Multi‐trait/environment sparse genomic prediction using the SFSI R‐package
Abstract Sparse selection indices (SSIs) can be used to predict the genetic merit of selection candidates using high‐dimensional phenotypes (e.g., crop imaging) measured on each of the candidates of selection. Unlike traditional selection indices, SSIs can perform variable selection, thus enabling b...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-06-01
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| Series: | The Plant Genome |
| Online Access: | https://doi.org/10.1002/tpg2.70050 |
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