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UAS-based imaging for prediction of chickpea crop biophysical parameters and yield.

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Title: UAS-based imaging for prediction of chickpea crop biophysical parameters and yield.
Authors: Avneri, Asaf1,2, Aharon, Shlomi1, Brook, Anna3, Atsmon, Guy1, Smirnov, Evgeny1, Sadeh, Roy2, Abbo, Shahal2, Peleg, Zvi2, Herrmann, Ittai2, Bonfil, David J.4, Nisim Lati, Ran1, ranl@volcani.agri.gov.il
Source: Computers & Electronics in Agriculture; Feb2023, Vol. 205, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 161552561
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: UAS-based imaging for prediction of chickpea crop biophysical parameters and yield.
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  Data: <searchLink fieldCode="JN" term="%22Computers+%26+Electronics+in+Agriculture%22">Computers & Electronics in Agriculture</searchLink>; Feb2023, Vol. 205, pN.PAG-N.PAG, 1p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=161552561
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.compag.2022.107581
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      – Code: eng
        Text: English
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      – TitleFull: UAS-based imaging for prediction of chickpea crop biophysical parameters and yield.
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            – D: 01
              M: 02
              Text: Feb2023
              Type: published
              Y: 2023
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              Value: 205
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