Heavy Metal-Induced Variability in Leaf Nutrient Uptake and Photosynthetic Traits of Avocado (Persea americana) in Mediterranean Soils: A Multivariate and Probabilistic Modeling of Soil-to-Plant Transfer Risks

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Abstract

Aims Soil contamination by heavy metals poses a serious threat to crop productivity, food safety, and ecosystem health, particularly in intensively cultivated regions. This study aimed to evaluate the impact of soil heavy metal (HM) contamination on nutrient uptake, photosynthetic performance, and bioaccumulation potential in Persea americana (avocado) orchards across the Mnasra region (Morocco). Methods Twenty representative sites were sampled, each comprising soil and mature avocado leaf tissues. Soil physicochemical properties and HM concentrations (Cd, Pb, Ni, Zn) were analyzed, while leaf samples were assessed for macronutrients (NPK, Ca, Mg), micronutrients (Fe, Mn, Zn, Cu, B), photosynthetic traits (SPAD index, chlorophyll a/b), and metal accumulation. Bioaccumulation Factors (BAFs) were calculated, and data were analyzed using multivariate techniques including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), Linear Discriminant Analysis (LDA), Partial Least Squares Regression (PLSR), and Monte Carlo Simulation. Results Results revealed wide intra-specific variability across orchards. Leaf Cd and Pb concentrations reached 0.92 and 3.54 mg/kg DW, respectively, with BAF values > 1 in multiple sites. PLSR demonstrated strong predictive power for leaf Cd (R² = 0.789) and Pb (R² = 0.772) from soil data. Monte Carlo simulations identified probabilistic exceedance of FAO/WHO thresholds for Cd and Pb in 15–25% of modeled cases. PCA and HCA distinguished five orchard clusters based on combined soil–leaf profiles. Conclusion This integrative approach confirms that soil metal contamination significantly alters avocado physiology, with site-specific patterns. The study advocates targeted soil monitoring and tailored remediation to support sustainable orchard management in vulnerable regions.

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