This dataset focuses on black aphid detection. It was created in a greenhouse cucumber cultivation as part of the H2020 PestNu project (No. 101037128). Images were captured over 44 days at UTH facilities in Volos, Greece, using mobile phone cameras positioned 30-40 cm from five pheromone-based glue-paper traps. One trap replacement occurred due to insect accumulation, with images collected mainly on weekdays, totaling 220 images. Expert agronomists annotated 13,357 black aphids using Roboflow, averaging 60.71 annotations per image. The dataset was split into training and validation subsets with an 80–20% ratio, leading to 175 images for training and 45 for validation. The dataset is organized into two main folders: “0_captured_dataset" contains the original 220 .jpg images. "1_annotated_dataset" includes the images and the annotated data, split into separate subfolders for training and validation. The Black Aphids count in each subset can be seen in the following table: Set Images Black Aphids Instances Training 175 10873 Validation 45 2484 Total 220 13357 Acknowledgments: This work is supported by the Green Deal PestNu project, funded by European Union’s Horizon 2020 research and innovation programme under the grant agreement No. 101037128, and the E-SPFdigit project, funded by European Union’s Horizon Europe research and innovation programme under the grant agreement No. 101157922.