Eggsplorer: A workflow to rapidly evaluate insect resistance based on oviposition 1 Micha Gracianna Devi, Dan Jeric Arcega Rustia Main advantages: 1. 2 . 3. Documentedimages of leaves. High throughputscreening . Handles eggsbetweenhoneydew. 4. Website-based (internal). 5. Exporteddata (.xlsx) of egg countand processedimage wit h level of confidence. Things to be optimized: • Under/overestimationof egg count . ↳The more variationin imag es fortraining, thesmarter the program becomes. Thingsto consider: 1. How low canitgo? Magnification, resolution, cost. 2. How efficientin termsof time & human resource? Acknowledgement: Bart van Marrewij k Jochen Hemmi ng Kas Swink els Lize B raat Wendy van’tWestende 1 2 1 Insect Resistance Breeding, Wageningen University and Research, The Netherlands 2 GreenhouseTechnology, WageningenUniversityandResearch, TheNetherlands Federico F. Espinosa Gina Pavloupolo u Harlino Prayud ha Keming Su 1.High quantityof samples forphenotypingpopulation. 2.Manual quantificationusingbinocularrequiresconstant focus adjustment; a lot of time is required. 3.Leafsamples aftercountingare thendiscarded; no documentation. 4.Variationin human eyecapacity; human error. Tomato Potato , Lotte Caarls Arabidopsis Challengesin conductingwhiteflyassays Abstract Up to date, conventional method is still used to quantify insect eggs for evaluating plant resistance. Commonly, this method includes the use of a binocular and manually adjusting the focus over a leaf segment, followed by counting with a ticke r whenever an egg is spotted. This procedure is laborious and require a good eye skill to distinguish the eggs. In susceptib le toma to a nd pota to plant s, whitefli es c an l ay mo re th an a hundr ed eg gs insi de a cl ip ca ge (⌀ 2 cm ). The se eg gs are sometimes packed in an area and ranges from translucent green to brown depending on the age. Moreover, whitefly eggs that are cov ere d in whit efly h oney dew and hi dden a mong trich omes are diffi cul t to det ect. Furtherm ore, t her e is a limitation to electronically document samples using images from a binocular. Eggsplorer is a workflow especially dev eloped to rapidly evaluate whitefly oviposition. This include the use of a digital microscope that can quickly capture high res olution Z-stacked collages of the whole leaf surface, then importing the images to the Eggsplorer program for egg quantific ation. A deep learning model, based on YOLOv5 , was trained to detect the eggs automatically in the images and deployed using an executable graphical user interface. As evaluated using a testing image dataset, the algorithm has an average accura cy of 0.93 with an error of ± 7 eggs per image and average r2 of 0.95, relative to the manual count.Up to date, conventional method is still used to quantify insect eggs for evaluating plant resistance. Commonly, this method includes the use of a binocular and manually adjusting the focus over a leaf segment, followed by counting with a ticker whenever an egg is spotted. This procedure is laborious and require a good eye skill to distinguish the eggs. In susceptible tomato and potato plants, whiteflies can lay more than a hundred eggs inside a clip cage (⌀ 2 cm). These eggs are sometimes packed in an area and ranges from translucent green to brown depending on the age. Moreover, whitefly eggs that are covered in whitefly honey dew and hidden among trichomes are difficult to detect. Furthermore, there is a limitation to electronically document samples using images from a binocular. Eggsplorer is a workflow especially developed to rapidly evaluate whitefly oviposition. This include the use of a digital microscope that can quickly capture high resolution Z-stacked collages of the whole leaf surface, then importing the images to the Eggsplorer program for egg quantification. A deep learning model, based on YOLOv5 , was trained to detect the eggs automatically in the images and deployed using an executable graphical user interface. As e