Publication:
Effects of Protein Hydrolysate Derived From Anchovy By-Product on Plant Growth of Primrose and Root System Architecture Analysis With Machine Learning

dc.authorscopusid6603354276
dc.authorwosidTütüncü, Mehmet/V-8966-2017
dc.contributor.authorTütüncü, Mehmet
dc.contributor.authorIDTütüncü, Mehmet/0000-0003-4354-6620
dc.date.accessioned2025-12-11T01:10:41Z
dc.date.issued2024
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Tutuncu, Mehmet] Ondokuz Mayis Univ, Fac Agr, Dept Hort, TR-55270 Samsun, Turkiyeen_US
dc.descriptionTütüncü, Mehmet/0000-0003-4354-6620en_US
dc.description.abstractProtein hydrolysates (PHs) derived from waste materials are promising for sustainable practices in agricultural production. This study evaluated the effects of PH enzymatically derived from anchovy by-products on the root system architecture (RSA) and aboveground development of potted primrose. The plants were treated with 0.5, 1.0, and 1.5 g/L concentrations of PH by drenching with 100 mL/pot at two-week intervals and irrigated once a week with 100 mL/pot during winter and twice weekly during spring. The results revealed that the 1.5 g/L treatment statistically significantly improved dry weight and leaf area, while the highest leaf chlorophyll content was observed with the 1.0 g/L treatment. The treatments did not influence leaf and flower numbers. Treatment with 1.0 g/L produced the most substantial improvement in root surface area, projected area, volume, length, tips, and forks. Additionally, the study employed machine learning (ML) algorithms, including GP, RF, XGBoost, and an ANN-based MLP. The input variables (root surface area, projected area, volume, length, tips, and forks) were assessed to model and predict the root traits. The ML and ANN algorithms' R-squared rates were noted in the following order: MLP > GP > RF > XGBoost. These outcomes hold significant implications for enhancing primrose growth.en_US
dc.description.woscitationindexScience Citation Index Expanded
dc.identifier.doi10.3390/horticulturae10040400
dc.identifier.issn2311-7524
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85191559509
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.3390/horticulturae10040400
dc.identifier.urihttps://hdl.handle.net/20.500.12712/41875
dc.identifier.volume10en_US
dc.identifier.wosWOS:001211143000001
dc.identifier.wosqualityQ1
dc.institutionauthorTütüncü, Mehmet
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.relation.ispartofHorticulturaeen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAmino Acidsen_US
dc.subjectImage Analysisen_US
dc.subjectMachine Learningen_US
dc.subjectOrnamental Planten_US
dc.subjectRoot Developmenten_US
dc.subjectFish Wasteen_US
dc.subjectSustainabilityen_US
dc.titleEffects of Protein Hydrolysate Derived From Anchovy By-Product on Plant Growth of Primrose and Root System Architecture Analysis With Machine Learningen_US
dc.typeArticleen_US
dspace.entity.typePublication

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