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Autor: Juan Burgueño
Juan Burgueño deepmala sehgal (2019)
Phenotypic evaluation of the Linked Topcross Population 1 (LTP1) from the MasAgro Biodiversidad - Seeds of Discovery Initiative under drought, heat, and irrigated conditions.
Dataset
Grazing behavior of New Zeland holstein cows with access to shade
Rodolfo Ramírez-Valverde Juan Burgueño (2022)
Artículo
Temperature and Humidity Index Artificial Shade CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SHADING DAIRY COWS SOLAR RADIATION
Phenotypic data for "Single-gene resolution of locally adaptive genetic variation in Mexican maize.
Martha Willcox Juan Burgueño Sarah Hearne (2020)
Phenotypic data for: Daniel J Gates, Dan Runcie, Garrett M. Janzen, Alberto Romero Navarro, Martha Willcox, Kai Sonder, Samantha J. Snodgrass, Fausto Rodríguez-Zapata, Ruairidh J. H. Sawers, Rubén Rellán-Álvarez, Edward S. Buckler, Sarah Hearne, Matthew B. Hufford, Jeffrey Ross-Ibarra. Single-gene resolution of locally adaptive genetic variation in Mexican maize. doi: https://doi.org/10.1101/706739.
Dataset
Sparse designs for genomic selection using multi-environment data
Yoseph Beyene Juan Burgueño Jose Crossa (2020)
This research study the genomic-enabled prediction accuracy of the composition of the following sparse testing allocation design: (1) all non-overlapping (0 overlapping) lines in environments, (2) all overlapping (0 non-overlapping) lines tested in all the environments, and (3) combinations of the two previous cases where certain numbers of non-overlapping (NO)/overlapping (O) lines were distributed in the environments. We also studied cases where the size of the testing population was decreased. The study used two large maize data sets (T1 and T2). Four different genomic-enabled prediction models were studied, two models (M1 and M2) that do not include the genomic × environment interaction (GE), whereas models M3 and M4 incorporate two forms of modeling GE. The results show that genome-based models including GE (M3 and M4) captured more genetic variability with the GE component than the other models for both data sets. Also, models M3 and M4 provide higher prediction accuracy than models M1 and M2 for the different allocation designs comprising different combinations of NO/O lines in environments. Results indicate that substantial savings of testing resources can be achieved by optimizing the allocation design using genome-based models including genomic × environment interaction.
Dataset
CIMMYT Maize Genetic Resource Lines
Terence Molnar Juan Burgueño Jose Crossa (2020)
CIMMYT makes available to the public a set of maize inbred lines called CIMMYT Maize Genetic Resource Lines (CMGRL). The CMGRLs are derived from crosses between elite CIMMYT lines and landrace accessions, populations or synthetics from the CIMMYT Germplasm Bank. CMGRLs are intended to be used by breeders as sources of novel alleles for traits of economic importance. These lines should also be of interest to maize researchers who are not breeders but are studying the underlying genetic mechanisms of abiotic and biotic traits. The inaugural group of CMGRLs includes five subtropical-adapted lines with tolerance to drought during flowering and grain-fill and four tropical adapted lines for Tar Spot Complex resistance.
Dataset
Evaluation of Maize Landraces for Drought Tolerance in 2014
Terence Molnar Martha Willcox Juan Burgueño (2016)
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Dataset
Evaluation of Maize Landraces for Drought Tolerance in 2014
Terence Molnar Martha Willcox Juan Burgueño (2016)
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Dataset
Evaluation of Maize Landraces for Drought Tolerance in 2015
Terence Molnar Samuel Trachsel Juan Burgueño (2018)
Maize landraces were evaluated for drought tolerance in three locations in 2015.
Dataset
Evaluation of maize pre-breeding materials under the Seeds of Discovery initiative in 2017
Terence Molnar Marcela Carvalho Juan Burgueño Jose Crossa Cesar Petroli Monica Mezzalama Sarah Hearne (2019)
These data describe the evaluation of landrace-derived pre-breeding materials for biotic and abiotic stress resistance as well as for general yield potential in 2017. Populations of interest for drought stress during flowering time, heat stress during flowering time, and Tar Spot tolerance were evaluated for yield potential and response to the stresses under the MasAgro Biodiversidad project. Populations of interest for MCMV tolerance were evaluated for response to stress under the MAIZE CRP project.
Dataset
Achla Sharma Juan Burgueño Prashant Vikram Nitika Sandhu Satinder Kaur Parveen Chhuneja (2023)
Artículo
Plant Nitrogen Use Efficiency Pre-Breeding Lines Genome-Wide Association Study Marker Trait Association CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT PRE-BREEDING BREEDING LINES NITROGEN LANDRACES GENETIC MARKERS