The Alliance of Bioversity International and CIAT

Today’s global challenges of poverty, malnutrition, climate change, land degradation, and biodiversity loss call for new research, solutions, innovations, and stronger partnerships that can deliver higher impact. To respond to these challenges, and building on their complementary mandates and long collaboration, Bioversity International and the International Center for Tropical Agriculture (CIAT) have joined forces to create an Alliance.

The Alliance delivers research-based solutions that harness agricultural biodiversity and sustainably transform food systems to improve people’s lives.

To do so, the Alliance works with local, national and multinational partners across Latin America and the Caribbean, Asia and Africa, and with the public and private sectors. With partners, the Alliance generates evidence and mainstreams innovations in large-scale programmes to create food systems and landscapes that sustain the planet, drive prosperity and nourish people.

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261 to 269 of 269 Results
Grass2Cash RHoMIS baseline survey in Kenya
Feb 2, 2020
Paul, Birthe K.; Odhiambo, Ruth; Burkart, Stefan; Notenbaert, An, 2020, "Grass2Cash RHoMIS baseline survey in Kenya", https://doi.org/10.7910/DVN/EZDXPP, Harvard Dataverse, V1, UNF:6:K+pSOssczhUmJCF9dQcBhQ== [fileUNF]
This data was collected using the Rural Household Multi-Indicator Survey (RHoMIS) tool to a conduct baseline survey among 200 households in Western Kenya. The standard RHoMIS tool was extended with a feeding and forage module. The dataset can be used to understand agricultural productivity, food security, income, gender dynamics and livestock feedi...
Travel time to livestock markets,dairy markets, input suppliers, livestock service providers, financial credit providers, and water bodies
Jan 30, 2020
Fraval, Simon; Mutua, John; Notenbaert, An; Thornton, Philip; Duncan, Alan, 2020, "Travel time to livestock markets,dairy markets, input suppliers, livestock service providers, financial credit providers, and water bodies", https://doi.org/10.7910/DVN/THAQQ7, Harvard Dataverse, V1
The Techfit tool provides a means to identify suitable feed technologies to address four key constraints: dry season feed availability, growing season feed availability, feed quantity and feed quality. The feasibility of introducing each technology is assessed using proxies for seven attributes: land availability, water availability, labour, capita...
Dry matter production mean, dry matter production coefficient of variation, proportion of dry matter from crops
Jan 30, 2020
Fraval, Simon; Mutua, John; Notenbaert, An; Thornton, Philip; Duncan, Alan, 2020, "Dry matter production mean, dry matter production coefficient of variation, proportion of dry matter from crops", https://doi.org/10.7910/DVN/UKJCFT, Harvard Dataverse, V1
The Techfit tool provides a means to identify suitable feed technologies to address four key constraints: dry season feed availability, growing season feed availability, feed quantity and feed quality. It is difficult to monitor animal feed availability and quality directly, this is because biomass is not necessarily utilized on the day of growth a...
Vietnam and Indonesia daily climate data (precipitation and temperature) per sub-geographical units 2000-2018
Jan 22, 2020 - CIAT - International Center for Tropical Agriculture Dataverse
Achicanoy, Harold; Mora, Brayan; Ramirez Villegas, Julian; Prager, Steven D., 2020, "Vietnam and Indonesia daily climate data (precipitation and temperature) per sub-geographical units 2000-2018", https://doi.org/10.7910/DVN/2LRIOU, Harvard Dataverse, V1
Daily climate data (precipitation and temperature) for Vietnam and Indonesia per sub-geographical units during the period 2000-2018
SUPERSEDED - The Rural Household Multiple Indicator Survey (RHoMIS) data of 13,310 farm households in 21 countries
SUPERSEDED - The Rural Household Multiple Indicator Survey (RHoMIS) data of 13,310 farm households in 21 countries
Jan 21, 2020 - Harvard Dataverse
-, RHoMIS, 2019, "SUPERSEDED - The Rural Household Multiple Indicator Survey (RHoMIS) data of 13,310 farm households in 21 countries", https://doi.org/10.7910/DVN/9M6EHS, Harvard Dataverse, V3, UNF:6:ZnVw+OfivEtIKcZWC9iwgw== [fileUNF]
[THIS VERSION HAS BEEN SUPERSEDED AND IS KEPT ONLINE FOR LEGACY PURPOSES ONLY. PLEASE FIND THE MOST RECENT VERSION OF THE DATASET AT https://doi.org/10.7910/DVN/WS38SA] The Rural Household Multiple Indicator Survey (RHoMIS) is a standardized farm household survey approach which collects information on 753 variables covering household demographics,...
Retail Diversity for Diet Diversity - Shopping Practices Household Survey
Retail Diversity for Diet Diversity - Shopping Practices Household Survey
Jan 6, 2020 - Retail Diversity for Diet Diversity
Wertheim-Heck, S.; Raneri, J., 2020, "Retail Diversity for Diet Diversity - Shopping Practices Household Survey", https://doi.org/10.7910/DVN/W1DGGL, Harvard Dataverse, V1, UNF:6:Rrj0lsu/gGIHFwezpdPmBg== [fileUNF]
Households within the field sites were randomly selected and administered a survey to capture data on their food shopping practices and preferences and how that related to food safety concerns and practices.
Retail Diversity for Diet Diversity - Dietary Intake Data
Retail Diversity for Diet Diversity - Dietary Intake Data
Jan 6, 2020 - Retail Diversity for Diet Diversity
Raneri, J.; Hoang The Ky; Wertheim-Heck, S., 2020, "Retail Diversity for Diet Diversity - Dietary Intake Data", https://doi.org/10.7910/DVN/NRNCX0, Harvard Dataverse, V1, UNF:6:XzQpt3s1LoTCGM/jmqMmeQ== [fileUNF]
Households were randomly selected from the field sites, where women were asked to recall all the foods and drinks they consumed the previous day, and specifying where those foods were sourced from. An adapted quantiative 24hour recall methodology was applied
Retail Diversity for Diet Diversity - Retail Outlet Census
Retail Diversity for Diet Diversity - Retail Outlet Census
Jan 6, 2020 - Retail Diversity for Diet Diversity
Wertheim-Heck, S.; Raneri, J., 2020, "Retail Diversity for Diet Diversity - Retail Outlet Census", https://doi.org/10.7910/DVN/ZWBUEK, Harvard Dataverse, V1
Every retail outlet present within the field sites were registered with their details recorded
Playing Out Transformative Adaptation in CCAFS Benchmark Sites in East Africa: "When, Where, How and With Whom?"
Playing Out Transformative Adaptation in CCAFS Benchmark Sites in East Africa: "When, Where, How and With Whom?"
May 17, 2017 - CCAFS - Climate Change, Agriculture and Food Security Dataverse
Laderach, Peter; Winowiecki, Leigh; Eitzinger, Anton; Twyman, Jennifer; Shikuku, Kelvin M., 2014, "Playing Out Transformative Adaptation in CCAFS Benchmark Sites in East Africa: "When, Where, How and With Whom?"", https://doi.org/10.7910/DVN/24451, Harvard Dataverse, V5
As part of this CCAFS project we collected various types of data in order to better understand vulnerabilities of smallholder farmers in East Africa to climate change. We collected and integrated interdisciplinary datasets in order to assess the biophysical, agronomic, social and economic realities at the sites. The study was carried out in four CC...
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