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The Dataverse portal of the International Center for Agricultural Research in Dry Ares (ICARDA) has been set up with the aim of making Findable, Accessible, Interoperable and Reusable (F.A.I.R.) the knowledge produced in research for development frameworks, joined by the Center and its partners. The portal is supported by the CGIAR Research Program on LIVESTOCK, the CGIAR Platform for BIGDATA in Agriculture, and is powered by CODEOBIA and hosted by Amazon Web Services (AWS). You may copy, distribute and transmit the data as long as you acknowledge the source through proper citation as shown below. You may not resale or use the data for any commercial purposes except with written permission from the respective authoring institution(s) and the author(s) concerned. By using the ICARDA Dataverse, the user expressly acknowledges that the data may contain some nonconformities, defects, or errors. No warranty is given that the data will meet the user's needs or expectations or that all nonconformities, defects, or errors can or will be corrected. The user should always verify actual data.

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21 to 30 of 4,556 Results
Nov 5, 2025 - Sustainable use and management of scarce water and land resources
Louhaichi, Mounir; Moyo, Hloniphani; Hassan, Sawsan, 2019, "The Response of Grazed Vegetation in Relation to the Type of Landscape in the Mountain Rangelands, Tajikistan", https://hdl.handle.net/20.500.11766.1/FK2/AFAJPH, MELDATA, V11
The dataset reports on information collected to investigate the response of grazed vegetation in relation to landscape type in the mountain rangelands of Tajikistan over two seasons in 2016 (autumn and spring). Slopes facing the north and south, and grazed during different season...
Nov 5, 2025 - Sustainable use and management of scarce water and land resources
Winowiecki, Leigh; Magaju, Christine; Nyaga, John; Ochenje, Ibrahim; Makui, Parmutia; Kiura, Esther; Crossland, Mary; Kuria, Anne; Valencia, Ana Maria; Muthuri, Silas; Mutua, Francisca; Mbuvi, Caroline; Maithya, Stephen; Mwende, Mercy; Muendo, Sylvester; Sinclair, Fergus, 2019, "Farmer Profiling Data - Kenya", https://hdl.handle.net/20.500.11766.1/FK2/E4MRCZ, MELDATA, V6
In order to assess the impact of the Land Restoration Program, understanding what land restoration options work, where and for whom, there is need to identify the context-specific variables that may influence the performance of the restoration options as well as their uptake. In...
Nov 5, 2025 - Building resilient integrated crop-livestock farming systems
Frija, Aymen; Ouerghemmi, Hassen; Majri, Rihab, 2020, "Phone farm survey about the impact of COVID-19 on small crop-livestock production households in Zaghouan, Tunisia", https://hdl.handle.net/20.500.11766.1/FK2/1NXHGT, MELDATA, V19
This survey aims at documenting the impact of COVID-19 on farmers performances and household livelihoods in central semi-arid Tunisia. The survey was conducted by phone, during the COVID confinement period (May 2020) with 100 representative and randomly selected farmers who were...
Nov 5, 2025 - Building resilient integrated crop-livestock farming systems
Massaoud, Ahlem; McLeod, Ross, 2021, "Dataset of key informant interviews conducted for the mid-term evaluation of the CLCA project in North Africa", https://hdl.handle.net/20.500.11766.1/FK2/5XV94T, MELDATA, V14
The dataset includes three questionnaires which are part of the mid-term evaluation of the IFAD CLCA project in North Africa.
Nov 5, 2025 - Sustainable use and management of scarce water and land resources
Bado, Vincent; Sanoussi Manzo, Maman Laminou; Amadou, Abdoulaye, 2020, "Farmer Profiling Data - Niger", https://hdl.handle.net/20.500.11766.1/FK2/O0RRZ1, MELDATA, V5
The dataset is a result of a survey conducted in Niger, inside the project "Restoration of degraded land for food security and poverty reduction in East Africa and the Sahel: taking successes in land restoration to scale". It includes socio-economical data about 1624 households....
Nov 5, 2025 - Big Data and ICT
Kosimov, Sherzod, 2015, "Soil sampling points in Fergana valley and Sogd", https://hdl.handle.net/20.500.11766.1/FK2/AEFLE7, MELDATA, V4
Soil sampling points in Fergana valley and Sogd, CRP WUE activities 2015
Nov 5, 2025 - Sustainable value chains, supportive policies and viable off-farm activities
Dosov, Botir, 2015, "CRP DS Baseline survey: Sogd Region dataset", https://hdl.handle.net/20.500.11766.1/FK2/H0EGAX, MELDATA, V11
This is the baseline dataset for CRP Dryland Systems collected from Sogd region, Tajikistan. The dataset includes responses from a household survey that covers agricultural practices, outputs, and household livelihoods.
Nov 5, 2025 - Big Data and ICT
De Pauw, Eddy; Atassi, Layal, 2019, "Annual Rainfall Likely To Be Exceeded In 9 Years Out Of 10", https://hdl.handle.net/20.500.11766.1/FK2/GLYCLI, MELDATA, V12
Annual rainfall likely to be exceeded in 9 years out of 10, in millimeters, at 30 arcsecond resolution, was prepared for the IFAD-ICARDA Project "Poverty Assessment in Sudan". Map prepared as part of three reports that detail the results of a poverty assessment and mapping projec...
Nov 5, 2025 - Big Data and ICT
Atassi, Layal; Al-Shamaa, Khaled; Biradar, Chandrashekhar, 2018, "Al_Khattem Potential Hot-spots Of Red Palm Weevil (RPW) Risk Based On Trap-data 2016", https://hdl.handle.net/20.500.11766.1/FK2/EY1UHA, MELDATA, V13
The layer was part of enhancing date palm integrated pest management and agricultural extension and technology transfer systems in Abu Dhabi project, the layer was generated from survey information on date palm in Abu Dhabi obtained from Abu Dhabi Farmers Services Center. The tra...
Nov 5, 2025 - Sustainable use and management of scarce water and land resources
Louhaichi, Mounir; Moyo, Hloniphani; Hassan, Sawsan, 2019, "The Response of Grazed Vegetation in Relation to the Type of Landscape in the Flat Rangelands, Uzbekistan", https://hdl.handle.net/20.500.11766.1/FK2/L7XSN8, MELDATA, V11
The dataset describes the information collected on the response of grazed vegetation in relation to landscape type in the flat rangelands of Uzbekistan over two seasons in 2016 (autumn and spring). We used a grazing gradient approach as a main tool to detect fine-scale changes in...
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