Location: Potato, Pulse and Small Grains Quality Research
Project Number: 3060-21430-009-032-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 5, 2025
End Date: Aug 31, 2026
Objective:
The objective of this project is to reduce subjective variability in potato storage disease measurements by utilizing a photovision echnique and machine learning algorithms. These algorithms will be applied to quantify potato storage defects and will provide plant breeders, growers and industry stakeholders with easily comparable precise quantitative measures of differences in potato clone storage quality.
Approach:
The field study will be conducted using seed tubers obtained commercially and from the NDSU Potato Breeding Program. After harvest, ubers will be mechanically bruised and infected with Globisporangium ultimum, the causal organism of Pythium Leak. Potato tubers will be sampled and photographed at different stages of disease development and these images will be used to build machine learning algorithms which will objectively determine extent of disease development.