230 related articles for article (PubMed ID: 27826661)
21. Exploring and exploiting the genetic variation of Fusarium head blight resistance for genomic-assisted breeding in the elite durum wheat gene pool.
Steiner B; Michel S; Maccaferri M; Lemmens M; Tuberosa R; Buerstmayr H
Theor Appl Genet; 2019 Apr; 132(4):969-988. PubMed ID: 30506523
[TBL] [Abstract][Full Text] [Related]
22. Genomic Selection for Processing and End-Use Quality Traits in the CIMMYT Spring Bread Wheat Breeding Program.
Battenfield SD; Guzmán C; Gaynor RC; Singh RP; Peña RJ; Dreisigacker S; Fritz AK; Poland JA
Plant Genome; 2016 Jul; 9(2):. PubMed ID: 27898810
[TBL] [Abstract][Full Text] [Related]
23. Multi-Trait Genomic Prediction of Yield-Related Traits in US Soft Wheat under Variable Water Regimes.
Guo J; Khan J; Pradhan S; Shahi D; Khan N; Avci M; Mcbreen J; Harrison S; Brown-Guedira G; Murphy JP; Johnson J; Mergoum M; Esten Mason R; Ibrahim AMH; Sutton R; Griffey C; Babar MA
Genes (Basel); 2020 Oct; 11(11):. PubMed ID: 33126620
[TBL] [Abstract][Full Text] [Related]
24. Genomic Prediction and Genome-Wide Association Studies of Flour Yield and Alveograph Quality Traits Using Advanced Winter Wheat Breeding Material.
Kristensen PS; Jensen J; Andersen JR; Guzmán C; Orabi J; Jahoor A
Genes (Basel); 2019 Aug; 10(9):. PubMed ID: 31480460
[TBL] [Abstract][Full Text] [Related]
25. Phenomic selection in wheat breeding: prediction of the genotype-by-environment interaction in multi-environment breeding trials.
Robert P; Goudemand E; Auzanneau J; Oury FX; Rolland B; Heumez E; Bouchet S; Caillebotte A; Mary-Huard T; Le Gouis J; Rincent R
Theor Appl Genet; 2022 Oct; 135(10):3337-3356. PubMed ID: 35939074
[TBL] [Abstract][Full Text] [Related]
26. Phenomic selection in wheat breeding: identification and optimisation of factors influencing prediction accuracy and comparison to genomic selection.
Robert P; Auzanneau J; Goudemand E; Oury FX; Rolland B; Heumez E; Bouchet S; Le Gouis J; Rincent R
Theor Appl Genet; 2022 Mar; 135(3):895-914. PubMed ID: 34988629
[TBL] [Abstract][Full Text] [Related]
27. Genome-Wide Association and Prediction of Grain and Semolina Quality Traits in Durum Wheat Breeding Populations.
Fiedler JD; Salsman E; Liu Y; Michalak de Jiménez M; Hegstad JB; Chen B; Manthey FA; Chao S; Xu S; Elias EM; Li X
Plant Genome; 2017 Nov; 10(3):. PubMed ID: 29293807
[TBL] [Abstract][Full Text] [Related]
28. Training population selection and use of fixed effects to optimize genomic predictions in a historical USA winter wheat panel.
Sarinelli JM; Murphy JP; Tyagi P; Holland JB; Johnson JW; Mergoum M; Mason RE; Babar A; Harrison S; Sutton R; Griffey CA; Brown-Guedira G
Theor Appl Genet; 2019 Apr; 132(4):1247-1261. PubMed ID: 30680419
[TBL] [Abstract][Full Text] [Related]
29. Single- and multi-trait genomic prediction and genome-wide association analysis of grain yield and micronutrient-related traits in ICARDA wheat under drought environment.
Tadesse W; Gataa ZE; Rachdad FE; Baouchi AE; Kehel Z; Alemu A
Mol Genet Genomics; 2023 Nov; 298(6):1515-1526. PubMed ID: 37851098
[TBL] [Abstract][Full Text] [Related]
30. Genomic selection in wheat: optimum allocation of test resources and comparison of breeding strategies for line and hybrid breeding.
