The response of maize, sorghum, and soybean yield to growing-phase climate revealed with machine learning
Accurate representation of crop responses to climate is critically important to understand impacts of climate change and variability in food systems. We use Random Forest (RF), a diagnostic machine learning tool, to explore the dependence of yield on climate and technology for maize, sorghum and soy...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2020-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/ab7b22 |