Apple genomes for postharvest fruit quality biomarkers
Author: Dr. Loren Honaas
Published: 2023
Summary: New tools and technologies are needed to help sustain the viability of the tree fruit industry. A key area to innovate is enhancement of supply-chain decision making. By making more informed decisions, losses of fruit quality in the postharvest period could be reduced. Towards this goal, this project developed foundational resources, methods, and datasets that have been used to build prototype biomarker models, or more accurately biosignatures because multiple targets are required for reliable predictions. We focused on two areas that relate to postharvest fruit quality: atharvest apple maturity and fruit textural changes during storage. We found that massive datasets (billions of measurements) can be leveraged with state-of-the-art computational methods to build models that are predictive of these two traits. Importantly validation experiments suggest that the models may work beyond the scope of the experiment, and reliable prototype models consist of a tractable number of gene targets.
