Author: Thanda Dhliwayo

Replication Data for: Estimation of Physiological Genomic Estimated Breeding Values (PGEBV) Combining full Hyperspectral and Marker Data Across Environments for Grain Yield Under Combined Heat and Drought Stress in Tropical Maize (Zea mays L.)

Samuel Trachsel Thanda Dhliwayo Mathias Trachsel (2019)

This file provides supporting material for the manuscript entitled ' Estimation of Physiological Genomic Estimated Breeding Values (PGEBV) Combining full Hyperspectral and Marker Data Across Environments for Grain Yield Under Combined Heat and Drought Stress in Tropical Maize (Zea mays L.)'. The file includes spreadsheets containing information on the experimental structure ('Experimental structure' spreadsheet), agronomic data ('Agronomic data' spreadsheet), hyperspectral data ('Hyperspectral data' spreadsheet) and molecular marker information ('markerdata' spreadsheet). A separate self explanatory summary of the information contained in the file can be found the the 'Read me first' spreadhsheet.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Replication Data for: Bayesian linear regression near infrared spectroscopy (NIR) to predict provitamin A carotenoids content in maize breeding programs

Jose Crossa Thanda Dhliwayo THOKOZILE NDHLELA natalia palacios rojas (2021)

Vitamin A deficiency (VAD) is a public health problem worldwide. For countries with a high per capita consumption of maize, breeding varieties with higher provitamin A carotenoid content than normal yellow maize — biofortification — can be a viable strategy to reduce VAD. Selection for provitamin A carotenoid content uses molecular markers and phenotypic data generated using expensive and laborious wet lab analyses. Near-infrared spectroscopy (NIRS) could be a fast and cheap method to measure carotenoids. This dataset contains carotenoid and NIRS data from 1857 tropical maize samples used as a training set to predict provitamin A carotenoid content of an independent set of 650 tropical maize samples using Bayesian linear regression models. The datasets contain information about specific carotenoids measured and the NIRS values measured at different wavelengths. The results of the analysis are described in the accompanying article.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Replication Data for: Genomic Prediction with Genotype by Environment Interaction Analysis for Kernel Zinc Concentration in Tropical Maize Germplasm

Edna Mageto Jose Crossa Paulino Pérez-Rodríguez Thanda Dhliwayo natalia palacios rojas XUECAI ZHANG (2020)

The Zinc association mapping (ZAM) panel is a set of 923 elite inbred lines from the International Maize and Wheat Improvement Center (CIMMYT) biofortification breeding program. The panel represented wide genetic diversity for kernel Zn and is comprised of several lines with tolerance/resistance to an array of abiotic and biotic stresses commonly affecting maize production in the tropics, improved nitrogen use efficiency, and grain nutritional quality. The ZAM panel_923_LINES_GENO and Zinc association mapping (ZAM) panel_phenotypic data are two files with GBS and phenotypic data for zinc (Zn) from this population. From the ZAM panel, four inbred lines (two with high-Zn and two with low-Zn) were selected and used to form the bi-parental populations, namely DH population1 and DH population2. Genotypic and phenotypic data corresponding to these populations are DH populations1&2_255_LINES_GENO and DH population1_phenotypic data and DH population2_phenotypic data

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Replication Data for: Genomic prediction of kernel zinc content in multiple maize populations using genotyping-by-sequencing and repeat amplification sequencing markers

Thanda Dhliwayo Edna Mageto Michael Olsen Jose Crossa Prasanna Boddupalli XUECAI ZHANG (2020)

An association-mapping panel (DTMA) and two DH populations (DH1 and DH2) were used in the current study, which in total includes 487 materials. The dataset includes three types of files. One is the genotype of 487 lines sequenced by GbS, named DTMA_DH2_DH3-955690.hmp.txt; one is the genotype of 487 lines sequenced by rAmpSeq named genotype-rAmpSeq.csv; and the third type of files are the phenotypic data files named DH1-phenotype.csv, DH2-phenotype.csv and DTMA-phenotype.csv.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

2021 CIMMYT Maize Latin America Product Announcement / Anuncio de Productos de Maíz de CIMMYT en Latinoamérica

Felix San Vicente Garcia Alberto Antonio Chassaigne Ricciulli Thanda Dhliwayo natalia palacios rojas XUECAI ZHANG Michael Olsen 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 Latin America and similar agro-ecological zones. Following a rigorous trialing and a stage-gate advancement process culminating in the 2020 Stage 5 trials, CIMMYT advanced a total of two new elite maize hybrids in Latin America in 2021. Phenotypic data collected in Stage 4 and Stage 5 trials for the two 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 NARS and private seed companies, in Latin America under various management and environmental conditions. Nuevos y mejorados híbridos desarrollados por el Programa Global de Maíz del CIMMYT se ponen a disposición de instituciones del sector público y privado, especialmente para aquellas instituciones colaboradoras interesadas en la comercialización y diseminación de semilla de maíz en Latinoamérica o en zonas agroecológicas similares. Después de un riguroso proceso de evaluación de germoplasma en distintas etapas que culminó en ensayos de evaluación de híbridos en etapa cinco, el CIMMYT avanzó dos nuevos híbridos élite en Latinoamérica en 2021. Datos fenotípicos recopilados en los ensayos en etapa cuatro y cinco, además de información sobre los sitios están incluidos en este conjunto de datos. Estos ensayos fueron conducidos bajo diferentes condiciones de manejo y ambientes a través de redes colaborativas con instituciones de investigación pública y empresas semilleras de Latinoamérica.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA