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Selecciona los temas de tu interés y recibe en tu correo las publicaciones más actuales
Sivakumar Sukumaran Matthew Paul Reynolds Carolina Sansaloni (2017, [Dataset])
GWAS identifies common loci under stressed and non-stressed environments.
MESFIN KEBEDE DESTA (2017, [Dataset])
This files ontains yiedl and soils data coillected by CSA (Central Statistical Agency) from four zones in Oromia (East Showa, Wollega, West and South West Showa and Jimma) and one Zone in Amhara (West Gojjam). A total of 38 primary sampling units were covered and making a total of 383 sampling points. Unreplicated crop cuts were made on farmers maize fields and yield measured. Soil samples were also collected at 0-20 and 20-50cm but are not all analysed yet.
47th International Durum Screening Nursery
Karim Ammar Thomas Payne (2020, [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.
Grain yield and stability of white early hybrids in the highland valleys of Mexico
Prasanna Boddupalli Jose Crossa (2017, [Dataset])
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Mary-Francis LaPorte Pattama Hannok Peter Bradbury Jose Crossa natalia palacios rojas Christine Diepenbrock (2024, [Dataset])
Vitamin A deficiency continues to cause challenges around the world including in areas where maize is an important component of human diets. Biofortification offers one solution for alleviating this deficiency. A Carotenoid Association Mapping panel, developed by the International Maize and Wheat Improvement Center (CIMMYT) contains 380 inbred lines adapted to tropical and subtropical environments that have varying grain concentrations of provitamin A and other health-beneficial carotenoids. The data in this study were used to assess the accuracy of several genomic prediction (GP) strategies for maize grain carotenoid traits within and between four environments in Mexico. Results are provided for these strategies including Ridge Regression-Best Linear Unbiased Prediction (including all markers versus subsets of markers), Elastic Net, Reproducing Kernel Hilbert Spaces, and Least Absolute Shrinkage and Selection Operator. The findings described in the accompanying journal article indicate the utility of genomic prediction methods for grain carotenoid traits and could inform their resource-efficient implementation in biofortification breeding programs.
Pathways to sustainable intensification in Eastern and Southern Africa - general overview
Paswel Marenya Menale Kassie Fulgence Mishili Gideon Obare (2016, [Dataset])
The Adoption Pathways project was part of a portfolio of projects that has contributed to the broader theme of sustainable intensification research led by the International Maize and Wheat Improvement Center (CIMMYT) and made possible by the contribution of several teams from national and international research groups brought together by funding from the Australian Centre for International Agricultural Research (ACIAR). The project was undertaken in the five Eastern and Southern African countries of Ethiopia, Kenya, Malawi, Mozambique and Tanzania. 1. Gender disaggregated three wave panel data set (2010/11, 2013), building on a legacy dataset collected under a related ACIAR funded project (SIMLESA) is now being developed covering close to 3500 households in each data wave across the five project countries. The 2015/16 data will be available in due course. 2. Several empirical evaluations of the gender gaps in technology adoption, food security and market access have been completed and published. 3. These results have been shared in various policy forums including but not limited to annual project meetings. In order to achieve its full impact in the coming years; we propose that new projects and initiatives based on the work of the Adoption Pathways project be established. These should focus on capacity building for the analysis of panel datasets, continued work on studying intrahousehold input allocation and sharing of agricultural output and scaling up the findings from this project to influence next generation of sustainable agriculture policies.
XUECAI ZHANG (2016, [Dataset])
Replication data for: Identification of QTL for early vigor and stay-green conferring tolerance to drought in two connected advanced backcross populations in tropical maize (Zea mays L.) We aimed to identify quantitative trait loci (QTL) for secondary traits related to grain yield (GY) in two BC1F2:3 backcross populations (LPSpop and DTPpop) under well-watered (4 environments; WW) and drought stressed (6; DS) conditions to facilitate breeding efforts towards drought tolerant maize. Out of the 105 detected QTL, 53 were overdominant indicative of strong heterosis. For 14 out of 18 detected vigor QTL, as well as for eight flowering time QTL the trait increasing allele was derived from CML491. Improving drought tolerance while at the same time maintaining yield potential could be achieved by combining alleles conferring early vigor from the recurrent parent with alleles advancing flowering from the donor. The highest yielding ten entries for all population-by-irrigation treatment combination (except LPSpop WW) used in this study outyielded the best check (CML312/CML444) by 32.5% (DTPpop WW) to 60% (DTPpop DS). Moreover three entries (((CML491/DTPWC9F104)//CML491)B2/CML503; ((CML491/LPSC7F64)//CML491)B154/CML503; ((CML491/LPSC7F64)//CML491)B218/CML503) ranked within the top ten across irrigation treatments. Best performing entries identified here under drought can therefore be used as new trait donor using phenotypic and/or molecular selection.
48th International Bread Wheat Screening Nursery MAS data
Susanne Dreisigacker (2017, [Dataset])
The International Bread Wheat Screening Nursery (IBWSN) is designed to rapidly assess a large number of advanced generation (F3-F7) lines of spring bread wheat under Mega-environment 1 (ME1) which represents diversity for a wide range of latitudes, climates, daylengths, fertility conditions, water management, and (most importantly) disease conditions. The distribution of these nurseries is deliberately biased toward the major spring wheat regions of the world where the diseases of wheat are of high incidence. It is distributed to 180 locations and contains 300-450 entries.
45th International Durum Screening Nursery
Karim Ammar Thomas Payne (2017, [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.