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8,381 to 8,390 of 10,686 Results
Module 6 Part B Expenditure on Non-food Items in the Last 12 Months.dta
Nov 1, 2017 - Pathways to sustainable intensification in Eastern and Southern Africa - Tanzania 2015
Unknown - 2.0 MB - MD5: 45a2c5000d91e69c44318ac3e4113506
Household Dataset
Module 7 Part A Social capital networks, Institiution.dta
Nov 1, 2017 - Pathways to sustainable intensification in Eastern and Southern Africa - Tanzania 2015
Unknown - 77.1 KB - MD5: 80b7ebb7b85e9a9b3cf79d7ad1e6f532
Individual Dataset
Module 7 Part B Social capital networks,Social network.dta
Nov 1, 2017 - Pathways to sustainable intensification in Eastern and Southern Africa - Tanzania 2015
Unknown - 190.0 KB - MD5: 3133322d5f53044434975854ecca7d28
Individual Dataset
MODULE 8 HOUSEHOLD DIETARY DIVERSITY SCORE.dta
Nov 1, 2017 - Pathways to sustainable intensification in Eastern and Southern Africa - Tanzania 2015
Unknown - 91.7 KB - MD5: 7b6bcdf705a16ed2367ef2294e3cffc2
Individual Dataset
MODULE 9 HOUSEHOLD FOOD INSECURITY ACCESS SCALE.dta
Nov 1, 2017 - Pathways to sustainable intensification in Eastern and Southern Africa - Tanzania 2015
Unknown - 19.2 KB - MD5: 5442f78281da95b3b02d12431e5be5b0
Individual Dataset
Pathways Survey-household (Tanzania _Final 17April2016).doc
Nov 1, 2017 - Pathways to sustainable intensification in Eastern and Southern Africa - Tanzania 2015
Unknown - 1.3 MB - MD5: d145904ddb6301e5236a357541eb280f
Questionnaire
Pathways to sustainable intensification in Eastern and Southern Africa - Malawi 2010
Nov 1, 2017
Marenya, Paswel; Kassie, Menale; Mangisoni, Julius; Muricho, Geoffrey; Alemu, Solomon, 2016, "Pathways to sustainable intensification in Eastern and Southern Africa - Malawi 2010", https://hdl.handle.net/11529/10759, CIMMYT Research Data & Software Repository Network, V8, UNF:5:uXU5D4MHcJxlIa8VI3x/LA== [fileUNF]
Using purposive sampling, the central and Southern regions were selected. The Central region transcends from high to low altitude while the Southern region is predominantly a low altitude area. Maize is extensively grown in both regions with groundnuts and haricot beans being the...
Prediction of multiple-trait and multiple-environment genomic data using recommender systems
Oct 10, 2017
Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, Jose; Montesinos-López, José Cricelio; Mota-Sanchez, David; Estrada-Gonzalez, Fermin; Gilberg, Jussi; Singh, Ravi; Mondal, Suchismita; Juliana, Philomin, 2017, "Prediction of multiple-trait and multiple-environment genomic data using recommender systems", https://hdl.handle.net/11529/11099, CIMMYT Research Data & Software Repository Network, V2
In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, while researchers have a...
Data.Trigo.RData
Oct 10, 2017 - Prediction of multiple-trait and multiple-environment genomic data using recommender systems
Unknown - 19.1 KB - MD5: f543faa4b1f3c7b38397ae6e5309da2d
Phenotypic data
Phenotypic wheat data
Gg.RData
Oct 10, 2017 - Prediction of multiple-trait and multiple-environment genomic data using recommender systems
Unknown - 369.0 KB - MD5: 6a64605058cc14524a8bf9a0c96b6025
Genotypic data
Genotypic maize data
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