Deployment and analysis of instance segmentation algorithm for in-field yield estimation of sweet potatoes

Shape estimation of sweetpotato (SP) storage roots is inherently challenging due to their varied size and shape characteristics. Even measuring “simple” metrics, such as length and diameter, requires significant time investments either directly in-field or afterward using automated graders. We present the results of a model that can perform grading and provide yield estimates directly in the field faster than manual measurements. Detectron2, a library consisting of deep-learning object detection algorithms, was used to implement Mask R-CNN, an instance segmentation model.  This model was deployed for in-field grade estimation of SP roots and evaluated against an optical sorter.  Roots from various clones imaged with a cellphone during trials between 2019 and 2020, were used in the model’s training and validation to fine-tune a model to detect SP roots.  Our results showed that the model (Average Precision = 74.1) could distinguish individual roots in environmental conditi..., , # Data from: Deployment and analysis of instance segmentation algorithm for in-field yield estimation of sweet potatoes

Dataset DOI: [10.5061/dryad.wh70rxx0z](10.5061/dryad.wh70rxx0z)

## Description of the data and file structure

This archive contains data presented in our paper, including the masks and imagery used to train our Mask R-CNN sweetpotato instance segmentation model, and data used to validate it (plot-level dataset, one-to-one dataset, and the commercial optical sorter baseline dataset).

### Files and variables

#### File: Dryad_SweetAPPS_Data.zip

**Description:** Contains the contents of the one-to-one dataset, plot-level dataset, and the sorter baseline data. Decompressing this file will create the following directories:

1. 3D_set: Monte-Carlo simulation data. Contains a Google Colab file, “process_data.ipynb”, that was used to generate the figures and analyses used for the free-space, plane, and roller data. Monte-Carlo datasets that were used are contained in the ...,