<?xml version='1.0' encoding='UTF-8'?><codeBook xmlns="ddi:codebook:2_5" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="ddi:codebook:2_5 https://ddialliance.org/Specification/DDI-Codebook/2.5/XMLSchema/codebook.xsd" version="2.5"><docDscr><citation><titlStmt><titl>Dry matter production mean, dry matter production coefficient of variation, proportion of dry matter from crops</titl><IDNo agency="DOI">doi:10.7910/DVN/UKJCFT</IDNo></titlStmt><distStmt><distrbtr source="archive">Harvard Dataverse</distrbtr><distDate>2020-01-30</distDate></distStmt><verStmt source="archive"><version date="2023-03-09" type="RELEASED">1</version></verStmt><biblCit>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</biblCit></citation></docDscr><stdyDscr><citation><titlStmt><titl>Dry matter production mean, dry matter production coefficient of variation, proportion of dry matter from crops</titl><IDNo agency="DOI">doi:10.7910/DVN/UKJCFT</IDNo></titlStmt><rspStmt><AuthEnty>Fraval, Simon</AuthEnty><AuthEnty affiliation="International Center for Tropical Agriculture - CIAT">Mutua, John</AuthEnty><AuthEnty affiliation="International Center for Tropical Agriculture (CIAT)">Notenbaert, An</AuthEnty><AuthEnty affiliation="International Livestock Research Institute (ILRI)">Thornton, Philip</AuthEnty><AuthEnty affiliation="International Livestock Research Institute (ILRI); University of Edinburgh">Duncan, Alan</AuthEnty></rspStmt><prodStmt><producer abbr="CIAT">International Center for Tropical Agriculture</producer><producer abbr="ILRI">International Livestock Research Institute</producer><producer>University of Edinburgh</producer><prodDate>2019-12-20</prodDate></prodStmt><distStmt><distrbtr source="archive">Harvard Dataverse</distrbtr><contact affiliation="Alliance of Bioversity International and CIAT" email="alliance-dm@cgiar.org">Alliance Data Management</contact><depositr>Mwanzia, Leroy</depositr><depDate>2020-01-29</depDate></distStmt><holdings URI="https://doi.org/10.7910/DVN/UKJCFT"/></citation><stdyInfo><subject><keyword xml:lang="en">Agricultural Sciences</keyword><keyword xml:lang="en">Earth and Environmental Sciences</keyword><keyword vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_926">Biomass</keyword><keyword vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_36108">Forage</keyword><keyword vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_2832">Feed grasses</keyword><keyword vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_2829">Feed crops</keyword><keyword vocab="Research Region">Africa</keyword><keyword vocab="Research Lever">Multifunctional Landscapes</keyword><keyword vocab="Research Lever">Crops for Nutrition and Health</keyword><topcClas vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_4397">Livestock</topcClas></subject><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.</abstract><sumDscr><timePrd cycle="P1" event="start" date="2015-01-01">2015-01-01</timePrd><timePrd cycle="P1" event="end" date="2015-12-31">2015-12-31</timePrd><nation>Kenya</nation><nation>Uganda</nation><nation>Tanzania, United Republic of</nation><nation>Ethiopia</nation><nation>Rwanda</nation><nation>Burundi</nation><geogUnit>300m at the equator / pixel size 0.003</geogUnit><dataKind>Geospatial Data</dataKind><dataKind>Geographic Data</dataKind><dataKind>Raster</dataKind></sumDscr></stdyInfo><method><dataColl><sources/></dataColl><anlyInfo/></method><dataAccs><setAvail/><useStmt/><notes type="DVN:TOU" level="dv">&lt;P>&lt;a rel="license" href="http://creativecommons.org/licenses/by/4.0/" target="_blank">&lt;img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" />&lt;/a>&lt;br />&#xd;
These data and documents are licensed under a &lt;a href="http://creativecommons.org/licenses/by/4.0/" target="_blank"> Creative Commons Attribution 4.0 International license.&lt;/a> You may copy, distribute and transmit the data as long as you acknowledge the source through proper &lt;a href="http://best-practices.dataverse.org/data-citation/" target="_blank">data citation&lt;/a>.&lt;/P></notes></dataAccs><othrStdyMat/></stdyDscr><otherMat ID="f3674507" URI="https://dataverse.harvard.edu/api/access/datafile/3674507" level="datafile"><labl>DMPcropProp.tif</labl><txt>The proportion of dry matter from crops over 2015 in East Africa</txt><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">image/tiff</notes></otherMat><otherMat ID="f3674506" URI="https://dataverse.harvard.edu/api/access/datafile/3674506" level="datafile"><labl>DMPcv.tif</labl><txt>Coefficient of variation for dry-matter production in 2015 in East Africa</txt><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">image/tiff</notes></otherMat><otherMat ID="f3674505" URI="https://dataverse.harvard.edu/api/access/datafile/3674505" level="datafile"><labl>DMPmean.tif</labl><txt>Mean dry-matter production over 2015 in East Africa</txt><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">image/tiff</notes></otherMat></codeBook>