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Bullock, D., Mangeni, A., Wiesner-Hanks, T., DeChant, C., Stewart, E.L., Kaczmar, N., Nelson, R.J., Gore, M.A., and Lipson, H. 2019. Automated weed detection in aerial imagery with context. arXiv:1910.00652v3


Feng, H., Acosta-Gamboa, L., Kruse, L.H., Fereira, A.R.N., Shakir, S., Xu, H., Sunter, G., Gore, M.A., Moghe, G.D., and Jander, G. 2020. An improved Nicotiana benthamiana strain for aphid and whitefly research. Preprint at bioRxiv

Diepenbrock, C.H., Ilut, D.C., Magallanes-Lundback, M., Kandianis, C.B.,Lipka, A.E., Bradbury, P.J., Holland, J.B., Hamilton, J.P., Wooldridge, E., Vaillancourt, B., Góngora-Castillo, E., Wallace, J.G., Cepela, J., Mateos-Hernandez, M., Owens, B.F., Tiede, T., Buckler, E.S., Rocheford, T., Buell, C.R., Gore, M.A., and DellaPenna, D. 2020. Eleven biosynthetic genes explain the majority of natural variation for carotenoid levels in maize grain. Preprint at bioRxiv

Jain, P., Liu, W., Zhu, S., Melkonian, J., Pauli, D., Riha, S.J., Gore, M.A., and Stroock, A.D. 2020. A minimally disruptive method for measuring water potential in-planta using hydrogel nanoreporters. Preprint at bioRxiv

Kim, M.-S., Lozano, R., Kim, J.H., Bae, D.N., Kim, S.-T., Park, J.-H., Choi, M.S., Kim, J., Ok, H.C., Park, S.-K., Gore, M.A., Moon, J.-K., and Jeong, S.-C. 2020. Purging of deleterious mutations during domestication in the predominant selfing crop soybean. PrePrint at bioRxiv

Matschi, S., Vasquez, M.F., Bourgault, R., Steinbach, P., Chamness, J., Kaczmar, N., Gore, M.A., Molina, I., and Smith, L.G. 2020. Structure-function analysis of the maize bulliform cell cuticle and its role in dehydration and leaf rolling. PrePrint at bioRxiv

Lozano, R., Gazave, E., dos Santos, J.P.R., Stetter, M., Valluru, R., Bandillo, N., Fernandes, S.B., Brown, P.J., Shakoor, N., Mockler, T.C., Ross-Ibarra, J., Buckler, E.S., and Gore, M.A. 2019. Comparative evolutionary analysis and prediction of deleterious mutation patterns between sorghum and maize. PrePrint at bioRxiv 10.1101/777623

Buckler, E.S., Ilut, D.C., Wang, X., Kretzschmar, T., Gore, M.A., and Mitchell, S.E. 2016. rAmpSeq: Using repetitive sequences for robust genotyping. PrePrint at bioRxiv


Matschi, S., Vasquez, M.F., Bourgault, R., Steinbach, P., Chamness, J., Kaczmar, N., Gore, M.A., Molina, I., and Smith, L.G. 2020. Structure-function analysis of the maize bulliform cell cuticle and its role in dehydration and leaf rolling. Plant Direct doi: 10.1002/pld3.282

Krause, M.R., Crossman, S., DuMond, T., Lott, R., Swede, J., Arliss, S., Robbins, R., Ochs, D., and Gore, M.A. 2020. Random forest regression for optimizing variable planting rates for corn and soybean using topographical and soil data. Agronomy Journal

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 enabling indirect selection for grain yield at the early-generation seed-limited stages in breeding programs. Crop Science

Brzozowski, L.J., Gore, M.A., Agrawal, A.A., and Mazourek, M. 2020. Divergence of defensive cucurbitacins in independent Cucurbita pepo domestication events leads to differences in specialist herbivore preference. Plant, Cell & Environment

Qiao, P. Bourgault, R. Mohammadi, M., Gore, M.A., Molina, I., and Scanlon, M.J. 2020. A maize LIPID TRANSFER PROTEIN may bridge the gap between PHYTOCHROME-mediated light signaling and cuticle biosynthesis. Plant Signaling & Behavior 15:e1790824

Anche, M.T., Kaczmar, N.S., Morales, N., Clohessy, J.W., Ilut, D.C., Gore, M.A., and Robbins, K.R. 2020. Temporal covariance structure of multi-spectral phenotypes and their predictive ability for end-of-season traits in maize. Theoretical and Applied Genetics 133:2853-2868.

