Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy
Context Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective The aim of this study was to assess the performance of statistical and machine learning methods to exp...
| Main Authors: | , , , , , |
|---|---|
| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Elsevier
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/131409 |
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