Author: Manje Gowda

Replication Data for: Multi-generation genomic prediction of maize yield using parametric and non-parametric sparse selection indices

Marco Lopez-Cruz Yoseph Beyene Manje Gowda Jose Crossa Paulino Pérez-Rodríguez Gustavo de los Campos (2021)

Genomic prediction models may be used in plant breeding pipelines. They are often calibrated using multi-generation data and there is an open question of whether all available data or a subset of it should be used to calibrate genomic prediction models. Therefore, a study was undertaken to determine whether combining sparse selection indexes (SSIs) and kernel methods could further improve prediction accuracy when training genomic models using multi-generation data. This dataset contains the genotypic and phenotypic data from CIMMYT maize doubled haploid lines that were used to perform the analyses. The results of the analyses are presented in the accompanying article.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

2021 CIMMYT Maize Southern Africa Product Announcement

Mainassara Zaman-Allah James Gichuru Gethi Cosmos Magorokosho THOKOZILE NDHLELA Manje Gowda Amsal Tarekegne Aparna Das Prasanna Boddupalli (2021)

New and improved maize hybrids, developed by the CIMMYT Global Maize Program, are available for uptake by public and private sector partners, especially those interested in marketing or disseminating hybrid maize seed across southern Africa and similar agro-ecological zones. Following a rigorous trialing and a stage-gate advancement process culminating in Stage 5 trials, CIMMYT advanced a total of four new elite maize hybrids in Southern Africa in 2021. Phenotypic data collected in Stage 4 and Stage 5 trials for the selected hybrids as well as information about the trial sites are provided in this dataset. These trials were conducted through a network of partners, including NARES, private seed companies, and NGOs, in eastern and southern Africa under various management and environmental conditions.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

CIMMYT Maize Regional Trial Data for Eastern Africa 2016

MacDonald Jumbo Yoseph Beyene Dan Makumbi Suresh L.M. Amsal Tarekegne Tsedeke Abate Manje Gowda Vijay Chaikam Prasanna Boddupalli (2020)

The summary results of the Regional Trials for CIMMYT Maize Hybrids in Eastern Africa for 2016. The trials are: EHYB16 - Early/extra-early maturing elite pre-commercial hybrids regional trials, EIHYB16 – Early-intermediate maturing elite pre-commercial hybrids regional trial, IHYB16 (Set 1) – Intermediate maturing elite pre-commercial hybrids regional trial, IHYB16 (Set 2) – Intermediate/Late maturing elite pre-commercial hybrids regional trial, and MLN tolerant hybrids – MLN trials of promising candidate hybrids.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Replication Data for: Genetic Dissection of Resistance to Gray Leaf Spot by Combining Genome-Wide Association, Linkage Mapping and Genomic Prediction in Tropical Maize Germplasm

Sudha Nair Biswanath Das MacDonald Jumbo Dan Makumbi Suresh L.M. Yoseph Beyene Michael Olsen Prasanna Boddupalli Manje Gowda (2020)

Gray leaf spot (GLS) is a major maize foliar disease in sub-Saharan Africa that can substantially reduce yields for farmers. This dataset contains supporting phenotypic and genotypic data used in the analysis of the genetic architecture of GLS resistance in maize. The data in this paper relate to several different sets of germplasm: (1) The IMAS (Improved Maize for Africa Soils) panel with 430 lines assembled from diverse breeding programs from Africa, Asia and Latin America. (2) A DH population developed from crossing CML550 with CML494; (3) A DH population developed from crossing CML550 with CML504; (4) A DH population developed from crossing CML550 with CML511; and (5) several F3 populations The IMAS panel is a good source for genetic studies on resistance for several maize diseases and also for abiotic stress like low N conditions. The DH populations are a good source for low N discovery studies as well as for MLN and other disease resistance studies.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

CIMMYT Maize Regional Trial Data for Eastern Africa 2017

MacDonald Jumbo Yoseph Beyene Dan Makumbi Lewis Machida Suresh L.M. Amsal Tarekegne Manje Gowda Vijay Chaikam Prasanna Boddupalli (2020)

The summary results of the Regional Trials for CIMMYT Maize Hybrids in Eastern Africa for 2017. The trials include: EHYB17-Set I – Early/extra-early maturing elite pre-commercial hybrids regional trials (including external and internal checks); IHYB17-Set I – Intermediate maturing elite pre-commercial hybrids regional trial (including external and internal checks); ILHYB17 – Intermediate-Late maturing elite pre-released and released hybrids regional trials (including external and internal checks); EHYB17-Set II – Early maturing elite pre-commercial hybrids regional trials; ILHYB17 Set II – Intermediate/late maturing elite pre-commercial hybrids regional trials.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Replication Data for: Genome-Wide Association Mapping And Genomic Prediction Analyses Reveal the Genetic Architecture of Grain Yield and Flowering Time Under Drought and Heat Stress Conditions in Maize

Jill Cairns Raman Babu Manje Gowda Dan Makumbi Cosmos Magorokosho Michael Olsen Prasanna Boddupalli Yanli Lu XUECAI ZHANG (2018)

Drought stress, heat stress, and combination of drought stress and heat stress have been recognized as the major abiotic constraints to maize yields in the main production regions. The phenotypic data used in the current study had been published by Jill E. Cairns et al in 2013 in the journal of Crop Science 53 :1335–1346 ( https://dx.doi.org/10.2135/cropsci2012.09.0545). In this study, the association mapping and genomic prediction analyses were conducted in a collection of 300 tropical and subtropical maize inbred lines to reveal the genetic architecture of grain yield and flowering time under well-watered, drought stress, heat stress, and combined drought and heat stress conditions. The genetic architecture information of the grain yield and flowering time revealed in this study, and the genomic regions identified for the different trait-environment combinations are helpful accelerating the efforts on rapid development of the stress-tolerant maize germplasm through marker-assisted selection or genomic selection.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA