Using an incomplete block design to allocate lines to environments improves sparse genome‐based prediction in plant breeding
Abstract Genomic selection (GS) is a predictive methodology that trains statistical machine‐learning models with a reference population that is used to perform genome‐enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. How...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-03-01
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| Series: | The Plant Genome |
| Online Access: | https://doi.org/10.1002/tpg2.20194 |