Wang, D.R., Venturas, M.D., Mackay, D.S., Hunsaker, D.J., Thorp, K.R., Gore, M.A., and Pauli, D. 2020. Use of hydraulic traits for modeling genotype‐specific acclimation in cotton under drought. New Phytologist 228:898-909.

Vogel, G., Gore, M.A., and Smart, C.D. 2020. Genome-wide association study in New York Phytophthora capsici isolates reveals loci involved in mating type and mefenoxam sensitivity. Phytopathology

Qiao, P. Bourgault, R. Mohammadi, M., Matschi, S., Philippe, G., Smith, L.G., Gore, M.A., Molina, I., and Scanlon, M.J. 2020. Transcriptomic network analyses shed light on the regulation of cuticle development in maize leaves. Proceedings of the National Academy of Sciences 117:12464-12471.

Morales, N., Kaczmar, N.S., Santantonio, N., Gore, M.A., Mueller, L.A., and Robbins, K.R. 2020. ImageBreed: Open-access plant breeding web–database for image-based phenotyping. The Plant Phenome Journal 3:e20004.

Baseggio, M., Murray, M., Magallanes-Lundback, M., Kaczmar, N., Chamness, J., Buckler, E.S., Smith, M.E., DellaPenna, D., Tracy, W.F., and Gore, M.A. 2020. Natural variation for carotenoids in fresh kernels is controlled by uncommon variants in sweet corn. The Plant Genome e20008.

Hu, H., Gutierrez-Gonzalez, J.J., Liu, X., Yeats, T.H., Garvin, D.F., Hoekenga, O.A., Sorrells, M.E., Gore, M.A., and Jannink, J.-L. 2020. Heritable temporal gene expression patterns correlate with metabolomic seed content in developing hexaploid oat seed. Plant Biotechnology Journal 18:1211-1222.

Jensen, S., Charles, J.R., Muleta, K., Bradbury, P., Casstevens, T., Deshpande, S.P., Gore, M.A., Gupta, R., Ilut, D.C., Johnson, L., Lozano, R., Miller, Z., Ramu, P., Rathore, A., Romay, M.C., Upadhyaya, H.D., Varshney, R., Morris, G.P., Pressoir, G., Buckler, E., and Ramstein, G. 2020. A sorghum practical haplotype graph facilitates genome-wide imputation and cost-effective genomic prediction. The Plant Genome 13:e20009

Lin, M., Matschi, S., Vasquez, M., Chamness, J., Kaczmar, N., Baseggio, M., Miller, M., Stewart, E.L., Qiao, P., Scanlon, M.J., Molina, I., Smith, L.G. and Gore, M.A. 2020. Genome-wide association study for maize leaf cuticular conductance identifies candidate genes involved in the regulation of cuticle development. G3: Genes| Genomes| Genetics

Iragaba,P., Kawuki, R. S., Bauchet, G., Ramu, P., Tufan, H.A., Earle, E.D, Gore, M.A., and Wolfe, M. 2020. Genomic characterization of Ugandan smallholder farmer‐preferred cassava (Manihot esculenta Crantz) varieties. Crop Science 60:1450-1461.

Falcon, C.M., Kaeppler, S.M., Spalding, E.P., Miller, N.D., Haase, N., AlKhalifah, N., Bohn, M., Buckler, E.S., Campbell, D.A. Ciampitti, I., Coffey, L., Edwards, J., Ert, D., Flint-Garcia, S., Gore, M.A., Graham, C., Hirsch, C.N., Holland, J.B., Jarquín, D., Knoll, J., Lauter, N., Lawrence-Dill, C.J., Lee, E.C., Lorenz, A., Lynch, J.P., Murray, S.C., Nelson, R., Romay, C.M., Rocheford, T., Schnable, P.S., Scully, B., Smith, M., Springer, N., Tuinstra, M., Walton, R., Weldekidan, T., Wisser, R.J., Xu, W., and de Leon, N. 2020. Relative utility of agronomic, phenological, and morphological traits for assessing genotype-by-environment interaction in maize inbreds. Crop Science 60:62-81.

Grover, C. E., Yoo, M.-J., Lin, M., Murphy, M.D., Harker, D.B., Byers, R.L., Lipka, A.E., Hu, G., Yuan, D., Conover, J.L., Udall, J.A., Paterson, A.H., Gore, M.A., and Wendel, J.F. 2020. Genetic analysis of the transition from wild to domesticated cotton (G. hirsutum L.). G3: Genes| Genomes| Genetics 10: 731-754.

dos Santos, J.P.R., Fernandes, S.B., McCoy, S., Lozano, R., Brown, P.J., Leakey, A.D.B., Buckler, E.S., Garcia, A.A.F., and Gore, M.A. 2020. Novel Bayesian networks for genomic prediction of developmental traits in biomass sorghum. G3: Genes| Genomes| Genetics 10:769-781.

Gazave, E., Tassone, E.E., Baseggio, M., Cryder, M., Byriel, K., Oblath, E., Lueschow, S., Poss, D., Hardy, C., Wingerson, M., Davis, J.B., Abdel-Haleem, H., Grant, D.M., Hatfield, J.L., Isbell, T.A., Vigil, M.F, Dyer, J.M., Jenks, M.A., Brown, J., Gore, M.A., and Pauli, D. 2020. Genome-wide association study identifies acyl-lipid metabolism candidate genes involved in the genetic control of natural variation for seed fatty acid traits in Brassica napus L. Industrial Crops and Products 145:112080.

McFarland, B.A., AlKhalifah, N., Bohn, M., Bubert, J., Buckler, E.S., Ciampitti, I., Edwards, J., Ertl, D., Gage, J.L., Falcon, C.M., Flint-Garcia, S., Gore, M.A., Graham, C., Hirsch, C.N., Holland, J.B., Hood, E., Hooker, D., Jarquin, D., Kaeppler, S.M., Knoll, J., Kruger, G., Lauter, N., Lee, E.C., Lima, D.C., Lorenz, A., Lynch, J.P., McKay, J., Miller, N.D, Moose, S.P., Murray, S.C., Nelson, R., Poudyal, C., Rocheford, T., Rodriguez, O., Romay, M.C., Schnable, J.C., Schnable, P.S., Scully, B., Sekhon, R., Silverstein, K., Singh, M., Smith, M., Spalding, E.P., Springer, N., Thelen, K., Thomison, P., Tuinstra, M., Wallace, J., Walls, R., Wills, D., Wisser, R.J., Xu, W., Yeh, C.-T., and de Leon, N. 2020. Maize genomes to fields (G2F): 2014–2017 field seasons: genotype, phenotype, climatic, soil, and inbred ear image datasets. BMC Research Notes 13:71.


Wiesner-Hanks, T., Wu, H., Stewart, E., DeChant, C., Kaczmar, N., Lipson, H., Gore, M.A., and Nelson, R.J. 2019. Millimeter-level plant disease detection from aerial photographs via deep learning and crowdsourced data. Frontiers in Plant Science 10:1550 doi: 10.3389/fpls.2019.01550

Gage, J.L., Richards, E., Lepak, N., Kaczmar, N., Soman, C., Chowdhary, G., Gore, M.A., and Buckler, E.S. 2019. In-field whole plant maize architecture characterized by subcanopy rovers and latent space phenotyping. The Plant Phenome Journal 2:190011 doi: 10.2135/tppj2019.07.0011

Qiao, P., Lin, M., Vasquez, M., Matschi, S., Chamness, J., Baseggio, M., Smith, L.G., Sabuncu, M.R., Gore, M.A., and Scanlon, M.J. 2019. Machine learning enables high-throughput phenotyping for analyses of the genetic architecture of bulliform cell patterning in maize. G3: Genes| Genomes| Genetics 9:4235-4243.

Wu, H., Wiesner-Hanks, T., Stewart, E.L., DeChant, C., Kaczmar, N., Gore, M.A., Nelson, R.J., and Lipson, H. 2019. Autonomous detection of plant disease symptoms directly from aerial imagery. The Plant Phenome Journal 2:190006 doi: 10.2135/tppj2019.03.0006

Stewart, E.L., Wiesner-Hanks, T., Kaczmar, N., DeChant, C., Wu, H., Lipson, H., Nelson, R.J., and Gore, M.A. 2019. Quantitative phenotyping of northern blight in UAV images using deep learning. Remote Sensing 11:2209.