Longin CF; Mi X; Würschum T
Theor Appl Genet; 2015 Jul; 128(7):1297-306. PubMed ID: 25877519
[TBL] [Abstract][Full Text] [Related]
31. Genomic Prediction and Indirect Selection for Grain Yield in US Pacific Northwest Winter Wheat Using Spectral Reflectance Indices from High-Throughput Phenotyping.
Lozada DN; Godoy JV; Ward BP; Carter AH
Int J Mol Sci; 2019 Dec; 21(1):. PubMed ID: 31881728
[TBL] [Abstract][Full Text] [Related]
32. Genomic selection for agronomic traits in a winter wheat breeding program.
Ficht A; Konkin DJ; Cram D; Sidebottom C; Tan Y; Pozniak C; Rajcan I
Theor Appl Genet; 2023 Mar; 136(3):38. PubMed ID: 36897431
[TBL] [Abstract][Full Text] [Related]
33. Estimation of physiological genomic estimated breeding values (PGEBV) combining full hyperspectral and marker data across environments for grain yield under combined heat and drought stress in tropical maize (Zea mays L.).
Trachsel S; Dhliwayo T; Gonzalez Perez L; Mendoza Lugo JA; Trachsel M
PLoS One; 2019; 14(3):e0212200. PubMed ID: 30893307
[TBL] [Abstract][Full Text] [Related]
34. Accelerating wheat breeding for end-use quality with multi-trait genomic predictions incorporating near infrared and nuclear magnetic resonance-derived phenotypes.
Hayes BJ; Panozzo J; Walker CK; Choy AL; Kant S; Wong D; Tibbits J; Daetwyler HD; Rochfort S; Hayden MJ; Spangenberg GC
Theor Appl Genet; 2017 Dec; 130(12):2505-2519. PubMed ID: 28840266
[TBL] [Abstract][Full Text] [Related]
35. Combining High-Throughput Phenotyping and Genomic Information to Increase Prediction and Selection Accuracy in Wheat Breeding.
Crain J; Mondal S; Rutkoski J; Singh RP; Poland J
Plant Genome; 2018 Mar; 11(1):. PubMed ID: 29505641
[TBL] [Abstract][Full Text] [Related]
36. Multiple-trait- and selection indices-genomic predictions for grain yield and protein content in rye for feeding purposes.
Schulthess AW; Wang Y; Miedaner T; Wilde P; Reif JC; Zhao Y
Theor Appl Genet; 2016 Feb; 129(2):273-87. PubMed ID: 26561306
[TBL] [Abstract][Full Text] [Related]
37. Multi-trait genomic-enabled prediction enhances accuracy in multi-year wheat breeding trials.
Montesinos-López A; Runcie DE; Ibba MI; Pérez-Rodríguez P; Montesinos-López OA; Crespo LA; Bentley AR; Crossa J
G3 (Bethesda); 2021 Sep; 11(10):. PubMed ID: 34568924
[TBL] [Abstract][Full Text] [Related]
38. Image-based phenomic prediction can provide valuable decision support in wheat breeding.
Roth L; Fossati D; Krähenbühl P; Walter A; Hund A
Theor Appl Genet; 2023 Jun; 136(7):162. PubMed ID: 37368140
[TBL] [Abstract][Full Text] [Related]
39. Maintenance of UK bread baking quality: Trends in wheat quality traits over 50 years of breeding and potential for future application of genomic-assisted selection.
Fradgley NS; Bentley AR; Gardner KA; Swarbreck SM; Kerton M
Plant Genome; 2023 Dec; 16(4):e20326. PubMed ID: 37057385
[TBL] [Abstract][Full Text] [Related]
40. Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat.
Juliana P; Montesinos-López OA; Crossa J; Mondal S; González Pérez L; Poland J; Huerta-Espino J; Crespo-Herrera L; Govindan V; Dreisigacker S; Shrestha S; Pérez-Rodríguez P; Pinto Espinosa F; Singh RP
Theor Appl Genet; 2019 Jan; 132(1):177-194. PubMed ID: 30341493
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
