Optimizing maize germination forecasts with random forest and data fusion techniques
Traditional methods for detecting seed germination rates often involve lengthy experiments that result in damaged seeds. This study selected the Zheng Dan-958 maize variety to predict germination rates using multi-source information fusion and a random forest (RF) algorithm. Images of the seeds and...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2024-11-01
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| Series: | PeerJ Computer Science |
| Subjects: | |
| Online Access: | https://peerj.com/articles/cs-2468.pdf |
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