Significant SNPs from SeeD GWAS Analysis of Flowering Time

Jorge Alberto Romero Navarro Martha Willcox Juan Burgueño Cinta Romay Kelly Swarts Samuel Trachsel Iván Ortíz-Monasterios Felix San Vicente Garcia Gary Atlin Peter Wenzl Sarah Hearne Edward Buckler (2017, [Dataset])

The files included in this study provide significant SNPs from the gene-level analysis for days to anthesis, days to silking, altitude, and latitude within the SeeD GWAS panel. Markers shown are only those found outside high LD regions as defined in the paper: A study of allelic diversity underlying flowering-time adaptation in maize landraces. Nature Genetics. 2017: 49, 476–480. doi:10.1038/ng.3784, and included in the file: HighLD ranges.txt.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

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, [Dataset])

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.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Replication Data for: Combination of Linkage and Association Mapping with Genomic Prediction to Infer QTL Regions Associated with Gray Leaf Spot and Northern Corn Leaf Blight Resistance in Tropical Maize

Manje Gowda Yoseph Beyene Suresh L.M. David Berger (2023, [Dataset])

Gray Leaf Spot (GLS) and Northern Corn Leaf Blight (NCLB) are two pathogens with high genetic diversity that can reduce grain yield in infected maize plants.To identify population-based quantitative trait loci (QTL) for GLS and NCLB resistance, a biparental population and an association mapping panel were genotyped and were also phenotyped across multi-environments in western Kenya. This dataset includes the analyzed BLUES of the collected phenotypic data for Gray Leaf Spot GLS and NCLB resistance from the DH population and diversity panel, as well as the GBS genotypic data. The results of the analysis are reported in the accompanying article.

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Genetic diversity, population structure and genome-wide association analyses of tan spot disease resistance in a core collection of Tunisian durum wheat landraces

Carolina Sansaloni Susanne Dreisigacker Amor Yahyaoui (2023, [Dataset])

A core collection of 235 durum wheat accessions consisting mainly of landraces was genotyped and evaluated for its genetic diversity and population structure. The same collection was phenotyped for the fungal pathogen Pyrenophora triciti-repentis (cause of tan spot disease of wheat) in Tunisia to perform genome-wide association analyses. The results highlight the significance of chromosomes, 2B, 3B, 5B, and 6A as genomic regions associated with tan spot resistance.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Harvestplus household survey, Zambia 2011, section on storage and climate

Hugo De Groote Zachary Gitonga Kai Sonder (2023, [Dataset])

In this data base, representative georeferenced farmer survey data from Zambia from 2011 are combined with climate data to estimate storage losses, analyze their relationship with climate, and estimate the effect of climate change on storage losses. The storage loss data include importance of different pests (maize weevils and larger grain borer), and farmers’ estimates of storage loss due to both pests, in grain and cobs. The climate data include temperature (from WorldClim) and relative humidity (from CHIRTS) over the storage season in 2011.

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Consumer study on acceptance of instant fortified millet with the Food Processing Lab (FPL) in Dakar, Senegal

Hugo De Groote Bernard Munyua John Taylor Mario Ferruzzi Cheikh Ndiaye Isiguzoro Onyeoziri Bruce Hamaker (2022, [Dataset])

For this study, 296 consumers from Dakar, Senegal, were invited to evaluated five pearl millet flours: (a) conventional, compared to four instant-porridge flour products; (b) sifted; (c) wholegrain; (d) sifted with premix; (e) wholegrain with micronutrient premix and food-to-food fortified (FtFF). Consumers' acceptance was measured with affective tests, and their willingness-to-pay (WTP) for the products was elicited through experimental auctions under two treatments: firstly without information, then with information.

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31st International Septoria Observation Nursery

Pawan Singh Carolina Saint Pierre (2022, [Dataset])

The International Septoria Observation Nursery (earlier Septoria Monitoring Nursery – SMN) is a single replicate nursery that contains diverse spring bread wheat (Triticum aestivum) germplasm adapted to ME2 (High rainfall environment) and ME4 (Low rainfall, semi-arid environment) with total 50-100 entries and white/red grain color.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

52nd International Durum Screening Nursery

Karim Ammar Thomas Payne (2021, [Dataset])

International Durum Screening Nursery (IDSN) distributes diverse CIMMYT-bred spring durum wheat germplasm adapted to irrigated and variable moisture stressed environments. Disease resistance and high industrial pasta quality are essential traits possessed in this germplasm. It is distributed to 100 locations, and contains 150 entries.

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CIMMYT Eastern Africa 2019 Regional Trial Report

MacDonald Jumbo Mosisa Worku Regasa Yoseph Beyene Dan Makumbi Prasanna Boddupalli (2021, [Dataset])

This dataset contains the results from three regional trials carried out in Eastern Africa in 2019. Each report focuses on a different product profile. Two reports present data for product profile EA-PP1, It focuses on includes early/intermediate-maturing white maize with multiple stress tolerance (drought, low N, MLN, MSV, TLB, GLS, ear rots) for the Eastern African rainfed mid-altitude dry/wet agro-ecologies. The third report presents data for product profile EA-PP2. It focuses on late-maturing, white maize varieties with multiple stress tolerance (drought, low N, GLS, TLB, MSV, ear rots, Striga) for the Eastern African rainfed upper mid-altitude region.

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Replication Data for: Allocation of wheat lines in sparse testing for genome-based multi-environment prediction

Leonardo Abdiel Crespo Herrera Ravi Singh Suchismita Mondal Philomin Juliana DIEGO JARQUIN Jose Crossa (2021, [Dataset])

Sparse testing can be used in plant breeding and genome-based prediction. In sparse testing not all of the lines are sown in all environments. The phenotypic and genotypic data files provided in this dataset were used to execute an analysis of three general cases of the composition of the sparse testing allocation design for wheat breeding.

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