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Part 1: Document Description
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Citation |
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Title: |
Dry matter production mean, dry matter production coefficient of variation, proportion of dry matter from crops |
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Identification Number: |
doi:10.7910/DVN/UKJCFT |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2020-01-30 |
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Version: |
1 |
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Bibliographic Citation: |
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 |
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Citation |
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Title: |
Dry matter production mean, dry matter production coefficient of variation, proportion of dry matter from crops |
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Identification Number: |
doi:10.7910/DVN/UKJCFT |
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Authoring Entity: |
Fraval, Simon |
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Mutua, John (International Center for Tropical Agriculture - CIAT) |
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Notenbaert, An (International Center for Tropical Agriculture (CIAT)) |
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Thornton, Philip (International Livestock Research Institute (ILRI)) |
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Duncan, Alan (International Livestock Research Institute (ILRI); University of Edinburgh) |
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Producer: |
International Center for Tropical Agriculture |
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International Livestock Research Institute |
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University of Edinburgh |
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Date of Production: |
2019-12-20 |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Alliance Data Management |
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Depositor: |
Mwanzia, Leroy |
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Date of Deposit: |
2020-01-29 |
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Holdings Information: |
https://doi.org/10.7910/DVN/UKJCFT |
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Study Scope |
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Keywords: |
Agricultural Sciences, Earth and Environmental Sciences, Biomass, Forage, Feed grasses, Feed crops, Africa, Multifunctional Landscapes, Crops for Nutrition and Health |
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Topic Classification: |
Livestock |
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Abstract: |
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 and deficits can be supplemented with imports from other locations. Instead of monitoring feed availability and quality directly, we estimate proxies, including: length of cropping period (LCP), total annual animal feed production, coefficient of variation of feed production and the proportion of crop residues. Remotely sensed and other spatially representative data provide a basis for generating these proxies. |
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Time Period: |
2015-01-01-2015-12-31 |
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Country: |
Kenya, Uganda, Tanzania, United Republic of, Ethiopia, Rwanda, Burundi |
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Geographic Unit(s): |
300m at the equator / pixel size 0.003 |
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Kind of Data: |
Geospatial Data |
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Kind of Data: |
Geographic Data |
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Kind of Data: |
Raster |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
<P><a rel="license" href="http://creativecommons.org/licenses/by/4.0/" target="_blank"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br /> These data and documents are licensed under a <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank"> Creative Commons Attribution 4.0 International license.</a> You may copy, distribute and transmit the data as long as you acknowledge the source through proper <a href="http://best-practices.dataverse.org/data-citation/" target="_blank">data citation</a>.</P> |
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Other Study Description Materials |
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Label: |
DMPcropProp.tif |
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Text: |
The proportion of dry matter from crops over 2015 in East Africa |
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Notes: |
image/tiff |
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Label: |
DMPcv.tif |
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Text: |
Coefficient of variation for dry-matter production in 2015 in East Africa |
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Notes: |
image/tiff |
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Label: |
DMPmean.tif |
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Text: |
Mean dry-matter production over 2015 in East Africa |
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Notes: |
image/tiff |