Exp4_kernza_seeds Computer Vision Project

Here are a few use cases for this project:

1. Agricultural Quality Control: Use the Kernza_seeds model to quickly and accurately assess the quality of harvested Kernza seeds by classifying them into dehulled, hulled, chaff, florets, BrokenSeed, and ergot categories. This information can help farmers optimize their harvest and ensure high-quality seeds for planting or consumption.

2. Grain Processing and Packaging: Implement the Kernza_seeds model in grain processing facilities to automate the sorting, cleaning, and packaging of Kernza seeds. By accurately identifying different classes, the model can improve efficiency and reduce manual labor involved in processing Kernza seeds.

3. Seed Research and Breeding: Utilize the Kernza_seeds model to study seed morphology and characteristics to support seed breeding programs. By identifying various classes of seeds and their components, researchers can better understand the factors affecting seed development, germination, and overall seed quality.

4. Food Safety and Contamination Detection: Apply the Kernza_seeds model to detect and identify any contaminated seeds (such as ergot-infected ones) during food production and processing. This can help prevent the spread of harmful substances and ensure the safety of food products made from Kernza seeds.

5. Environmental Impact Assessment: Use the Kernza_seeds model to monitor the impact of agricultural practices on wild Kernza populations by identifying the presence of hulled, dehulled, and BrokenSeed classes among naturally occurring seeds. This information can help in devising sustainable farming practices and seed dispersal strategies to protect and conserve the natural environment.