Wu, D., Hought, J., Baseggio, M., Hart, J.P., Gore, M.A., and Ilut, D.C. 2019. Genomic characterization of the Native Seeds/SEARCH common bean collection and its seed coat patterns. Genetic Resources and Crop Evolution 7:1469-1482.

Khoury, C.K., Kisel, Y., Kantar, M., Barber, E., Ricciardi, V., Klirs, C., Kucera, L., Mehrabi, Z., Johnson, N., Klabin, S., Valiño, A., Nowakowski, K., Bartomeus, I., Ramankutty, N., Miller, A., Schipanski, M., Gore, M.A., and Novy, A. 2019. Science–graphic art partnerships to increase research impact. Nature Communications Biology 2:295.

Kremling, K.A.G., Diepenbrock, C.H., Gore, M.A., Buckler, E.S., and Bandillo, N.B. 2019. Transcriptome-wide association supplements genome-wide association in Zea mays. G3: Genes| Genomes| Genetics 9:3023-3033.

Carlson, M.O., Montilla-Bascón, G., Hoekenga, O.A., Tinker, N.A., Poland, J., Baseggio, M., Sorrells, M., Jannink, J.-L., Gore, M.A., and Yeats, T.H. 2019. Multivariate genome-wide association analyses reveal the genetic basis of seed fatty acid composition in oat (Avena sativa L.)G3: Genes| Genomes| Genetics 9:2963-2975.

Mbah, E. U., Nwankwo, B.C., Njoku, D.N., and Gore, M.A. 2019. Genotypic evaluation of twenty-eight high- and low-cyanide cassava in low-land tropics, southeast Nigeria. Heliyon 5: e01855.

Owens, B.F., Mathew, D., Diepenbrock, C., Tiede, T., Wu, D., Mateos-Hernandez, M., Gore, M.A., and Rocheford, T. 2019. Genome-wide association study and pathway-level analysis of kernel color in maize. G3: Genes| Genomes| Genetics 9:1945-1955.

Iragaba, P., Nuwamanya, E., Wembabazi, E., Baguma, Y., Dufour, D., Earle, E. D., Kerr, R.B., Tufan, H.A., Gore, M.A., and Kawuki, R.S. 2019. Estimates for heritability and consumer-validation of a penetrometer method for phenotyping softness of cooked cassava roots. African Crop Science Journal 27:147-163.

Krause, M.R., González-Pérez, L., Crossa, J., Pérez-Rodríguez, P., Montesinos-López, O., Singh, R.P., Dreisigacker, S., Poland, J., Rutkoski, J., Sorrells, M., Gore, M.A., and Mondal, S. 2019. Hyperspectral reflectance-derived relationship matrices for genomic prediction of grain yield in wheatG3: Genes| Genomes| Genetics

Glahn, R., Tako, E., and Gore, M.A. 2019. The germ fraction inhibits iron bioavailability of maize: Identification of an approach to enhance maize nutritional quality via processing and breeding. Nutrients 11:833

Gleason, S. M., Cooper, M., Wiggans, D.R., Bliss, C.A., Romay, M.C., Gore, M.A., Mickelbart, M.V., Topp, C.N., Zhang, H., DeJonge, K.C., and Comas, L.H. 2019. Stomatal conductance, xylem water transport, and root traits underpin improved performance under drought and well-watered conditions across a diverse panel of maize inbred lines. Field Crops Research 234:119-128.

Valluru, R., Gazave, E.E., Fernandes, S.B., Ferguson, J.N., Lozano, R., Hirannaiah, P., Zuo, T., Brown, P.J., Leakey, A.D.B., Gore, M.A., Buckler, E.S., and Bandillo, N. 2019. Deleterious mutation burden and its association with complex traits in sorghum (Sorghum bicolor)Genetics

Baseggio, M., Murray, M., Magallanes-Lundback, M., Kaczmar, N., Chamness, J., Buckler, E. S., Smith, M.E., DellaPenna, D., Tracy, W.F. and Gore, M.A. 2019. Genome-wide association and genomic prediction models of tocochromanols in fresh sweet corn kernels. The Plant Genome 12:1-17. doi:10.3835/plantgenome2018.06.0038


Clohessy, J.W., Pauli, D., Kreher, K.M., Buckler V, E.S., Armstrong, P.R., Wu, T., Hoekenga, O.A., Jannink, J.-L., Sorrells, M.E., and Gore, M.A. 2018. A low-cost automated system for high-throughput phenotyping of single oat seeds. The Plant Phenome Journal 1:180005. doi: 10.2135/tppj2018.07.0005

Wiesner-Hanks, T., Stewart, E.L., Kaczmar, N., DeChant, C., Wu, H., Nelson, R.J., Lipson, H., and Gore, M.A. 2018. Image set for deep learning: field images of maize annotated with disease symptomsBMC Research Notes 11:440. doi:10.1186/s13104-018-3548-6

AlKhalifah, N., Campbell, D.A., Falcon, C.M., Gardiner, J.M., Miller, N.D., Romay, M.C., Walls, R., Walton, R., Yeh, C.-T., Bohn, M., Bubert, J., Buckler, E.S., Ciampitti, I., Flint-Garcia, S., Gore, M.A., Graham, C., Hirsch, C., Holland, J.B., Hooker, D., Kaeppler, S., Knoll, J., Lauter, N., Lee, E.C., Lorenz, A., Lynch, J.P., Moose, S.P., Murray, S.C., Nelson, R., Rocheford, T., Rodriguez, O., Schnable, J.C., Scully, B., Smith, M., Springer, N., Thomison, P., Tuinstra, M., Wisser, R. J., Xu, W., Ertl, D., Schnable, P.S., De Leon, N., Spalding, E.P., Edwards, J., and Lawrence-Dill, C.J. 2018. Maize genomes to fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets. BMC Research Notes 11:452. doi:10.1186/s13104-018-3508-1

Pauli, D., Ziegler, G. Ren, M., Jenks, M.A., Hunsaker, D.J., Zhang, M., Baxter, I. and Gore, M.A. 2018. Multivariate analysis of the cotton seed ionome reveals a shared genetic architecture. G3: Genes| Genomes| Genetics 8:1147-1160. doi:

Zhu, X., Sun, L., Kuppu, S., Hu, R., Mishra, N., Smith, J., Esmaeili, N., Herath, M., Gore, M.A., Payton, P., Shen, G., and Zhang, H. 2018. The yield difference between wild-type cotton and IPT-transgenic cotton depends on when water-deficit stress is applied. Scientific Reports 8:2538. doi:10.1038/s41598-018-20944-7

Byrne, P.F., Volk, G.M., Gardner, C., Gore, M.A., Simon, P.W., and Smith, S. 2018. Sustaining the future of plant breeding: The Critical role of the USDA-ARS National Plant Germplasm System. Crop Science 58:451-468. doi:10.2135/cropsci2017.05.0303


Diepenbrock, C.H., Kandianis, C.B., Lipka, A.E., Magallanes-Lundback, M., Vaillancourt, B., Góngora-Castillo, E., Wallace, J.G., Cepela, J., Mesberg, A., Bradbury, P.J., Ilut, D.C., Mateos-Hernandez, M., Hamilton, J., Owens, B. F., Tiede, T., Buckler, E.S., Rocheford, T., Buell, C.R., Gore, M.A., and DellaPenna, D. 2017. Novel loci underlie natural variation of vitamin E levels in maize grain. The Plant Cell 29:2374-2392.

Pauli, D., White, J.W., Andrade-Sanchez, P., Conley, M., Heun, J., Thorp, K.R., French, A.N., Hunsaker, D.J., Carmo-Silva, E.A., Wang, G., and Gore, M.A. 2017. Investigation of the influence of leaf thickness on canopy reflectance and physiological traits in upland and Pima cotton populations. Frontiers in Plant Science 8:1405. doi:10.3389/fpls.2017.01405

DeChant, C., Wiesner-Hanks, T., Chen, S., Stewart, E., Yosinski, J., Gore, M.A., Nelson, R., Lipson, H. 2017. Automated identification of northern leaf blight-infected maize plants from field imagery using deep learning. Phytopathology 107:1426-1432. doi:10.1094/PHYTO-11-16-0417-R

Ilut, D.C., Sanchez, P.L., Coffelt, T. A., Dyer, J.M., Jenks, M.A., and Gore, M.A. 2017. A century of guayule: Comprehensive genetic characterization of the US national guayule (Parthenium argentatum A. Gray) germplasm collection. Industrial Crops and Products 109:300-309. doi:10.1016/j.indcrop.2017.08.029

Ariga, H., Katori, T., Tsuchimatsu, T., Hirase, T., Tajima, Y., Parker, J.E., Alcázar, R., Koornneef, M., Hoekenga, O., Lipka, A.E., Gore, M.A., Sakakibara, H., Kojima, M., Kobayashi, Y., Iuchi, S., Kobayashi, M., Shinozaki, K., Sakata, Y., Hayashi, T., Saijo, Y., and Taji, T. 2017. NLR locus-mediated trade-off between abiotic and biotic stress adaptation in Arabidopsis. Nature Plants 3:17072. doi:10.1038/nplants.2017.72

Holdsworth, W.L., Gazave, E., Cheng, P., Myers, J.R., Gore, M.A., Coyne, C.J., McGee, R.J., and Mazourek, M. 2017. A community resource for exploring and utilizing genetic diversity in the USDA pea single plant plus collection. Horticulture Research 4:17017. doi:10.1038/hortres.2017.17

Grover, C.E., Gallagher, J.P., Szadkowski, E.P., Page, J.T., Gore, M.A., Udall, J.A., and Wendel, J.F. 2017. Nucleotide diversity in the two co-resident genomes of allopolyploid cotton. Plant Systematics and Evolution 303:1–22. doi:10.1007/s00606-017-1411-1

Dabbert, T.A., Pauli, D., and Gore, M.A. 2017. Influences of the combination of high temperature and water deficit on the heritabilities and correlations of agronomic and fiber quality traits in upland cotton. Euphytica 213:6. doi:10.1007/s10681-016-1798-8

Angelovici, R., Batushansky, A., Deason, N., Gonzalez-Jorge, S., Gore, M.A., Fait, A., and DellaPenna, D. 2017. Network-guided GWAS improves identification of genes affecting free amino acids. Plant Physiology 173:872-886. doi:10.1104/pp.16.01287

Carlson, M.O., Gazave, E., Gore, M.A., and Smart, C.D. 2017. Temporal genetic dynamics of an experimental, biparental field population of Phytophthora capsici. Frontiers in Genetics 8:26. doi:10.3389/fgene.2017.00026.

Bird, K.A., An, H., Gazave, E., Gore, M.A., Pires, J.C., Robertson, L.D., and Labate, J.A. 2017. Population structure and phylogenetic relationships in a diverse panel of Brassica rapa L. Frontiers in Plant Science 8:321. doi:10.3389/fpls.2017.00321

Thompson, A.L., Pauli, D., Tomasi, P., Yurchenko, O., Jenks, M.A., Dyer, J.M., and Gore, M.A. 2017. Chemical variation for fiber cuticular wax levels in upland cotton (Gossypium hirsutum L.) evaluated under contrasting irrigation regimes. Industrial Crops and Products 100:153-162. doi:10.1016/j.indcrop.2017.02.030


Pauli, D., Chapman, S.C., Bart, R., Topp, C.N., Lawrence-Dill, C.J., Poland, J., and Gore, M.A. 2016. The quest for understanding phenotypic variation via integrated approaches in the field environment. Plant Physiology 172:622-634. doi:10.1104/pp.16.00592

Gonzalez-Jorge, S., Mehrshahi, P., Magallanes-Lundback, M., Lipka, A.E., Angelovici, R., Gore, M.A., and DellaPenna, D. 2016. ZEAXANTHIN EPOXIDASE activity potentiates carotenoid degradation in maturing Arabidopsis seed. Plant Physiology 171:1837-1851. doi:10.1104/pp.16.00604

French, A.N., Gore, M.A., and Thompson, A. 2016. Cotton phenotyping with lidar from a track-mounted platform. Proceedings of SPIE 9866, Autonomous air and ground sensing systems for agricultural optimization and phenotyping, SPIE Proceedings 9866. doi:10.1117/12.2224423

