Using Weather Patterns and AI to Understand Crop Yield Variability and Prediction
Lead Research Organisation:
CRANFIELD UNIVERSITY
Department Name: School of Water, Energy and Environment
Abstract
The main hypothesis of this PhD project is that weather types can be used to explain spatial and temporal climate-related crop variability and can provide longer crop yield prediction lead times than for example using specific indicators such as precipitation or temperature. The study will be applied to Europe and North America given the availability of the crop yield data, with a focus on the UK.
People |
ORCID iD |
| Christopher Knight (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| NE/S007350/1 | 01/10/2019 | 30/09/2027 | |||
| 2753490 | Studentship | NE/S007350/1 | 01/10/2021 | 31/03/2025 | Christopher Knight |