from Tar Spot trials conducted in 2015 as part of the Seeds of Discovery / MasAgro Biodiversidad project. |
Feb 7, 2018 -
Evaluation of Maize Landraces and Related Pre-breeding Materials for Tar Spot Resistance in 2015
Tabular Data - 300 B - 10 Variables, 5 Observations - UNF:6:J9ZYZVx1huHrIdQM9mgyMA==
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Feb 7, 2018 -
Evaluation of Maize Landraces and Related Pre-breeding Materials for Tar Spot Resistance in 2015
Plain Text - 4.1 KB -
MD5: e959545f1040bca733168825ace988d6
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Feb 7, 2018 -
Evaluation of Maize Landraces and Related Pre-breeding Materials for Tar Spot Resistance in 2015
Plain Text - 981 B -
MD5: e5c7801ee6f9859391c8fa7c6e498ba6
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MS Excel Spreadsheet - 891.3 KB -
MD5: 451dfb39758541741341938757243be9
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MS Excel Spreadsheet - 3.4 MB -
MD5: 6719ad3b02817cb241f689119df1ea51
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