7,831 to 7,840 of 10,510 Results
Oct 8, 2018
Sonder, Kai; Schulthess, Urs; Chomé, Guillaume, 2018, "Evaluating Radar Satellite Based Remote Sensing for Conservation Agriculture Adoption Detection in North and Central Mexico", https://hdl.handle.net/11529/10548137, CIMMYT Research Data & Software Repository Network, V1
Conservation agriculture has been tested and out scaled for over 60 years in rural areas of Mexico, however the rate of adoption and dis adoption, as well as the current area under CA is unknown. Estimates range between 50,000 ha and over 800,000 ha depending on the source. Studi... |
Oct 8, 2018 -
Evaluating Radar Satellite Based Remote Sensing for Conservation Agriculture Adoption Detection in North and Central Mexico
Adobe PDF - 1.9 MB -
MD5: 37f4bdf8baee6dec17d3ca1678950a9c
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Oct 8, 2018
Cerón-Rojas, J.Jesús; Toledo, Fernando; Crossa, Jose, 2018, "Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices", https://hdl.handle.net/11529/10548136, CIMMYT Research Data & Software Repository Network, V1
This dataset provides supplemental information related to an investigation of constrained multistage linear phenotypic selection indices. |
Oct 8, 2018 -
Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices
MS Word - 358.0 KB -
MD5: 02e60fff9e7c5c038887aa8a2dde15c8
This file has supplementary material of the article "The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices" |
Sep 28, 2018
Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, Jose; Gianola, Daniel; Hernández-Suarez, Carlos Moisés; Martín-Vallejo, Javier, 2018, "Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits", https://hdl.handle.net/11529/10548134, CIMMYT Research Data & Software Repository Network, V1
This study provides supplemental data to support an investigation of the power of multi-trait deep learning (MTDL) models in terms of genomic-enabled prediction accuracy. |
Sep 28, 2018 -
Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits
RAR Archive - 41.9 MB -
MD5: cdd5ff94aff34916a943fe27c4bb20a6
Supporting data |
Sep 21, 2018
Basnet, Bhoja Raj; Crossa, Jose; Pérez-Rodríguez, Paulino; Manes, Yann; Singh, Ravi; Rosyara, Umesh; Camarillo-Castillo, Fatima; Murua, Mercedes, 2018, "Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models", https://hdl.handle.net/11529/10548129, CIMMYT Research Data & Software Repository Network, V1
Genomic prediction of hybrids unobserved in field evaluations is crucial. In this study, we used genomic G×E models for hybrid prediction, where similarity between lines was assessed by pedigree and molecular markers, and similarity between environments was accounted for by envir... |
Sep 21, 2018 -
Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models
Gzip Archive - 7.8 MB -
MD5: 899ad733bc009f213bfdeed4df1cb4bd
This zipped folder contains 4 supplemental files and one data dictionary to describe the variables contained in the other files. |
Aug 6, 2018 -
36th Elite Spring Wheat Yield Trial
MS Excel Spreadsheet - 415.2 KB -
MD5: e37c8ccea311bb0bf473a96840bc3378
Agronomic information by location |
Aug 6, 2018 -
36th Elite Spring Wheat Yield Trial
MS Excel Spreadsheet - 4.9 KB -
MD5: 85d48e9e612d0468913ea42c6984f8da
List of genotypes included on the nursery |
