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Autor: Cesar Petroli
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
Melaku Gedil Ana Luisa Garcia-Oliveira Nnanna Unachukwu Cesar Petroli Sarah Hearne Abebe Menkir (2023)
Artículo
Genetic Relationship Desirable Target Traits Parental Selection CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENETIC STRUCTURES INBRED LINES MAIZE BREEDING PROGRAMMES
Flaviane Malaquias Costa Natália Almeida Rafael Vidal Charles Clement Fábio Freitas Cesar Petroli Elizabeth Veasey (2021)
This dataset contains the genotypic data used identify dispersal patterns of maize genetic diversity in the lowlands of South America. In the study, 184 maize accessions were characterized with 5,313 single nucleotide polymorphisms (SNPs).
Dataset
BAFFOUR BADU-APRAKU Ana Luisa Garcia-Oliveira Cesar Petroli Sarah Hearne Melaku Gedil (2020)
DArTSeq SNPs were generated for 436 early and extra-early maturing maize inbreds developed by the IITA maize improvement program as well as three inbred maize lines developed by CIMMYT. SNP calling was done using a proprietary analytical pipeline developed by DArT P/L. The study aimed at investigating genetic diversity and the population structure of this specific set of samples.
Dataset
Taller: "Aprovechamiento De Los Atlas Moleculares De Maíz Y Trigo." Diciembre 2015
Carolina Sansaloni Cesar Petroli Jorge Franco Gordon Stephen Sebastian Raubach Sarah Hearne Kate Dreher (2015)
PROPÓSITO GENERAL DE APRENDIZAJE: Al finalizar el taller, los participantes serán capaces de utilizar los atlas moleculares de maíz y trigo para el estudio, conservac ión y aprovechamiento de la diversidad genética. A través de un taller se desarrollarán capacidades en los participantes para que aprovechen los atlas moleculares de maíz y trigo generados por el proyecto MasAgro-Biodiversidad; para lo cual se utilizará la exposición, demostraciones prácticas, análisis de casos y discusiones grupales. Se desarrollarán los siguientes ejes temáticos: 1. Fundamentos de la técnica de genotipificación por secuenciación (GbS) 2. An álisis de la diversidad genética para su conservación y aprovechamiento 3. Utilización de los atlas moleculares de maíz y trigo desarrollados por MasAgro - Biodiversidad
Dataset
Use of remote sensing for linkage mapping and genomic prediction for common rust resistance in maize
Alexander Loladze Francelino Rodrigues Cesar Petroli Felix San Vicente Garcia Bruno Gerard Osval Antonio Montesinos-Lopez Jose Crossa Johannes Martini (2024)
Artículo
Common Rust Rp1 Locus CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RUSTS REMOTE SENSING VEGETATION INDEX MAIZE CHROMOSOME MAPPING
Alexander Loladze Francelino Rodrigues Cesar Petroli Felix San Vicente Garcia Bruno Gerard Osval Antonio Montesinos-Lopez Jose Crossa Johannes Martini (2023)
Disease resistance improvement efforts in plant breeding can help to reduce the negative impact of biotic stresses on crop production.Disease resistance can be assessed through a labor-intensive process of assigning visual scores (VS) of susceptibility (or resistance) by specially trained staff. Remote sensing (RS) tools can also be used to measure traits such as vegetation indices that can also be used to assess plant responses to diseases. This dataset contains phenotypic and genotypic data from a two-year evaluation trial of three newly developed biparental populations of maize doubled haploid lines (DH). Data from VS and RS methods for assessing common rust resistance were used in genome wide association study (GWAS) as well as genomic prediction (GP) analyses. A report on the comparison of the results of these analyses is provided in the accompanying article.
Dataset
Replication Data for: Genomic Prediction of Gene Bank Wheat Landraces
Jose Crossa DIEGO JARQUIN Jorge Franco Paulino Pérez-Rodríguez Juan Burgueño Carolina Saint Pierre Prashant Vikram Carolina Sansaloni Cesar Petroli Deniz Akdemir Clay Sneller Matthew Paul Reynolds Thomas Payne Carlos Guzman Roberto Peña Peter Wenzl Sukhwinder Singh (2023)
Genomic prediction methods may be used to enhance efforts to rapidly introgress traits of interest from exotic germplasm into elite materials. This study examined the performance of different genomic prediction models using genotypic and phenotypic data related to 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in germplasm banks. The Mexican and Iranian collections were evaluated under optimal, drought, and heat conditions for several traits including the highly heritable traits, days to heading (DTH), and days to maturity (DTM). The results of the different analyses are reported in the accompanying journal article.
Dataset
Carolina Sansaloni Jorge Franco Bruno Santos Lawrence Percival-Alwyn Cesar Petroli Jaime Campos Kate Dreher Thomas Payne David Marshall Benjamin Kilian Iain Milne Sebastian Raubach Paul Shaw Gordon Stephen Carolina Saint Pierre Juan Burgueño Jose Crossa Huihui Li Andrzej Kilian Peter Wenzl Ahmed Amri Cristobal Uauy Marianne Bänziger Mario Caccamo Kevin Pixley (2020)
A diverse panel of domesticated hexaploid and tetraploid wheat lines and their tetraploid and diploid wild relatives were genotyped using the DArtSeq technology and characterized in a global wheat diversity analysis.
Dataset