Why is seed imaging revolutionizing seed analysis?
See how Janine Maruschak of Canadian Food Inspection Agency (CFIA) is automating seed analysis with VideometerLab Autofeeder solution
Seed quality assessment based on spectral imaging is currently transforming the seed industry. Traditional methods based on physical, physiological, biochemical, and molecular evaluation are effective, but often time-consuming, labor intensive, destructive, and requiring highly trained seed experts.
Spectral imaging is integrated with machine learning and artificial intelligence in the VideometerLab instrument providing a fast, non-destructive, and versatile seed evaluation system that can evolve over time and effectively handle variation from growth season to growth season, location, varietal and climate changes through a cloud database of virtualized seeds (aka digital twins). While seed imaging should not be the only tool to capture the characteristics of seed phonotypes, it will be the obvious backbone of a seed phenotype database due the fast, non-destructive, and versatile measurement.
What is seed phenotyping?
The seed phenotype consists of all observable characteristics (e.g. length, weight, shape, color) of a seed resulting from the seed genotype expressed through the lifetime environment of the seed. Distinct variants (e.g. long, red caryopsis, mold resistant) of phenotypic characteristics are called traits.
How to do seed phenotyping?
Spectral imaging seed analysis protocol
Read the SpectraSeed presentations: