1. Applied Wheat Genomics
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Feed the Future Innovation Lab for Applied Wheat Genomics

Publications

2022

2021

Juliana, P., R. P. Singh, J. Poland, S. Shrestha, J. Huerta-Espino, V. Govindan, S. Mondal, L. A. Crespo-Herrera, U. Kumar, A. K. Joshi, T. Payne, P. K. Bhati, V. Tomar, F. Consolacion and J. A. Campos Serna. Elucidating the genetics of grain yield and stress-resilience in bread wheat using a large-scale genome-wide association mapping study with 55,568 lines. Sci Rep 11, 5254 (2021). https://doi.org/10.1038/s41598-021-84308-4

Tomar, V., D. Singh, G. S. Dhillon, R. P. Singh, J. Poland, A. K. Joshi, P. K. Singh, P. K. Bhati, S. Kumar, M. Rahman, B. S. Tiwari and U. Kumar (2021) New QTLs for spot blotch disease resistance in wheat (Triticum aestivum L.) using genome-wide association mapping. Frontiers in Genetics 11: 613217-613217. https://doi.org/10.3389/fgene.2020.613217

Tomar V, Singh D, Dhillon GS, Chung YS, Poland J, Singh RP, Joshi AK, Gautam Y, Tiwari BS and Kumar U (2021) Increased Predictive Accuracy of Multi-Environment Genomic Prediction Model for Yield and Related Traits in Spring Wheat (Triticum aestivum L.). Front. Plant Sci. 12:720123. https://doi.org/10.3389/fpls.2021.720123

Vipin Tomar, Guriqbal Singh Dhillon, Daljit Singh, Ravi Prakash Singh, Jesse Poland, Arun Kumar Joshi1, Uttam Kumar (2021) Evaluations of Genomic Prediction and Identification of New Loci for Resistance to Stripe Rust Disease in Wheat (Triticum aestivum L.). Frontiers Plant Science. 12:710485. (doi:10.3389/fgene.2021.710485)

Tomar Vipin, Dhillon GS, Singh Daljit, Singh RP, Poland J, Joshi AK, Tiwari BS, Kumar Uttam. (2021). Elucidating SNP-based genetic diversity and population structure of advanced breeding lines of bread wheat (Triticum aestivum L.). PeerJ 9:e11593 http://doi.org/10.7717/peerj.11593

Farhad, M., Tripathi, S.B., Singh, R.P., Joshi, A., Bhati, P., Vishwakarma, M.K., Mondal, S., Malik, A.A. and Kumar, U. (2021), Multi-trait selection of bread wheat ideotypes for adaptation to early sown condition. Crop Sci.. Accepted Author Manuscript. https://doi.org/10.1002/csc2.20628

Dreisigacker S, Crossa J, Pérez-Rodríguez P, Montesinos-López OA, Rosyara U, Juliana P, et al. Implementation of Genomic Selection in the CIMMYT Global Wheat Program, Findings from the Past 10 Years. Crop Breed Genet Genom. 2021;3(2): e210005. https://doi.org/10.20900/cbgg20210005

Maria Itria Ibba, Philomin Juliana, Nayelli Hernández-Espinosa, Gabriel Posadas-Romano, Susanne Dreisigacker, Deepmala Sehgal, Leonardo Crespo-Herrera, Ravi Singh, Carlos Guzmán, Genome-wide association analysis for arabinoxylan content in common wheat (T. Aestivum L.) flour. Journal of Cereal Science, Volume 98,2021,103166,ISSN 0733-5210,https://doi.org/10.1016/j.jcs.2021.103166

Crossa J, Fritsche-Neto R, Montesinos-Lopez OA, Costa-Neto G, Dreisigacker S, Montesinos-Lopez A and Bentley AR (2021) The Modern Plant Breeding Triangle: Optimizing the Use of Genomics, Phenomics, and Enviromics Data. Front. Plant Sci. 12:651480. doi: 10.3389/fpls.2021.651480

2020

Gao, L., D.-H. Koo, P. Juliana, T. Rife, D. Singh, C. Lemes da Silva, T. Lux, K. M. Dorn, M. Clinesmith, P. Silva, X. Wang, M. Spannagl, C. Monat, B. Friebe, B. Steuernagel, G. J. Muehlbauer, S. Walkowiak, C. Pozniak, R. Singh, N. Stein, M. Mascher, A. Fritz and J. Poland (2021). The Aegilops ventricosa 2NvS segment in bread wheat: cytology, genomics and breeding. Theoretical and Applied Genetics 134(2): 529-542

Juliana, P., R. P. Singh, H.-J. Braun, J. Huerta-Espino, L. Crespo-Herrera, V. Govindan, S. Mondal, J. Poland and S. Shrestha (2020) Genomic selection for grain yield in the CIMMYT wheat breeding program—status and perspectives. Frontiers in Plant Science 11(1418). DOI: 10.3389/fpls.2020.564183

Sehgal, D., Rosyara, U., Mondal, S., Singh, R., Poland, J. Dreisigacker, S., (2020) Incorporating Genome-Wide Association Mapping Results Into Genomic Prediction Models for Grain Yield and Yield Stability in CIMMYT Spring Bread Wheat, Frontiers in Plant Science, https://doi.org/10.3389/fpls.2020.00197.

Sehgal, D., S. Mondal, L. Crespo-Herrera, G. Velu, P. Juliana, J. Huerta-Espino, S. Shrestha, J. Poland, R. Singh and S. Dreisigacker (2020) Haplotype-Based, Genome-Wide Association Study Reveals Stable Genomic Regions for Grain Yield in CIMMYT Spring Bread Wheat. Frontiers in Genetics 11(1427). DOI: 10.3389/fgene.2020.589490

Reynolds, M., Chapman, S., Crespo-Herrera, L., Molero, G., Mondal, S., NL Pequeno, D., Pinto, F., Pinera-Chavez, F. J., Poland, J., Rivera-Amado,  C., Saint Pierre, C., Sukumaran, S., (2020) Breeder friendly phenotyping, Plant Science,https://doi.org/10.1016/j.plantsci.2019.110396.

Juliana, P., R. P. Singh, H.-J. Braun, J. Huerta-Espino, L. Crespo-Herrera, T. Payne, J. Poland, S. Shrestha, U. Kumar, A. K. Joshi, M. Imtiaz, M. M. Rahman and F. H. Toledo (2020). "Retrospective Quantitative Genetic Analysis and Genomic Prediction of Global Wheat Yields." Frontiers in Plant Science,11(1328).

Krause, M.R., Mondal, S., Crossa, J., Singh, R.P., Pinto, F., Haghighattalab, A., Shrestha, S., Rutkoski, J., Gore, M.A., Sorrells, M.E. and Poland, J. (2020),  Aerial high-throughput phenotyping enables indirect selection for grain yield at the early generation, seed-limited stages in breeding programs. Crop Science, 2020. 60(6): p. 3096-3114.

Juliana, P., X. He, M. R. Kabir, K. K. Roy, M. B. Anwar, F. Marza, J. Poland, S. Shrestha, R. P. Singh and P. K. Singh (2020). "Genome-wide association mapping for wheat blast resistance in CIMMYT’s international screening nurseries evaluated in Bolivia and Bangladesh." Scientific Report,s10(1): 15972.

Ibba, M. I., J. Crossa, O. A. Montesinos-López, A. Montesinos-López, P. Juliana, C. Guzman, E. Delorean, S. Dreisigacker and J. Poland (2020). "Genome-based prediction of multiple wheat quality traits in multiple years." The Plant Genome, e20034.

de los Campos, G., P. Pérez-Rodríguez, M. Bogard, D. Gouache, J. Crossa (2020). A data-driven simulation platform to predict cultivars’ performances under uncertain weather conditions.” Nature, Communication https://doi.org/10.1038/s41467-020-18480-y.

Pérez-Rodríguez, P., O. A. Montesinos-López, A. Montesinos-López, J. Crossa (2020). “Bayesian regularized quantile regression: A robust alternative for genome-based prediction of skewed data.”  The Crop Journal, 1-10 pp. doi.org/10.1016/j.cj.2020.04.009.

Paulino Pérez-Rodríguez, Samuel Flores-Galarza, Humberto Vaquera-Huerta, David Hebert del Valle-Paniagua, Osval A. Montesinos-López and José Crossa (2020). “Genome-based prediction of Bayesian linear and non-linear regression models for ordinal data.” The Plant Genome, 1-13 pp. DOI: 10.1002/tpg2.20021.

Martini, J. W. R., J. Crossa, F. H. Toledo, J.  Cuevas (2020). “On Hadamard and Kronecker products in covariance structures for genotype × environment interaction.” The Plant Genome, 1-12 pp. doi.org/10.1002/tpg2.20033.

Gerard, G. S., L. A. Crespo-Herrera, J. Crossa, S. Mondal, G. Velu, P. Julian, J. Huerta-Espino, M. Vargas, M. S. Rhandawa, S. Bhavani, H. Braun, R. P. Singh (2020). “Grain yield genetic gains and changes in physiological related traits for CIMMYT’s High Rainfall Wheat Screening Nursery tested across international environments.” Field Crops Research, 249 (2020) 107742. doi.org/10.1016/j.fcr.2020.107742.

Martini, J. W.R. , F. H. Toledo, J. Crossa (2020). “On the approximation of interaction effect models by Hadamard powers of the additive genomic relationship.” Theoretical Population Biology. 132 (2020) 16–23. doi.org/10.1016/j.tpb.2020.01.004.

Cerón-Rojas, J. J., J. Crossa (2020).“Combined Multistage Linear Genomic Selection Indices To Predict the Net Genetic Merit in Plant Breeding.” G3: Genes|Genomes|Genetics. Volume 10 (2087-2101). Doi.org/10.1534/g3.120.401171

Fleitas, M. C., S. Mondal, G. S. Gerard, N. Hernandez-Espinosa, R. P. Singh, J. Crossa, C. Guzman (2020). “Identification of CIMMYT spring bread wheat germplasm maintaining superior grain yield and quality under heat-stress.” Journal of Cereal Science, 93 (2020) 102981. doi.org/10.1016/j.jcs.2020.102981.

Lopez-Cruz, M., E. Olson, G. Rovere, J. Crossa, S. Dreisigacker, S. Mondal, R. Singh, G. de los Campos (2020). “Regularized selection indices for breeding value prediction using hyper-spectral image data.” Nature/Scientific Reports, doi.org/10.1038/s41598-020-65011-2 1.

Cerón‑Rojas, J. J., J. Crossa (2020). “Expectation and variance of the estimator of the maximized selection response of linear selection indices with normal distribution.” Theoretical and Applied Genetics, 1-16. doi.org/10.1007/s00122-020-03629-6.

Shimizu, K. K., D. Copetti, M. Okada, T. Wicker, T. Tameshige, M. Hatakeyama, R. Shimizu-Inatsugi, C. Aquino, K. Nishimura, F. Kobayashi, K. Murata, T. Kuo, E. Delorean, J. Poland, G. Haberer, M. Spannagl, K. F. X. Mayer, J. Gutierrez-Gonzalez, G. J. Muehlbauer, C. Monat, A. Himmelbach, S. Padmarasu, M. Mascher, S. Walkowiak, T. Nakazaki, T. Ban, K. Kawaura, H. Tsuji, C. Pozniak, N. Stein, J. Sese, S. Nasuda and H. Handa (2020) De novo genome assembly of the Japanese wheat cultivar Norin 61 highlights functional variation in flowering time and fusarium resistance genes in East Asian genotypes. Plant and Cell Physiology. DOI: 10.1093/pcp/pcaa152

Walkowiak, S., L. Gao, C. Monat, G. Haberer, M. T. Kassa, J. Brinton, R. H. Ramirez-Gonzalez, M. C. Kolodziej, E. Delorean, D. Thambugala, V. Klymiuk, B. Byrns, H. Gundlach, V. Bandi, J. N. Siri, K. Nilsen, C. Aquino, A. Himmelbach, D. Copetti, T. Ban, L. Venturini, M. Bevan, B. Clavijo, D.-H. Koo, J. Ens, K. Wiebe, A. N’Diaye, A. K. Fritz, C. Gutwin, A. Fiebig, C. Fosker, B. X. Fu, G. G. Accinelli, K. A. Gardner, N. Fradgley, J. Gutierrez-Gonzalez, G. Halstead-Nussloch, M. Hatakeyama, C. S. Koh, J. Deek, A. C. Costamagna, P. Fobert, D. Heavens, H. Kanamori, K. Kawaura, F. Kobayashi, K. Krasileva, T. Kuo, N. McKenzie, K. Murata, Y. Nabeka, T. Paape, S. Padmarasu, L. Percival-Alwyn, S. Kagale, U. Scholz, J. Sese, P. Juliana, R. Singh, R. Shimizu-Inatsugi, D. Swarbreck, J. Cockram, H. Budak, T. Tameshige, T. Tanaka, H. Tsuji, J. Wright, J. Wu, B. Steuernagel, I. Small, S. Cloutier, G. Keeble-Gagnère, G. Muehlbauer, J. Tibbets, S. Nasuda, J. Melonek, P. J. Hucl, A. G. Sharpe, M. Clark, E. Legg, A. Bharti, P. Langridge, A. Hall, C. Uauy, M. Mascher, S. G. Krattinger, H. Handa, K. K. Shimizu, A. Distelfeld, K. Chalmers, B. Keller, K. F. X. Mayer, J. Poland, N. Stein, C. A. McCartney, M. Spannagl, T. Wicker and C. J. Pozniak (2020) Multiple wheat genomes reveal global variation in modern breeding. Nature 588(7837): 277-283. DOI: 10.1038/s41586-020-2961-x

Wang, X., P. Silva, N. M. Bello, D. Singh, B. Evers, S. Mondal, F. P. Espinosa, R. P. Singh and J. Poland (2020) Improved accuracy of high-throughput phenotyping from unmanned aerial systems by extracting traits directly from orthorectified images. Frontiers in Plant Science 11(1616). DOI: 10.3389/fpls.2020.587093

2019

Juliana, P., Montesinos-López, O. A., 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, R. P. (2019). Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat. Theoretical and Applied Genetics, 132(1), 177–194. https://doi.org/10.1007/s00122-018-3206-3

Howard R., D. Gianola, O. Montesinos-López, P. Juliana, R. Singh, J. Poland, S. Shrestha,  P. Pérez-Rodríguez, J. Crossa and D. Jarquín. 2019. Joint Use of Genome, Pedigree, and Their Interaction with Environment for Predicting the Performance of Wheat Lines in New Environments. G3: Genes|Genomes|Genetics doi: 10.1534/g3.119.400508

Krause, M. R., L. González-Pérez, J. Crossa, P. Pérez-Rodríguez, O. Montesinos-López, R. P. Singh, S. Dreisigacker, J. Poland, J. Rutkoski, M. Sorrells, M. A. Gore and S. Mondal (2019)  Hyperspectral reflectance-derived relationship matrices for genomic prediction of grain yield in wheat.  G3: Genes|Genomes|Genetics 9(4): 1231. DOI: 10.1534/g3.118.200856

Sehgal, D., Mondal, S., Guzman, C., Barrios, G. G., Franco, C., Singh, R. P., & Dreisigacker, S. (2019). Validation of candidate gene-based markers and identification of novel loci for thousand-grain weight in spring bread wheat. Frontiers in Plant Science, 10, 1189.

Singh, D., X. Wang, U. Kumar, L. Gao, M. Noor, M. Imtiaz, R. P. Singh and J. Poland (2019)  High-throughput phenotyping enabled genetic dissection of crop lodging in wheat.  Frontiers in Plant Science 10(394). DOI: 10.3389/fpls.2019.00394

Shrestha, S., Crossa, J., Crespo-Herrera, L., Toledo, F.H., Govindan, V., Kumar, U. et al., 2019. Improving grain yield in, stress resilience and quality of bread wheat. G3: Genes, Genomes, Genetics, 9(4), 1231-1247. https://doi.org/10.1534/g3.118.200856 using large-scale genomics. Nature genetics,  51, pages 1530–1539.

Gongora-Canul, C., Salgado, J., Singh, D., Cruz, A., Cotrozzi, L., Couture, J. J., Poland, J. & Cruz, C. (2019). Temporal Dynamics of wheat blast epidemics and agreement between remotely sensed data measurements and visual estimations of wheat spike blast (WSB) under field conditions. Phytopathology.  https://doi.org/10.1094/PHYTO-08-19-0297-R

Juliana, P., Poland, J., Huerta-Espino, J., Shrestha, S., Crossa, J., Crespo-Herrera, L., ... & Singh, R. (2019). Improving grain yield, stress resilience and quality of bread wheat using large-scale genomics. Nature Genetics, 1-10. https://www.nature.com/articles/s41588-019-0496-6

2018

Crain, J., Mondal, S., Rutkoski, J., Singh, R. P., & Poland, J. (2018). Combining High-Throughput Phenotyping and Genomic Information to Increase Prediction and Selection Accuracy in Wheat BreedingThe Plant Genome11(1), 0. https://doi.org/10.3835/plantgenome2017.05.0043

Battenfield, S. D., Sheridan, J. L., Silva, L. D. C. E., Miclaus, K. J., Dreisigacker, S., Wolfinger, R. D., Peña, R. J., Singh, R. P., Jackson, E. W., Fritz, A. K., Guzmán, C., & Poland, J. A. (2018). Breeding-assisted genomics: Applying meta-GWAS for milling and baking quality in CIMMYT wheat breeding program. PLOS ONE, 13(11), e0204757. https://doi.org/10.1371/journal.pone.0204757

Juliana, P., Singh, R.P., Singh, P.K., Poland, J.A., Bergstrom, G.C., Huerta-Espino, J., Bhavani, S., Crossa, J. & Sorrells, M.E. (2018) Genome-wide association mapping for resistance to leaf rust, stripe rust and tan spot in wheat reveals potential candidate genes. Theoretical and Applied Genetics, 1-18.  

Juliana, P., Singh, R. P., Poland, J., Mondal, S., Crossa, J., Montesinos-López, O. A., Dreisigacker, S., Pérez-Rodríguez, P., Huerta-Espino, J., Crespo-Herrera, L., & Govindan, V. (2018). Prospects and Challenges of Applied Genomic Selection—A New Paradigm in Breeding for Grain Yield in Bread Wheat. The Plant Genome, 11(3). Retrieved from https://dl.sciencesocieties.org/publications/tpg/pdfs/0/0/180017

Juliana, P., Montesinos-López, O. A., 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, R. P. (2018). Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat. Theoretical and Applied Genetics, 1–18. https://doi.org/10.1007/s00122-018-3206-3

Wang, X., Singh, D., Marla, S., Morris, G., & Poland, J. (2018). Field-based high-throughput phenotyping of plant height in sorghum using different sensing technologies. Plant Methods, 14(1), 53. https://doi.org/10.1186/s13007-018-0324-5

2017

Haghighattalab, A., J. Crain, S. Mondal, J. Rutkoski, R. P. Singh and J. Poland (2017)  Application of geographically weighted regression to improve grain yield prediction from unmanned aerial system imagery.  Crop Science. DOI: 10.2135/cropsci2016.12.1016

Crossa, J., Pérez-Rodríguez, P., Cuevas, J., Montesinos-López, O., Jarquín, D., de los Campos, G., Burgueño, J., Camacho-González, J.M., Pérez-Elizalde, S., Beyene, Y., Dreisigacker, S., Singh, R., Zhang, X., Gowda, M., Roorkiwal, M., Rutkoski, J., & Varshney, R.K. (2017). Genomic Selection in Plant Breeding: Methods, Models, and Perspectives. Trends in Plant Science. Published online. http://dx.doi.org/10.1016/j.tplants.2017.08.011

Lado, B., S. Battenfield, C. Guzmán, M. Quincke, R. P. Singh, S. Dreisigacker, R. J. Peña, A. Fritz, P. Silva, J. Poland and L. Gutiérrez (2017) Strategies for selecting crosses using genomic prediction in two wheat breeding programs. The Plant Genome 10(2). DOI: 10.3835/plantgenome2016.12.0128

Montesinos‑López, A., Montesinos‑López, O.A., Cuevas, J., Mata‑López, W.A., Burgueño, J., Mondal, S., Huerta, J., Singh, R., Autrique, E., González‑Pérez, L., & Crossa, J. 2017. Genomic Bayesian functional regression models with interactions for predicting wheat grain yield using hyper‑spectral image data. Plant Methods 13:62 DOI 10.1186/s13007-017-0212-4

Montesinos‑López, O.A, Montesinos‑López, A., Cross, J., Montesinos‑López, J.C., Moto-Sanchez, D., Estrada-Gonzalez, F., Gilberg, J., Singh, R., Mondal, S., & Juliana, P.2017. Prediction of multiple-trait and multiple-environment genomic data using recommender systems. G3,doi: 10.1534/g3.117.300309

Dunckel, S., Crossa, J., Wu, S., Bonnett, D., & Poland, J. (2017). Genomic Selection for Increased Yield in Synthetic-Derived Wheat. Crop Science, 57(2). https://doi.org/10.2135/cropsci2016.04.0209

Juliana, P., Singh, R. P., Singh, P. K., Crossa, J., Huerta-Espino, J., Lan, C., Bhavani, S., Rutkoski, J. E., Poland, J. A., Bergstrom, G. C., & Sorrells, M. E. (2017). Genomic and pedigree-based prediction for leaf, stem, and stripe rust resistance in wheat. Theoretical and Applied Genetics, 1–16. https://doi.org/10.1007/s00122-017-2897-1

Juliana, P., Singh, R. P., Singh, P. K., Crossa, J., Rutkoski, J. E., Poland, J. A., Bergstrom, G. C., & Sorrells, M. E. (2017). Comparison of Models and Whole-Genome Profiling Approaches for Genomic-Enabled Prediction of Septoria Tritici Blotch, Stagonospora Nodorum Blotch, and Tan Spot Resistance in Wheat. The Plant Genome, 10(2), 0. https://doi.org/10.3835/plantgenome2016.08.0082

Pérez-Rodríguez, P., Crossa, J., Rutkoski, J., Poland, J., Singh, R., Legarra, A., Autrique, E., Campos, G. de los, Burgueño, J., & Dreisigacker, S. (2017). Single-Step Genomic and Pedigree Genotype × Environment Interaction Models for Predicting Wheat Lines in International Environments. The Plant Genome, 0(0), 0. https://doi.org/10.3835/plantgenome2016.09.0089

Sehgal, D., Autrique, E., Singh, R., Ellis, M., Singh, S., Dreisigacker, S. (2017). Identification of genomic regions for grain yield and yield stability and their epistatic interactions, 2017, Scientific Reports, 7, 41578. doi:10.1038/srep41578

Tanger, P., Klassen, S., Mojica, J. P., Lovell, J. T., Moyers, B. T., Baraoidan, M., Naredo, M. E. B., McNally, K. L., Poland, J., Bush, D. R., Leung, H., Leach, J. E., & McKay, J. K. (2017). Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice. Scientific Reports, 7, 42839. https://doi.org/10.1038/srep42839

2016

Guzman, C., R. J. Peña, R. Singh, E. Autrique, S. Dreisigacker, J. Crossa, J. Rutkoski, J. Poland, and S. Battenfield (2016). Wheat quality improvement at CIMMYT and the use of genomic selection on it. Applied and Translational Genomics. DOI: 10.1016/j.atg.2016.10.004

Tack, J., A. Barkley, T. Rife, J. Poland, and L. Nalley (2016). Quantifying variety-specific heat resistance and the potential for adaptation to climate change. Global Change Biology, 22(8), 2904–2912. https://doi.org/10.1111/gcb.13163  

Rutkoski, J., J. Poland, S. Mondal, E. Autrique, L. G. Párez, J. Crossa, M. Reynolds and R. Singh (2016)  Canopy temperature and vegetation indices from high-throughput phenotyping improve accuracy of pedigree and genomic selection for grain yield in wheat.  G3: Genes| Genomes| Genetics. DOI: 10.1534/g3.116.032888

Poland, J. and J. Rutkoski (2016). Advances and challenges in genomic selection for disease resistance. Annual Review of Phytopathology 54(1): DOI: doi:10.1146/annurev-phyto-080615-100056

Battenfield, S. D., C. Guzmán, R. C. Gaynor, R. Singh, R. Peña, S. Dreisigacker, A. Fritz and J. Poland (2016). Genomic selection for processing and end-use quality traits in the CIMMYT spring bread wheat breeding program.  The Plant Genome. DOI: 10.3835/plantgenome2016.01.0005

Crain, J., Y. Wei, J. Barker, S. Thompson, P. Alderman, M. Reynolds, N. Zhang and J. Poland (2016). Development and deployment of a portable field phenotyping platform. Crop Science 56(3): 965-975. DOI: 10.2135/cropsci2015.05.0290

Montesinos-López, O. A., A. Montesinos-López, J. Crossa, F. Toledo, O. Pérez-Hernández, K. M. Eskridge, J. Rutkoski. A genomic Bayesian multi-trait and multi-environment model. G3:Genes | Genomes | Genetics. 6:2725-2744 doi:10.1534/g3.116.032359

