2023
DOI: 10.1038/s41598-023-34375-6
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Convolutional neural networks in the qualitative improvement of sweet potato roots

Abstract: The objective was to verify whether convolutional neural networks can help sweet potato phenotyping for qualitative traits. We evaluated 16 families of sweet potato half-sibs in a randomized block design with four replications. We obtained the images at the plant level and used the ExpImage package of the R software to reduce the resolution and individualize one root per image. We grouped them according to their classifications regarding shape, peel color, and damage caused by insects. 600 roots of each class … Show more

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Cited by 3 publications
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