Advanced computational approaches for predicting sunflower yield: Insights from ANN, ANFIS, and GEP in normal and salinity stress environments

• Sanaz Khalifani,

  Roles Conceptualization, Methodology

  Affiliation Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran

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• Reza Darvishzadeh ,

  Roles Project administration, Supervision, Writing – review & editing

  * E-mail: r.darvishzadeh@urmia.ac.ir (RD); mkordrostami@aeoi.org.ir (MK)

  Affiliation Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran

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• Majid Montaseri,

  Roles Data curation, Formal analysis, Validation, Writing – original draft

  Affiliation Department of Water Engineering, Faculty of Agriculture, Urmia University, Urmia, Iran

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• Sarvin Zaman Zad Ghavidel,

  Roles Resources, Software, Supervision

  Affiliation Department of Water Engineering, Faculty of Agriculture, Urmia University, Urmia, Iran

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• Hamid Hatami Maleki,

  Roles Validation, Writing – original draft, Writing – review & editing

  Affiliation Department of Plant Production and Genetics, Faculty of Agriculture, University of Maragheh, Maragheh, Iran

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• Mojtaba Kordrostami

  Roles Project administration, Supervision

  * E-mail: r.darvishzadeh@urmia.ac.ir (RD); mkordrostami@aeoi.org.ir (MK)

  Affiliation Nuclear Agriculture Research School, Nuclear Science and Technology Research Institute (NSTRI), Karaj, Iran

  https://orcid.org/0000-0003-0314-1354

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