Standard Operating Procedure (SOP) for digital imaging and quantification of banana weevil damage using Ilastik and ImageJ (Fiji)

The quantification of weevil damage on banana corms is an important task when assessing resistance. In the process of analysing hundreds of samples for weevil damage, there is an increased likelihood of error especially when using expert visual scoring observations. This necessitates the need for reliable and objective high-throughput digital phenotyping methods using analysis tools such as with ImageJ (Elliot et al., 2022). Accurate and reliable data is essential in crop pathology research and in breeding programs as they serve as basis to elucidate susceptibility and resistance levels in breeding germplasm (Li et al., 2020). Digital imaging coupled with computer software tools provide powerful features for image segmentation, classification, and measurement, enabling the quantification of weevil damage on banana corms in a precise and efficient manner. By utilizing Ilastik's machine learning algorithms and ImageJ’s extensive image processing capabilities, we can effectively analyse digital images of banana corms damaged by weevils (Berg et al., 2019; Schneider et al., 2012). The combination of these tools allows for accurate identification and assessment of damage, as well as the objective extraction of relevant quantitative measurements for further analysis.