Green-Synthesized ZnO Nanoparticle Seed Priming Effects on Linseed Crop Traits

Experimental data compares the effects of green-synthesized, chemically synthesized, and bulk zinc oxide nanoparticles as seed priming agents on linseed crop traits. The dataset was created by Yusuf Şavşatlı and last updated in May 2026. It includes results from field trials assessing morphological and yield-related traits under varying nanoparticle concentrations and priming durations.

Use Cases

• Modeling nonlinear relationships between nanoparticle treatments and plant traits using machine learning algorithms like KNN and Random Forest.
• Analyzing the hormetic effect of nanoparticle concentration and exposure time on crop performance.
• Comparing the efficacy of biogenic versus chemically synthesized nanoparticles for sustainable agriculture.
• Applying response surface methodology to understand interactions between nanoparticle type, concentration, and priming duration.

Strengths

• Dataset is licensed under CC-BY-4.0, allowing for open reuse.
• Description details a structured experimental design with specific nanoparticle concentrations (25, 50, 75 ppm) and priming durations (1, 2, 4 hours).
• The study employed multiple machine learning models (KNN, RF, XGBoost, etc.) and achieved a reported predictive accuracy of R² = 0.84.

Limitations

• Dataset size is 152.6 KB, indicating a very limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Field experiments assessing morphological and yield-related traits of linseed cultivar 'Yılmaz'.

Freshness

Last updated 2026-05-11 04:26:54; freshness should be verified.