Detection of insect-damaged sunflower seeds using near-infrared hyperspectral imaging and machine learning
Insect damage can significantly affect seed germination rates and overall seed quality, resulting in notable economic losses. Detecting insect-damaged seeds is vital for upholding food safety standards and satisfying consumer expectations in confectionery sunflower markets. To tackle this issue, thi...
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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/S2772375525003430 |
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