<?xml version='1.0' encoding='UTF-8'?><metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns="http://dublincore.org/documents/dcmi-terms/"><dcterms:title>Dry matter production mean, dry matter production coefficient of variation, proportion of dry matter from crops</dcterms:title><dcterms:identifier>https://doi.org/10.7910/DVN/UKJCFT</dcterms:identifier><dcterms:creator>Fraval, Simon</dcterms:creator><dcterms:creator>Mutua, John</dcterms:creator><dcterms:creator>Notenbaert, An</dcterms:creator><dcterms:creator>Thornton, Philip</dcterms:creator><dcterms:creator>Duncan, Alan</dcterms:creator><dcterms:publisher>Harvard Dataverse</dcterms:publisher><dcterms:issued>2020-01-30</dcterms:issued><dcterms:modified>2023-03-09T14:15:09Z</dcterms:modified><dcterms:description>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.</dcterms:description><dcterms:subject>Agricultural Sciences</dcterms:subject><dcterms:subject>Earth and Environmental Sciences</dcterms:subject><dcterms:subject>Biomass</dcterms:subject><dcterms:subject>Forage</dcterms:subject><dcterms:subject>Feed grasses</dcterms:subject><dcterms:subject>Feed crops</dcterms:subject><dcterms:subject>Africa</dcterms:subject><dcterms:subject>Multifunctional Landscapes</dcterms:subject><dcterms:subject>Crops for Nutrition and Health</dcterms:subject><dcterms:date>2019-12-20</dcterms:date><dcterms:contributor>Mwanzia, Leroy</dcterms:contributor><dcterms:dateSubmitted>2020-01-29</dcterms:dateSubmitted><dcterms:temporal>2015-01-01</dcterms:temporal><dcterms:temporal>2015-12-31</dcterms:temporal><dcterms:type>Geospatial Data</dcterms:type><dcterms:type>Geographic Data</dcterms:type><dcterms:type>Raster</dcterms:type><dcterms:spatial>Kenya</dcterms:spatial><dcterms:spatial>Uganda</dcterms:spatial><dcterms:spatial>Tanzania, United Republic of</dcterms:spatial><dcterms:spatial>Ethiopia</dcterms:spatial><dcterms:spatial>Rwanda</dcterms:spatial><dcterms:spatial>Burundi</dcterms:spatial><dcterms:rights>&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></dcterms:rights></metadata>