A Comparison of Three Automated Root-Knot Nematode Egg Counting Approaches Using Machine Learning, Image Analysis, and a Hybrid Model
Meloidogyne spp. (root-knot nematodes [RKNs]) are a major threat to a wide range of agricultural crops worldwide. Breeding crops for RKN resistance is an effective management strategy, yet assaying large numbers of breeding lines requires laborious bioassays that are time-consuming and require exper...
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Bibliographische Detailangaben
| Veröffentlicht in: | Plant disease. - 1997. - 108(2024), 9 vom: 23. Sept., Seite 2625-2629
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| 1. Verfasser: |
Fraher, Simon P
(VerfasserIn) |
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| Weitere Verfasser: |
Watson, Mark,
Nguyen, Hoang,
Moore, Savannah,
Lewis, Ramsey S,
Kudenov, Michael,
Yencho, G Craig,
Gorny, Adrienne M |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | Plant disease
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| Schlagworte: | Journal Article
Comparative Study
automated counting
convolutional neural network
meloidogyne
root-knot nematode |
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