9,191 to 9,200 of 10,921 Results
Adobe PDF - 240.9 KB -
MD5: cd0401263632270f8751deb1f86b7bc8
Codebook for wheat datasets |
Adobe PDF - 279.9 KB -
MD5: 1794be1aab03e3032707fc97ef9d5508
Codebook for rice datasets |
Mar 9, 2017 -
A variational Bayes genomic-enabled prediction model with genotype × environment interaction
Unknown - 376.8 KB -
MD5: 0b0889757980aefa3f3bae20d3ecc318
Maize data |
Mar 9, 2017 -
A variational Bayes genomic-enabled prediction model with genotype × environment interaction
Unknown - 459.3 KB -
MD5: c59905b897fe95f9d600f78cd42b4fba
Wheat data |
Mar 9, 2017 -
A variational Bayes genomic-enabled prediction model with genotype × environment interaction
Unknown - 5.2 MB -
MD5: 4a3ec390c48988b3203c50904a8b78da
Wheat yield data |
Feb 28, 2017 -
Survey to assess the impact of multi-level factors of change on farm trajectories in Southern Bangladesh
Adobe PDF - 103.9 KB -
MD5: 1afb9d26eaf3d4b4f7eca241d289f509
Detailed information on the data collection methodology and variables contained in datasets |
Feb 16, 2017 -
Genomic-enabled prediction in maize using kernel models with genotype × environment interaction
Unknown - 3.2 MB -
MD5: 5ec14850d84981924150ab72a73ffd3b
HEL dataset |
Feb 16, 2017 -
Genomic-enabled prediction in maize using kernel models with genotype × environment interaction
Unknown - 8.3 MB -
MD5: ea15b012992ef6cfd169e4c2595d2c2b
UPS dataset |
Tabular Data - 31.7 KB - 9 Variables, 1350 Observations - UNF:5:0e6r9+Vhetf+GI0UHt6Z7A==
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Tabular Data - 15.4 KB - 30 Variables, 174 Observations - UNF:5:pQ1S1K0thgDkRp0SIFC2Yg==
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