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Prediction of Total Soluble Solids in Apricot Using Adaptive Boosting Ensemble Model Combined with NIR and High-Frequency UVE-Selected Variables.

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Title: Prediction of Total Soluble Solids in Apricot Using Adaptive Boosting Ensemble Model Combined with NIR and High-Frequency UVE-Selected Variables.
Authors: Gao, Feng1,2 (AUTHOR), Xing, Yage1,2,3,4 (AUTHOR), Li, Jialong1,3,4 (AUTHOR), Guo, Lin1,3,4 (AUTHOR), Sun, Yiye5 (AUTHOR), Shi, Wen1,5 (AUTHOR), Yuan, Leiming2,5 (AUTHOR)
Source: Molecules. Apr2025, Vol. 30 Issue 7, p1543. 12p.
Database: Academic Search Ultimate
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DbLabel: Academic Search Ultimate
An: 184445092
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  Data: Prediction of Total Soluble Solids in Apricot Using Adaptive Boosting Ensemble Model Combined with NIR and High-Frequency UVE-Selected Variables.
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  Data: <searchLink fieldCode="JN" term="%22Molecules%22">Molecules</searchLink>. Apr2025, Vol. 30 Issue 7, p1543. 12p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=184445092
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      – Type: doi
        Value: 10.3390/molecules30071543
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      – Code: eng
        Text: English
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        StartPage: 1543
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      – TitleFull: Prediction of Total Soluble Solids in Apricot Using Adaptive Boosting Ensemble Model Combined with NIR and High-Frequency UVE-Selected Variables.
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              Text: Apr2025
              Type: published
              Y: 2025
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