| 000 | 02511nab|a22003617a|4500 | ||
|---|---|---|---|
| 001 | 66092 | ||
| 003 | MX-TxCIM | ||
| 005 | 20240919021233.0 | ||
| 008 | 20231s2023||||mx |||p|op||||00||0|eng|d | ||
| 022 | _a1940-3372 (Online) | ||
| 024 | 8 | _ahttps://doi.org/10.1002/tpg2.20305 | |
| 040 | _aMX-TxCIM | ||
| 041 | _aeng | ||
| 100 | 1 |
_aMontesinos-Lopez, O.A. _8I1706800 _92700 _gGenetic Resources Program |
|
| 245 | 1 | 0 | _aSparse multi-trait genomic prediction under balanced incomplete block design |
| 260 |
_bWiley, _c2023. _aUSA : |
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| 500 | _aPeer review | ||
| 500 | _aOpen Access | ||
| 520 | _aSparse testing is essential to increase the efficiency of the genomic selection methodology, as the same efficiency (in this case prediction power) can be obtained while using less genotypes evaluated in the fields. For this reason, it is important to evaluate the existing methods for performing the allocation of lines to environments. With this goal, four methods (M1–M4) to allocate lines to environments were evaluated under the context of a multi-trait genomic prediction problem: M1 denotes the allocation of a fraction (subset) of lines in all locations, M2 denotes the allocation of a fraction of lines with some shared lines in locations but not arranged based on the balanced incomplete block design (BIBD) principle, M3 denotes the random allocation of a subset of lines to locations, and M4 denotes the allocation of a subset of lines to locations using the BIBD principle. The evaluation was done using seven real multi-environment data sets common in plant breeding programs. We found that the best method was M4 and the worst was M1, while no important differences were found between M3 and M4. We concluded that M4 and M3 are efficient in the context of sparse testing for multi-trait prediction. | ||
| 546 | _aText in English | ||
| 591 | _aMontesinos-Lopez, O.A. : No CIMMYT Affiliation | ||
| 650 | 7 |
_2AGROVOC _91132 _aGenomics |
|
| 650 | 7 |
_aPlant breeding _gAGROVOC _2 _91203 |
|
| 650 | 7 |
_2AGROVOC _910737 _aMarker-assisted selection |
|
| 650 | 7 |
_2AGROVOC _921704 _aBreeding programmes |
|
| 700 | 1 |
_aMosqueda-Gonzalez, B.A. _919441 |
|
| 700 | 1 |
_aSalinas-Ruiz, J. _94951 |
|
| 700 | 1 |
_aMontesinos-Lopez, A. _92702 |
|
| 700 | 1 |
_aCrossa, J. _gGenetic Resources Program _8CCJL01 _959 |
|
| 773 | 0 |
_tPlant Genome _dUSA : Wiley, 2023. _gv. 16, no. 2, e20305 _wu94757 _x1940-3372 |
|
| 856 | 4 |
_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/22536 |
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| 942 |
_cJA _n0 _2ddc |
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| 999 |
_c66092 _d66084 |
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