Factors influencing genomic prediction accuracies of tropical maize resistance to fall armyworm and weevils
| cg.authorship.types | CGIAR and advanced research institute | en |
| cg.contributor.affiliation | Makerere University | en |
| cg.contributor.affiliation | Bioversity International and the International Center for Tropical Agriculture | en |
| cg.contributor.affiliation | National Crops Resources Research Institute, Uganda | en |
| cg.contributor.affiliation | University of Cape Coast | en |
| cg.contributor.affiliation | University of Abomey-Calavi | en |
| cg.contributor.donor | Carnegie Corporation of New York | en |
| cg.contributor.donor | Integrated Genotyping Service and Support | en |
| cg.contributor.donor | United States Agency for International Development | en |
| cg.creator.identifier | Lewis Machida: 0000-0002-0012-3997 | en |
| cg.identifier.doi | https://doi.org/10.3390/plants10010029 | en |
| cg.isijournal | ISI Journal | en |
| cg.issn | 2223-7747 | en |
| cg.issue | 1 | en |
| cg.journal | Plants | en |
| cg.reviewStatus | Peer Review | en |
| cg.subject.alliancebiovciat | AGRICULTURE | en |
| cg.volume | 10 | en |
| dc.contributor.author | Badji, Arfang | en |
| dc.contributor.author | Machida, Lewis | en |
| dc.contributor.author | Kwemoi, Daniel Bomet | en |
| dc.contributor.author | Kumi, Frank | en |
| dc.contributor.author | Okii, Dennis | en |
| dc.contributor.author | Mwila, Natasha | en |
| dc.contributor.author | Agbahoungba, Symphorien | en |
| dc.contributor.author | Ibanda, Angele | en |
| dc.contributor.author | Bararyenya, Astere | en |
| dc.contributor.author | Nghituwamhata, Selma Ndapewa | en |
| dc.contributor.author | Odong, Thomas L. | en |
| dc.contributor.author | Wasswa, Peter | en |
| dc.contributor.author | Otim, Michael | en |
| dc.contributor.author | Ochwo-Ssemakula, Mildred | en |
| dc.contributor.author | Talwana, Herbert | en |
| dc.contributor.author | Asea, Godfrey | en |
| dc.contributor.author | Kyamanywa, Samuel | en |
| dc.contributor.author | Rubaihayo, Patrick | en |
| dc.date.accessioned | 2021-01-14T13:29:07Z | en |
| dc.date.available | 2021-01-14T13:29:07Z | en |
| dc.identifier.uri | https://hdl.handle.net/10568/110863 | |
| dc.title | Factors influencing genomic prediction accuracies of tropical maize resistance to fall armyworm and weevils | en |
| dcterms.abstract | Genomic selection (GS) can accelerate variety improvement when training set (TS) size and its relationship with the breeding set (BS) are optimized for prediction accuracies (PAs) of genomic prediction (GP) models. Sixteen GP algorithms were run on phenotypic best linear unbiased predictors (BLUPs) and estimators (BLUEs) of resistance to both fall armyworm (FAW) and maize weevil (MW) in a tropical maize panel. For MW resistance, 37% of the panel was the TS, and the BS was the remainder, whilst for FAW, random-based training sets (RBTS) and pedigree-based training sets (PBTSs) were designed. PAs achieved with BLUPs varied from 0.66 to 0.82 for MW-resistance traits, and for FAW resistance, 0.694 to 0.714 for RBTS of 37%, and 0.843 to 0.844 for RBTS of 85%, and these were at least two-fold those from BLUEs. For PBTS, FAW resistance PAs were generally higher than those for RBTS, except for one dataset. GP models generally showed similar PAs across individual traits whilst the TS designation was determinant, since a positive correlation (R = 0.92***) between TS size and PAs was observed for RBTS, and for the PBTS, it was negative (R = 0.44**). This study pioneered the use of GS for maize resistance to insect pests in sub-Saharan Africa. | en |
| dcterms.accessRights | Open Access | |
| dcterms.audience | Scientists | en |
| dcterms.available | 2020-12-24 | en |
| dcterms.bibliographicCitation | Badji, A.; Machida, L.; Kwemoi, D.B.; Kumi, F.; Okii, D.; Mwila, N.; Agbahoungba, S.; Ibanda, A.; Bararyenya, A.; Nghituwamhata, S.N.; Odong, T.; Wasswa, P.; Otim, M.; Ochwo-Ssemakula, M.; Talwana, H.; Asea, G.; Kyamanywa, S.; Rubaihayo, P. (2020) Factors influencing genomic prediction accuracies of tropical maize resistance to fall armyworm and weevils. Plants 10(29) 2021 22 p. ISSN: 2223-7747 | en |
| dcterms.extent | 22 p. | en |
| dcterms.issued | 2020-12 | en |
| dcterms.language | en | |
| dcterms.license | CC-BY-4.0 | |
| dcterms.publisher | MDPI | en |
| dcterms.subject | marker-assisted selection | en |
| dcterms.subject | maize | en |
| dcterms.subject | defence mechanisms | en |
| dcterms.subject | selección asistida por marcadores | en |
| dcterms.subject | maíz | en |
| dcterms.subject | mecanismos de defensa | en |
| dcterms.type | Journal Article |