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Model prediction of depth-specific soil texture distributions with artificial neural network: A case study in Yunfu, a typical area of Udults Zone, South China.

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Title: Model prediction of depth-specific soil texture distributions with artificial neural network: A case study in Yunfu, a typical area of Udults Zone, South China.
Authors: Ding, Xiaogang1, Zhao, Zhengyong1,2, z.zhao@unb.ca, Yang, Qi2, Chen, Lina1, Tian, Qiuyan2, Li, Xiaochuan1, Meng, Fan-Rui3
Source: Computers & Electronics in Agriculture; Feb2020, Vol. 169, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 141785289
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: <searchLink fieldCode="JN" term="%22Computers+%26+Electronics+in+Agriculture%22">Computers & Electronics in Agriculture</searchLink>; Feb2020, Vol. 169, pN.PAG-N.PAG, 1p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=141785289
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.compag.2020.105217
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      – Code: eng
        Text: English
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      – TitleFull: Model prediction of depth-specific soil texture distributions with artificial neural network: A case study in Yunfu, a typical area of Udults Zone, South China.
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            NameFull: Tian, Qiuyan
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            NameFull: Li, Xiaochuan
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            – D: 01
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              Text: Feb2020
              Type: published
              Y: 2020
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              Value: 169
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