<mets:mets OBJID="eprint_11945" LABEL="Eprints Item" xsi:schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mets="http://www.loc.gov/METS/" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mets:metsHdr CREATEDATE="2023-07-05T14:22:01Z"><mets:agent ROLE="CUSTODIAN" TYPE="ORGANIZATION"><mets:name>OAR@ICRISAT</mets:name></mets:agent></mets:metsHdr><mets:dmdSec ID="DMD_eprint_11945_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:titleInfo><mods:title>Pilot studies on GP Crop yield estimation using Technology (Kharif 2019) using SENTINEL- 2 satellite data (in Andhra Pradesh, Telangana and Odisha States (Five Districts)) for Groundnut, Chickpea, Maize and Rice</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">M K</mods:namePart><mods:namePart type="family">Gumma</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">M D M</mods:namePart><mods:namePart type="family">Kadiyala</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">P</mods:namePart><mods:namePart type="family">Panjala</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">I</mods:namePart><mods:namePart type="family">Mohammed</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>The Government of India plans to optimize Crop Cutting Experiments (CCEs) using different technologies including satellite derived metrics on crop performance and spatial variability to guide the selection and number of ground data sites. This requires the development of an approach for different crops for the different agro-climatic regions of India. The present study plans to develop an approach for following crops viz., Groundnut, Chickpea, Rice and Maize. The above crops will be studied in five districts of three states viz. Andhra Pradesh, Telangana and Odisha. The study will use comprehensive and existing environmental, weather and management data along with satellite derived crop spatial data. This information will be modelled using statistical optimization techniques to assess the optimal numbers of CCE’s that can be undertaken.</mods:abstract><mods:classification authority="lcc">Chickpea</mods:classification><mods:classification authority="lcc">Groundnut</mods:classification><mods:classification authority="lcc">Maize</mods:classification><mods:originInfo><mods:dateIssued encoding="iso8061">2020-02</mods:dateIssued></mods:originInfo><mods:originInfo><mods:publisher>ICRISAT</mods:publisher></mods:originInfo><mods:genre>Monograph</mods:genre></mets:xmlData></mets:mdWrap></mets:dmdSec><mets:amdSec ID="TMD_eprint_11945"><mets:rightsMD ID="rights_eprint_11945_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:useAndReproduction>
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