4.6 Article

Thermographic assessment of scab disease on apple leaves

Journal

PRECISION AGRICULTURE
Volume 12, Issue 5, Pages 699-715

Publisher

SPRINGER
DOI: 10.1007/s11119-010-9212-3

Keywords

Apple scab; Remote sensing; Disease quantification; Thermal imaging; Transpiration rate; Venturia inaequalis

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Phytopathogenic fungi may affect both the cuticular and the stomatal conductance of plant tissue resulting in significant modifications of leaf temperature. Venturia inaequalis colonizes apple leaves below the cuticle (subcuticularly) causing scab disease. The suitability of digital infrared thermography for sensing and quantifying apple scab was assessed by investigating the effects of V. inaequalis on the water balance of apple leaves in relation to the disease stage and the severity of scab. Transpiration was measured by infrared thermo-imaging to evaluate spatial heterogeneity of the leaves in response to localized infections. Fungal development was assessed microscopically. Subcuticular growth of the pathogen caused localized decreases in leaf temperature before symptoms appeared that significantly increased the maximum temperature difference (MTD) of leaves. The MTD increased with scab development and was strongly correlated to the size of infection sites (rA(linear)(2) = 0.85) and overall disease severity (% diseased leaf area, rA(square)(2) = 0.71). In later stages of the disease, the MTD decreased because of leaf senescence. Thermographic measurements revealed differences in disease severity resulting from disease stage, resistance of host tissue and differences in the aggressiveness of V. inaequalis isolates. Subcuticular growth of the pathogen was beyond the area of conidia production, therefore, the area of leaf with increased transpiration was larger than the scab lesions; the proportion decreased from > 70% in the early stages to < 20% for mature lesions. Leaf transpiration was increased by all stages of scab development, therefore, MTD may be used not only for the differentiation between diseased and non-diseased leaves, but also for disease quantification, e.g. in screening systems and monitoring in precision agriculture.

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