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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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In accordance with scientific standards, all users of these data should make appropriate acknowledgement to the producer of the data as well as the distributor using bibliographic citation. Such citations will appear in footnotes or in the reference section of any such manuscript. The citation should use the citation standard documented in http://thedata.org/citation and as shown on the "Data Citation" section of the cataloguing information page for each dataverse study. ICARDA requests a copy of any material produced based on the data. This includes position papers, scientific reports, and graduate papers in addition to publications. All users of the data should use the related publications as a baseline for their analysis whenever possible. Doing so will be an added safeguard against misinterpretation of the data. Related publications are listed in the cataloguing information.

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While utmost care has been taken by ICARDA and data authors when collecting and compiling the data, the data is however offered "as is" with no express or implied warranty. In no event shall the data authors, the authoring institutions be liable for any actual, incidental or consequential damages arising from use of the data.

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521 to 530 of 608 Results
Feb 11, 2023 - Big Data and ICT
Biradar, Chandrashekhar, 2015, "Central Asia and NW China absolute change of annual minimum temperature 2020s_A2", https://hdl.handle.net/20.500.11766.1/FK2/LRM1Z7, MELDATA, V4
Central Asia and North-West China (Xingjiang province) absolute change of annual minimum temperature in 2020 according to IPCC near-term climate change scenario A2
Feb 11, 2023 - Big Data and ICT
Biradar, Chandrashekhar, 2015, "Central Asia and NW China absolute change of annual mean precipitation 2020s_A1b", https://hdl.handle.net/20.500.11766.1/FK2/AHVZDB, MELDATA, V5
Central Asia and North-West China (Xingjiang province) absolute change of annual mean precipitation in 2020 according to IPCC near-term climate change scenario A1b
Feb 11, 2023 - Sustainable use and management of scarce water and land resources
Strohmeier, Stefan, 2020, "Soil cracking baseline - preliminary monitoring results", https://hdl.handle.net/20.500.11766.1/FK2/XNKBCN, MELDATA, V4
The dataset contains a baseline on soil cracking: it includes preliminary monitoring results on the effect of different crops on soil cracking.
Feb 11, 2023 - Big Data and ICT
Biradar, Chandrashekhar, 2015, "Central Asia and NW China annual average of monthly minimum temperature 2020s_A1b", https://hdl.handle.net/20.500.11766.1/FK2/WDL6EV, MELDATA, V4
Central Asia and North-West China (Xingjiang province) annual average in monthly minimum temperature in 2020 according to IPCC near-term climate change scenario A1b
Feb 11, 2023 - Big Data and ICT
Biradar, Chandrashekhar, 2015, "Central Asia and NW China absolute change of the annual maximum temperature 2020s_A2", https://hdl.handle.net/20.500.11766.1/FK2/H4RWHJ, MELDATA, V4
Central Asia and North-West China (Xingjiang province) absolute change of annual maximum temperature in 2020 according to IPCC near-term climate change scenario A2
Feb 11, 2023 - Sustainable use and management of scarce water and land resources
Tarekegn, Alemu; Demsew, Yengusie, 2020, "Adaptability of Different Sweet Lupin Varieties for Feed production", https://hdl.handle.net/20.500.11766.1/FK2/LIMQJ3, MELDATA, V2
Final dataset from agronomic experiment in Gumara Maksegnit (2016), as elaborated by GARC researchers in charge for this trial (Alemu Tarekegn and Yengusie Demsew). Please contact author and contact person at ICARDA to obtain more detailed metadata or to propose collaboration.
Feb 11, 2023 - Building resilient integrated crop-livestock farming systems
Majid, Abdul, 2019, "Comparison between maize, millet and guar improved and local varieties for green fodder and dry matter yield - Pakistan 2015", https://hdl.handle.net/20.500.11766.1/FK2/R0KNBQ, MELDATA, V3
The dataset contanins a data comparison between improved maize, millet and guar variety vs. local varieties for green fodder yield (GFY) and dry matter yield (DMY). The data are from 2 farmers fields at Latifal and Saghar village at Chakwal site (Pakistan).
Feb 10, 2023 - Climate adapted crops and livestock
Bishaw, Zewdie; Niane, Abdoul Aziz, 2019, "Varietal realeases from ICARDA germplasm 2018", https://hdl.handle.net/20.500.11766.1/FK2/CHIKBH, MELDATA, V3
The dataset contains a list of ICARDA varietal releases since 1977, including pedigree, selection history and specific features.
Feb 10, 2023 - Climate adapted crops and livestock
Verma, Ramesh Pal Singh; Singh, Murari; Gyawali, Sanjaya, 2016, "Datasets on High Input Barley Trials 2014", https://hdl.handle.net/20.500.11766.1/FK2/PSLKTA, MELDATA, V3
The dataset contains the results of a high Input barley trials carried on in Morocco and Lebanon during the cropping season 2013-2014.
Feb 10, 2023 - Big Data and ICT
Biradar, Chandrashekhar, 2015, "Central Asia and NW China annual mean precipitation 2020s_A2", https://hdl.handle.net/20.500.11766.1/FK2/8HWJXZ, MELDATA, V7
Central Asia and North-West China (Xingjiang province) annual mean precipitation in 2020 according to IPCC near-term climate change scenario A2
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