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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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Apr 4, 2019 - Building resilient integrated crop-livestock farming systems
Wamatu, Jane; Asmare, Yonas, 2019, "Improved Barley Near Infra-red Spectroscopy (NIRS) equation", https://hdl.handle.net/20.500.11766.1/CWW2TQ, MELDATA, V1
A total of 700 spring barley straw samples of genotypic diversity from diverse environments in Morocco were selected and scanned using a FOSS Near Infra-red Spectroscopy (NIRS) System 5000 spectrophotometer in the 1100nm to 2498nm spectral region. Calibration equations for feed q...
Unknown - 19.8 KB - MD5: c2fec16f0e2771f8ae49e108b71c99e2
Comma Separated Values - 21.8 KB - MD5: c1c527d16f3facf196453ef173e4fa8f
Comma Separated Values - 164.7 KB - MD5: 8027347a33ab010ab53fd2bfb1efbd6e
Comma Separated Values - 718 B - MD5: 1ab6a5538cc3d4963666df4b33e3eeb3
Comma Separated Values - 244 B - MD5: 2ac18030c938d2a123ad92b5684ed662
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