CIMMYT Maize Line (CML) SNPs Generated Using DArTseq Genotyping

Sarah Hearne jiafa chen Cesar Petroli (2016, [Dataset])

This set of genotypic data was used for the analyses described in the paper: Chen J, Zavala C, Ortega N, Petroli C, Franco J, Burgueño J, et al. (2016) The Development of Quality Control Genotyping Approaches: A Case Study Using Elite Maize Lines. PLoS ONE 11(6): e0157236. doi:10.1371/journal.pone.0157236

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

TAMASA Nigeria. Agronomy Panel Survey 2016. Crop cut data

Oyakhilomen Oyinbo Jordan Chamberlin Julius Adewopo (2017, [Dataset])

This data covers the crop aspect of the Agronomy Panel Survey (APS) implemented in 99 selected communities across 17 LGAs in 22 randomly selected 10km x 10 km sampling grids from Kano, Kaduna and Katsina States. The XLS file has tabs for Metadata, Variables, Data and Data history.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

DArTseq-derived SNPs for wheat Iranian landrace accessions

Carolina Sansaloni Cesar Petroli (2014, [Dataset])

More than 2000 Iranian wheat landrace accessions from the CIMMYT Germplasm Bank have been genotyped using the DArTSeq technology.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Pathways to sustainable intensification in Eastern and Southern Africa - Ethiopia 2015

Paswel Marenya Menale Kassie Fulgence Mishili Gideon Obare (2017, [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.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

TAMASA Ethiopia. Nutrient omission trial (NOT) datasets for 2015 and 2016 seasons

Peter Craufurd (2017, [Dataset])

Nutrient Ommission Trials (NOT's) conducted in two zones (West Showa and Jimma) in Ethiopia in 2015 and 2016. Trials comprise six nutrient management treatements, namely Control (zero fertilzer), PK, NK, PK, NPK, NPK+Ca+Mg+Zn+B. Trials were conducted on-farm with six plots per farm. Observations include soil analysis (0-20cm), biomass and grain yields

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

TAMASA Ethiopia. Agronomy Panel Survey 2016. Yield, soil and agronomy data

MESFIN KEBEDE DESTA Jordan Chamberlin Tolera Abera Goshu (2017, [Dataset])

Data from crop-cuts as part of the Agronomy Panel Survey (APS) implemented in Oromia in three Zones (East Wollega, West Showa and Jimma). The APS included 16 peasant associations and 76 communities across the western part of Ethiopia in 56 randomly selected 1 X 1 km areas from eight 10km x 10 km sampling grids. Replicated crop cuts were made on farmers maize fields and yield measured. Soil samples were also collected but have not been analysed yet.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

23rd Semi-Arid Wheat Yield Trial

Ravi Singh Thomas Payne (2017, [Dataset])

The Semi-Arid Wheat Yield Trial (SAWYT) is a replicated yield trial that contains spring bread wheat (Triticum aestivum) germplasm adapted to low rainfall, drought prone environments typically receiving less than 500 mm of water available during the cropping cycle. The combination of water-use efficiency and water responsive broad adaptation plus yield potential is important in drought environments where rainfall is frequently erratic across and within years. Stripe rust, leaf rust and stem rust, root rots, nematodes, and bunts are the key biotic constraints. Typical target environments include winter rain or Mediterranean-type drought associated with post-flowering moisture stress and heat stress such as those found at Aleppo (Syria), Settat (Morocco) and Marcos Juarez (Argentina), all classified by CIMMYT within Wheat Mega Environment 4 (Low rainfall, semi-arid environment; ME4: SA). It is distributed to 150 locations, and contains 50 entries.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

FAO-SIAC Estimating CA adoption in Guanajuato (Municipality of Valle de Santiago, Jaral del Progreso), Mexico (calibration sites)

Kai Sonder Guillaume Chomé (2017, [Dataset])

Use of remote sensing based radar images for zero tillage detection in Guanajuato (Municipality of Valle de Santiago, Jaral del Progreso), Mexico.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

FAO-SIAC Estimating CA adoption in Sinaloa, Sonora y Guanajuato; Mexico (calibration sites)

Kai Sonder Guillaume Chomé (2017, [Dataset])

Use of remote sensing based radar images for zero tillage detection in Sinaloa, Sonora y Guanajuato; Mexico.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

24th to 35th International Bread Wheat Screening Nursery

Ravi Singh Thomas Payne (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.

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