Sally Duncan ¹ Adele Mcleod ² Carlos Poblete-Echeverría ^1*

• ¹ South African Grape and Wine Research Institute (SAGWRI), Faculty of AgriSciences, Stellenbosch University, Stellenbosch University, Stellenbosch, Western Cape, South Africa
• ² Department of Plant Pathology, Stellenbosch University, Stellenbosch, Western Cape, South Africa

Avocado production faces a substantial global threat in the form of Phytophthora root rot (PRR). When trees succumb to PRR, their canopy health deteriorates, leading to adverse impacts on production. To effectively implement remedial strategies, infected trees need to be identified, evaluated, and located within the field. The current commercially accepted method for determining PRR severity in canopies consists of a visual estimation using the 'Ciba-Geigy' rating scale. This rating scale incorporates a numerical severity ranking system based on a visual approach conducted by trained personnel. However, tracking tree health using visual ratings is a time-consuming process, fraught with practical challenges arising from gradual visual changes, spatial variation, and dimensions of the orchards. To address these limitations, the integration of remote sensor-based methods is proposed as a viable alternative to the visual severity ranking. A field experiment was conducted in two avocado blocks to investigate the effect of spatial resolution, phenological stages, and canopy conditions on the mapping of PRR severity. The results of this study showed that canopy management practices revealed a pronounced influence in the determination of the severity ranking using remote sensing (RS) methods and that these methods can be used as an alternative to visual estimations. Additionally, the spatial resolution of the images emerged as a significant factor, improving the estimation of severity when more detailed spatial data were incorporated into the analysis. In the most favourable scenario, an R 2 determination coefficient of 0.80 was achieved. In summary, RS approaches can provide valuable information to mitigate the effect of PRR in avocado production. However, the image characteristics and particular canopy conditions need to be carefully considered in order to deliver a reliable method that can be used for informed decision-making. Nonetheless, the results were promising and could open doors to further investigate RS methods as a subjective and efficient means of PRR severity rankings.