Haghighattalab, A., L. González Pérez, S. Mondal, D. Singh, D. Schinstock, J. Rutkoski, I. Ortiz-Monasterio, R. P. Singh, D. Goodin and J. Poland (2016). Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries.  Plant Methods 12(1): 1-15. DOI: 10.1186/s13007-016-0134-6

Wang, X., Thorp, K. R., White, J. W., French, A. N., & Poland, J. A. (2016). Approaches for Geospatial Processing of Field-Based High-Throughput Plant Phenomics Data from Ground Vehicle Platforms. Transactions of the ASABE, 59(5), 1053–1067. https://doi.org/10.13031/trans.59.11502

Sun, J., Rutkoski, J., Poland, J., Crossa,  J., Jannink, J., Sorrells, M. Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield. The Plant Genome. doi: 10.3835/plantgenome2016.11.0111

Pérez-Rodríguez, P., Crossa, J., Rutkoski, J., Poland, J., Singh, R., Legarra, A., Autrique, E., Campos, G. de los, Burgueño, J., & Dreisigacker, S. (2017). Single-Step Genomic and Pedigree Genotype × Environment Interaction Models for Predicting Wheat Lines in International Environments. The Plant Genome, 0(0), 0. https://doi.org/10.3835/plantgenome2016.09.0089

Barker, J., Zhang, N., Sharon, J., Steeves, R., Wang, X., Wei, Y., & Poland, J. (2016). Development of a field-based high-throughput mobile phenotyping platform. Computers and Electronics in Agriculture, 122, 74–85. https://doi.org/10.1016/j.compag.2016.01.017

2015

Juliana P., J. E. Rutkoski, J. Poland, R. P. Singh, S. Murugasamy, S. Natesan, H. Barbier, M. E. Sorrells. Genome-Wide Association Mapping for Leaf Tip Necrosis and Pseudo-black Chaff in Relation to Durable Rust Resistance in Wheat. The Plant Genome. Vol. 8, No. 2. doi:10.3835/plantgenome2015.01.0002.

Crain J. L., Y. Wei, J. Barker, S. M. Thompson, P. D. Alderman, M. Reynolds, N. Zhang, J. Poland. Development and deployment of a portable field phenotyping platform. Crop Science. Vol. 56 No. 3, p. 965-975. doi:10.2135/cropsci2015.05.0290.

Rutkoski J. , Poland J., Mondal, S. Autrique E., Gonzalez Perez L., Crossa J., Reynolds M., Singh R., Predictor traits from high-throughput phenotyping improve accuracy of pedigree and genomic selection for yield in wheat. In preparation.

Dunckel, S., M. Rouse, R Bowden, and J. Poland (2015)  Genetic mapping of race-specific stem rust resistance in the synthetic hexaploid W7984 x Opata M85 mapping population. Crop Sci. 55:1–9.
DOI: 10.2135/cropsci2014.11.0755

Poland, J. (2015)  Breeding assisted genomics. Current Opinion in Plant Biology: 24,119–124

Rife, T., S. Wu, R. Bowden and J. Poland (2015)  Spiked GBS: a unified, open platform for single marker genotyping and whole-genome profiling.  BMC Genomics 16(1): 248

Rutkoski, J., R. P. Singh, J. Huerta-Espino, S. Bhavani, J. Poland, J. L. Jannink and M. E. Sorrells (2015)  Genetic gain from phenotypic and genomic selection for quantitative resistance to stem rust of wheat.  The Plant Genome 8(2). DOI: 10.3835/plantgenome2014.10.0074

Rutkoski, J., R. P. Singh, J. Huerta-Espino, S. Bhavani, J. Poland, J. L. Jannink and M. E. Sorrells (2015)  Efficient use of historical data for genomic selection: A case study of stem rust resistance in wheat.  The Plant Genome 8(1). DOI: 10.3835/plantgenome2014.09.0046

M. Lopez‐Cruz, J. Crossa, D. Bonnett, S. Dreisigacker, J. Poland, J‐L Jannink, R. P. Singh, E. Autrique and G. de los Campos. (2015)  Increased prediction accuracy in wheat breeding trials using a marker × environment interaction genomic selection model. G3: Genes|Genomes|Genetics doi:10.1534/g3.114.016097