231 to 240 of 276 Results
Aug 25, 2020
Samuel, Folake; Adeyemi, Olutayo A.; Meldrum, Gennifer; Kennedy, Gina; Shittu, Oluyemisi O., 2020, "Barrier analysis for daily fruit and vegetable consumption among low income consumers in Ibadan, Nigeria", https://doi.org/10.7910/DVN/VSTM3B, Harvard Dataverse, V1, UNF:6:apuhdOFI5wQkmDQE2yKPtA== [fileUNF]
Barrier analysis is completed with at least 45 doers of the behavior of interest and 45 non-doers who do not practice the behaviour. In this case, the behaviour of interest was the consumption of an adequate quantity and diversity of fruits and vegetables by low income adults in the focal neighbourhoods. Doers and non-doers were identified based on... |
Aug 25, 2020
Truong, Mai; Meldrum, Gennifer; Kennedy, Gina; Tran, Thanh Do; Phuong, Ngothiha; Nguyen, Huu Bac, 2020, "Barrier analysis for daily fruit and vegetable consumption among low income consumers in Hanoi, Vietnam.", https://doi.org/10.7910/DVN/I53FX2, Harvard Dataverse, V1, UNF:6:b2QsoAG6DtePg0ZHxjBFtA== [fileUNF]
Barrier analysis is completed with at least 45 doers of the behavior of interest and 45 non-doers who do not practice the behaviour. In this case, the behaviour of interest was the consumption of an adequate quantity and diversity of fruits and vegetables by low income adults in the focal neighbourhoods. Doers and non-doers were selected from the l... |
Aug 4, 2020 - CIAT - International Center for Tropical Agriculture Dataverse
Hyman, Glenn Graham, 2020, "Global Climate Regions for Cassava", https://doi.org/10.7910/DVN/WFAMUM, Harvard Dataverse, V2
This map shows global climate regions for cassava cultivation. Maps were developed separately for Asia, Africa and Latin America based on Carter et al. 1992. The maps were combined into a single map for the tropical and subtropical regions of the world. The determination of the climate regions is based on mean growing season temperature, number of... |
Aug 3, 2020
Hyman, Glenn Graham; Larrea, Carlos; Farrow, Andrew, 2020, "Poverty mapping case studies", https://doi.org/10.7910/DVN/DQQIXZ, Harvard Dataverse, V1
This project developed data, information and knowledge on the spatial distribution of poverty in eight developing countries. The eight case studies included poverty and food security maps, the data sets, preprints of journal articles for a special issue of Food Policy, standardized geospatial metadata and a browse graphic showing key maps. The diff... |
Jul 28, 2020 - CIAT - International Center for Tropical Agriculture Dataverse
Farrow, A.; Muthoni-Andriatsitohaina, R.; Ongom, B.; Ojara, M., 2020, "Bean production areas in sub-Saharan Africa", https://doi.org/10.7910/DVN/8W0QK7, Harvard Dataverse, V1, UNF:6:qMkDAr5PGnQnoeiDPaQJGA== [fileUNF]
176 bean production areas were identified and reviewed using a form of the Delphi method of consensus building among experts from almost all bean producing countries of sub-Saharan Africa. Data were collected for: bean production, cropping systems and producers; seed systems; bean use and marketing; bean grain types and varieties; and abiotic and b... |
Jul 2, 2020
Perez, Lisset; Lavelle, Patrick; Rudbeck, Martin; Castro-Nunez, Augusto; Camilo, Karen; Vanegas, Martha; Sachet, Erwan; Romero Sanchez, Miguel A.; Suarez Salazar, Juan C.; Solarte, Antonio; Francesconi, Wendy; Quintero, Marcela, 2020, "Farmscape composition and livelihood sustainability in deforested landscapes of Colombian Amazonia", https://doi.org/10.7910/DVN/EJNDO5, Harvard Dataverse, V1, UNF:6:uGMP0UM98nOK4/PtM8x2Ug== [fileUNF]
A total of 341 households were interviewed, 176 (51.6%) in the Andean foothills (with cattle raising as a dominant activity), and 165 (48.4%) in the hillside area where crop farming is dominant. The sample is representative of the four municipalities, according to the Colombian Census carried out in 2005. We used a stratified optimal random samplin... |
Jun 25, 2020
Siriwan, Wanwisa; Jiménez, Jenyfer; Hemniam, Nuannapa; Saokham, Kingkan; Cuellar, Wilmer, 2020, "Surveillance and diagnostics dataset on Sri Lankan cassava mosaic virus (Fam. Geminiviridae) and CMD in Thailand", https://doi.org/10.7910/DVN/Z5TR2F, Harvard Dataverse, V1, UNF:6:v47oLjxsXGUV4c83qrYVYQ== [fileUNF]
Emergent agricultural pathogens cause severe damage worldwide. Standard surveillance and diagnostic protocols need to be evaluated and implemented at regional level, particularly with diseases caused by a wide range of pathogens that can induce similar symptoms. This dataset provides a description of surveillance and diagnostics data for CMD in Tha... |
Jun 25, 2020
Siles, Pablo; Tellez, Orlando; Peng, Yuan-Ching; Zeledón, Yasser, 2020, "Impact of NPK fertilization on upland rice yield, Nicaragua", https://doi.org/10.7910/DVN/H0HUSY, Harvard Dataverse, V1, UNF:6:t6JfXEH7AIeMiuA9WotrhA== [fileUNF]
This dataset contains information of experiments carried out upland rice in two regions of Nicaragua (Caribbean and Pacific Region), as well as a compilation of soils data from different regions in Nicaragua collected during 2019 in seed banks of rice and beans. The experiments were designed to explore the effects of N, P and K in the yield of upla... |
Jun 23, 2020 - CIAT - International Center for Tropical Agriculture Dataverse
Peng, Yuan-Ching; Siles, Pablo; Zeledón, Yasser; Dorado, Hugo Andres; Rivera-Palacio, Juan, 2020, "Upland rice from technological validation areas and community banks of seeds in Nicaragua", https://doi.org/10.7910/DVN/CKRZTT, Harvard Dataverse, V2, UNF:6:O7d0clOhMqPPoOKOo7Mhxg== [fileUNF]
This dataset contains 438 crop cycles for upland rice in 22 departments of Nicaragua that were collected with INTA (Instituto Nacional de Tecnología Agropecuaria) in the period 2016 – 2020. In the dataset, 100 and 338 records came from technological validation areas and community banks of seeds, respectively. Each location was georeferenced. Variab... |
Jun 11, 2020
Morimoto, Yasuyuki; Maundu, Patrick; Imbumi, Maryam; Kariuki, Lucy; Tumbo, Dominic, 2020, "Agro-nutrition baseline survey data of 20 villages in the Kitui district (Kenya), in 2008", https://doi.org/10.7910/DVN/NRL2WU, Harvard Dataverse, V1, UNF:6:BcPf8Mwv3q1ErBqejRpumQ== [fileUNF]
"This is a baseline survey data that was collected within the project ‘Managing agricultural biodiversity for better nutrition and health, improved livelihoods and more sustainable production systems in sub-Saharan Africa’ implemented by Bioversity International. The survey was conducted in Kitui District in Eastern Province of Kenya in September 2... |