MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03257nab|a22003977a|4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
66984 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
MX-TxCIM |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20240611230951.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
240111s2024 gw |||p|op||| 00| 0 eng d |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
|---|
| International Standard Serial Number |
0040-5752 |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
|---|
| International Standard Serial Number |
1432-2242 (Online) |
| 024 8# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
https://doi.org/10.1007/s00122-023-04508-6 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
MX-TxCIM |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Fritsche-Neto, R. |
| 9 (RLIN) |
6507 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Improving hybrid rice breeding programs via stochastic simulations : |
| Remainder of title |
number of parents, number of hybrids, tester update, and genomic prediction of hybrid performance |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc. |
Berlin (Germany) : |
| Name of publisher, distributor, etc. |
Springer, |
| Date of publication, distribution, etc. |
2024. |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Peer review |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Open Access |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Key message: Schemes that use genomic prediction outperform others, updating testers increases hybrid genetic gain, and larger population sizes tend to have higher genetic gain and less depletion of genetic variance Abstract: One of the most common methods to improve hybrid performance is reciprocal recurrent selection (RRS). Genomic prediction (GP) can be used to increase genetic gain in RRS by reducing cycle length, but it is also possible to use GP to predict single-cross hybrid performance. The impact of the latter method on genetic gain has yet to be previously reported. Therefore, we compared via stochastic simulations various phenotypic and genomics-assisted RRS breeding schemes which used GP to predict hybrid performance rather than reducing cycle length, which allows minimal changes to traditional breeding schemes. We also compared three breeding sizes scenarios that varied the number of genotypes crossed within heterotic pools, the number of genotypes crossed between heterotic pools, the number of hybrids evaluated, and the number of genomic predicted hybrids. Our results demonstrated that schemes that used genomic prediction of hybrid performance outperformed the others for the average interpopulation hybrid population and the best hybrid performance. Furthermore, updating the testers increased hybrid genetic gain with phenotypic RRS. As expected, the largest breeding size tested had the highest rates of genetic improvement and the lowest decrease in additive genetic variance due to the drift. Therefore, this study demonstrates the usefulness of single-cross prediction, which may be easier to implement than rapid-cycling RRS and cyclical updating of testers. We also reiterate that larger population sizes tend to have higher genetic gain and less depletion of genetic variance. |
| 546 ## - LANGUAGE NOTE |
|---|
| Language note |
Text in English |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
6445 |
| Topical term or geographic name as entry element |
Stochastic models |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| 9 (RLIN) |
1243 |
| Topical term or geographic name as entry element |
Rice |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| 9 (RLIN) |
1151 |
| Topical term or geographic name as entry element |
Hybrids |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
2232 |
| Topical term or geographic name as entry element |
Genetic improvement |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
2091 |
| Topical term or geographic name as entry element |
Genetic gain |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
21704 |
| Topical term or geographic name as entry element |
Breeding programmes |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ali, J. |
| 9 (RLIN) |
32795 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
De Asis, E.J. |
| 9 (RLIN) |
32796 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Allahgholipour, M. |
| 9 (RLIN) |
32797 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Labroo, M. |
| Field link and sequence number |
001712529 |
| 9 (RLIN) |
26662 |
| Miscellaneous information |
Formerly Excellence in Breeding |
| 773 0# - HOST ITEM ENTRY |
|---|
| Title |
Theoretical and Applied Genetics |
| Related parts |
v. 137, no. 1, art. 3 |
| Place, publisher, and date of publication |
Berlin (Germany) : Springer, 2024. |
| International Standard Serial Number |
0040-5752 |
| Record control number |
G444762 |
| 856 4# - ELECTRONIC LOCATION AND ACCESS |
|---|
| Link text |
Open Access through DSpace |
| Uniform Resource Identifier |
https://hdl.handle.net/10883/22884 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
Article |
| Suppress in OPAC |
No |
| Source of classification or shelving scheme |
Dewey Decimal Classification |