Explainable Machine Learning to Map the Impact of Weather and Soil on Wheat Yield and Revenue Across the Eastern Australian Grain Belt
Understanding the causes of spatiotemporal variation in crop yields across large areas is important in closing yield gaps and producing more food for the growing global population. While there has been much focus on using data-driven models to predict crop yield, there is also an opportunity to use...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
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| Series: | Agriculture |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-0472/14/12/2318 |