Assessment of Peacock Spot Disease (<i>Fusicladium oleagineum</i>) in Olive Orchards Through Agronomic Approaches and UAV-Based Multispectral Imaging

Abstract

Olive leaf spot (OLS), caused by Fusicladium oleagineum, is a significant disease affecting olive orchards, leading to reduced yields and compromising olive tree health. Early and accurate detection of this disease is critical for effective management. This study presents a comprehensive assessment of OLS disease progression in olive orchards by integrating agronomic measurements and multispectral imaging techniques. Key disease parameters—incidence, severity, diseased leaf area, and disease index—were systematically monitored from March to October, revealing peak values of 45% incidence in April and 35% severity in May. Multispectral drone imagery, using sensors for NIR, Red, Green, and Red Edge spectral bands, enabled the calculation of vegetation indices. Indices incorporating Red Edge and near-infrared bands, such as Red Edge and SR705-750, exhibited the strongest correlations with disease severity (correlation coefficients of 0.72 and 0.68, respectively). This combined approach highlights the potential of remote sensing for early disease detection and supports precision agriculture practices by facilitating targeted interventions and optimized orchard management. The findings underscore the effectiveness of integrating a traditional agronomic assessment with advanced spectral analysis to improve OLS disease surveillance and promote sustainable olive cultivation.

Keywords

• olive leaf spot
• <i>Fusicladium oleagineum</i>
• multispectral imaging
• vegetation indices
• disease incidence
• precision agriculture