Machine learning-based evaluation of seed priming and biostimulant applications in rainfed wheat
The results demonstrated that seed priming with ZnSO<sub>4</sub> considerably expedited spike emergence, enhanced plant height, and increased biological yield, with elevated ZnSO<sub>4</sub> concentrations intensifying these effects. Foliar application of biostimulants enhanced yield components, grain yield, and protein-related characteristics. The maximum grain production (1,648 kg ha<sup>-1</sup>) was attained with 0.3% ZnSO<sub>4</sub> seed priming in conjunction with nano foliar application of Fe, Zn, and Mn, indicating synergistic nutrient uptake/use or, alternatively, the potential of prediction approaches such as regularized regressions (Ridge, Lasso, Elastic Net) were most accurate for biological yield, protein content, and harvest index, whereas XGBoost/CatBoost captured nonlinearities but were less consistent for seed-related features. Overall, ZnSO<sub>4</sub> priming combined with nano biostimulants markedly enhances rainfed wheat performance.
Authors
- Solmaz Najafı (ORCID: https://orcid.org/0000-0003-1011-7184)
- Loretta Pace (ORCID: https://orcid.org/0000-0001-6465-3279)
- Beatrice Farda (ORCID: https://orcid.org/0000-0003-4202-0352)
- Younes Rezaee Danesh (ORCID: https://orcid.org/0000-0003-1060-0264)
- Leila Sharifi
- Mahdi Ghiyasi
- Murat Tunçtürk
- Rüveyde Tunçtürk
- Bardia Talebian
Institutions
- Van Yüzüncü Yıl Üniversitesi (TR)
- University of L'Aquila (IT)
- Urmia University (IR)
Publication Details
- Journal
- PeerJ
- Published
- 2026-03-02
- DOI
- https://doi.org/10.7717/peerj.20578
- Primary Topic
- Seed Germination and Physiology
- Type
- article
- Field-Weighted Citation Impact
- 0.00