Data for: Unlocking the Power of AI for Fruit Phenotyping: A Genetic Validation Study in Arabidopsis

This dataset contains annotated images of mature inflorescences, collected from experiments conducted on the Multiparent Advanced Generation Inter-Cross (MAGIC) population. The images were utilised to develop and validate a deep learning-based pipeline for Arabidopsis fruit trait extraction.

- The images and annotations have been separated into a training and a test set. 

- The pretrained Cascade Mask-RCNN model (in PyTorch) for instance segmentation of Arabidopsis siliques is also provided in arabidopsis.pth file.  

The instructions for installing and testing the pipeline, along with the extracted phenotype data and MAGIC genomic data for QTL analysis, can be found in https://github.com/kieranatkins/silique-detector/ . 

For the verification of the pipeline using QTL analysis, the full dataset collection (in total of over 7000 images) has been utilised, and the raw images and metadata are available at the following links.:

AT023: 10.5281/zenodo.13853394

AT024: 10.5281/zenodo.13856248

AT025: 10.5281/zenodo.13856317