Smart and accurate: A new tool to identify stressed soybean seeds based on multispectral images and machine learning models
Extreme environmental conditions have been recurrent during the last few years and have impacted crop seed quality worldwide, mainly but not limited to, soybeans (Glycine max (L) Merrill). To overcome this, seed companies often demand innovative tools to address seed quality factors. Machine learnin...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-12-01
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| Series: | Smart Agricultural Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375525002758 |
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