phenoSEED
phenoSEED performs high-throughput, individual-seed phenotyping from BELT (Bioimaging Enabled Lentil Traits) top- and side-view optical images to extract quantitative seed traits such as color, size, shape, and seed-coat patterning for lentil (Lens culinaris L.) and other small-seed species.
Key Features:
- Integration with BELT: Integrated with the BELT (Bioimaging Enabled Lentil Traits) portable imaging system for small-seed optical analysis.
- Individual-seed imaging automation: Automates individualized imaging of seeds as they pass through an imaging chamber.
- Image views captured: Captures both top and side optical views of each seed.
- Python-based analysis script: Implements a Python-based analysis script for image processing and trait extraction.
- Color calibration: Performs color calibration to ensure accurate color data acquisition from images.
- Trait extraction (color, size, shape): Extracts quantitative traits related to seed color, size, and shape.
- Seed-coat patterning extraction: Includes functionality to extract lentil seed-coat patterning.
- High-throughput data acquisition: Increases the rate of phenotypic data collection compared to manual methods.
- Operator-bias reduction: Automates measurements to reduce operator bias and capture qualitative traits traditionally assessed visually.
- Test case: Primary test case reported for lentil (Lens culinaris L.) and applicable to various small-seed types.
Scientific Applications:
- Lentil phenotyping: Individual-seed phenotyping of lentil (Lens culinaris L.) including color, size, shape, and coat patterning.
- Plant breeding and genetics: Provides quantitative phenotypic data to support selection and cultivar development in plant breeding and genetics research.
- High-throughput trait screening: Enables high-throughput screening of seed traits for downstream statistical and genetic analyses.
Methodology:
A Python-based analysis script performs color calibration on BELT-acquired top and side images and extracts quantitative seed traits (color, size, shape) and lentil seed-coat patterning.
Topics
Details
- Programming Languages:
- Python
- Added:
- 1/14/2020
- Last Updated:
- 1/9/2021
Operations
Publications
Halcro K, McNabb K, Lockinger A, Socquet-Juglard D, Bett KE, Noble SD. The BELT and phenoSEED platforms: shape and colour phenotyping of seed samples. Unknown Journal. 2019. doi:10.1101/825695.
Halcro K, McNabb K, Lockinger A, Socquet-Juglard D, Bett KE, Noble SD. The BELT and phenoSEED platforms: shape and colour phenotyping of seed samples. Unknown Journal. 2019. doi:10.1101/825695.