Team
- Faculty: Alan Fern (OSU), Prasad Tadepalli (OSU), Markus Keller (WSU)
- Senior Collaborators: Paola Pesantez-Cabrera (WSU, Data Scientist), Sean Hill (WSU AgWeatherNet)
- Graduate students: Zhengxian Lin (OSU, M.S.), Kin-Ho Lam (OSU, M.S.), Aseem Saxeena (OSU, Ph.D.)
- Undergraduate students: Rohan Ballapragada (OSU, Computer Science)
Objectives
- Develop machine learning models for grape cold hardiness prediction and compare those to existing models.
- Develop and evaluate multi-task learning methods for cold hardiness of different grape cultivars.
- Adapt models developed for grapes to predict sweet cherry cold-hardiness and bud break timing.
- Develop transfer learning methods that can leverage phenology data when cold hardiness training data is not available.
- Porting relevant beta models on AgWeatherNet for grower decision support and testing by a selected set of users.
Hypotheses
- Develop machine learning models for grape cold hardiness prediction and compare those to existing models.
- Develop and evaluate multi-task learning methods for cold hardiness of different grape cultivars.
- Adapt models developed for grapes to predict sweet cherry cold-hardiness and bud break timing.
- Develop transfer learning methods that can leverage phenology data when cold hardiness training data is not available.
- Porting relevant beta models on AgWeatherNet for grower decision support and testing by a selected set of users.
Related Tools
Related Publications
2023
1.
Grape Cold Hardiness Prediction via Multi-Task Learning Conference
Association for the Advancement of Artificial Intelligence (AAAI) 2023, 2023.
2.
Multi-Task Learning for Budbreak Prediction Workshop
2nd AAAI Workshop on AI for Agriculture and Food Systems (AIAFS), arXiv, 2023, (arXiv:2301.01815 [cs]).
3.
Persistent Homology to Study Cold Hardiness of Grape Cultivars Workshop
2nd AAAI Workshop on AI for Agriculture and Food Systems (AIAFS), arXiv, 2023.
2022
4.
Grape Cold Hardiness Prediction via Multi-Task Learning Workshop
Fourth International Workshop on Machine Learning for Cyber-Agricultural Systems (MLCAS2022), 2022.
5.
Extracting patterns in cold hardiness behavior using topological data analysis Workshop
arXiv, 2022.