Gazave, E., Tassone E.E., Ilut, D.C., Wingerson, M., Datema, E., Witsenboer, H., Davis, J.B., Grant, D., Dyer, J.M., Jenks, M.A., Brown, J., and Gore, M.A. 2016. Population genomic analysis reveals differential evolutionary histories and patterns of diversity across subgenomes and subpopulations of Brassica napus L. Frontiers in Plant Science 7:525. doi:10.3389/fpls.2016.00525

Pauli, D., Andrade-Sanchez, P., Carmo-Silva, A.E., Gazave, E., French, A.N., Heun, J., Hunsaker, D.J., Lipka, A.E., Setter, T.L., Strand, R.J., Thorp, K.R., Wang, S., White, J.W., and Gore, M.A. 2016. Field-based high-throughput plant phenotyping reveals the temporal patterns of quantitative trait loci associated with stress-responsive traits in cotton. G3: Genes| Genomes| Genetics 6:865-879. doi:10.1534/g3.115.023515

Hinze, L.L., Gazave, E., Gore, M.A., Fang, D.D., Scheffler, B.E., Yu, J.Z., Jones, D.C., Frelichowski, J., and Percy, R.G. 2016. Genetic diversity of the two commercial tetraploid cotton species in the Gossypium Diversity Reference Set. Journal of Heredity 107:274-286. doi:10.1093/jhered/esw004

Ilut, D.C., Lipka, A.E., Jeong, N., Bae, D.N., Kim, D.H., Kim, J.H., Redekar, N., Yang, K., Park, W., Kang, S.-T., Kim, N., Moon, J.-K., Saghai Maroof, M.A., Gore, M.A., and Jeong, S.-C. 2016. Identification of haplotypes at the Rsv4 genomic region in soybean associated with durable resistance to soybean mosaic virus. Theoretical and Applied Genetics 129:453-468. doi:10.1007/s00122-015-2640-8

Tassone, E.E., Lipka, A.E., Tomasi, P., Lohrey, G.T., Dyer, J.M., Gore, M.A., and Jenks, M.A. 2016. Chemical variation for leaf cuticular wax levels revealed in a diverse panel of Brassica napus L. Industrial Crops and Products 79:77-83. doi:10.1016/j.indcrop.2015.10.047


Thorp, K.R., Gore, M.A., Andrade-Sanchez, P., Carmo-Silva, E., Welch, S.M., White, J.W., and French, A.N. 2015. Proximal hyperspectral sensing and data analysis approaches for field-based plant phenomics. Computers and Electronics in Agriculture 118:225-236. doi:10.1016/j.compag.2015.09.005

Ilut, D.C., Sanchez, P.L., Costich, D.E., Friebe, B., Coffelt, T.A., Dyer, J.M., Jenks, M.A., and Gore, M.A. 2015. Genomic diversity and phylogenetic relationships in the genus Parthenium (Asteraceae). Industrial Crops and Products 76:920-929. doi:10.1016/j.indcrop.2015.07.035

Grover, C.E., Gallagher, J.P., Jareczek, J.J., Page, J.T., Udall, J.A., Gore, M.A., and Wendel, J.F. 2015. Re-evaluating the phylogeny of allopolyploid Gossypium L. Molecular Phylogenetics and Evolution 92:45-52. doi:10.1016/j.ympev.2015.05.023

Hulse-Kemp, A.M., Lemm, J., Plieske, J., Ashrafi, H., Buyyarapu, R., Fang, D.D., Frelichowski, J., Giband, M., Hague, S., Hinze, L.L., Kochan, K., Riggs, P., Scheffler, J.A., Udall, J.A., Ulloa, M., Wang, S.S., Zhu, Q.-H., Bag, S.K., Bhardwaj, A., Burke, J.J., Byers, R.L., Claverie, M., Gore, M.A., et al. and Stelly, D.M. 2015. Development of a 63K SNP array for Gossypium and high-density mapping of intra- and inter-specific populations of cotton (G. hirsutum L.). G3: Genes| Genomes| Genetics 5:1187-1209. doi:10.1534/g3.115.018416

Diepenbrock, C.H. and Gore, M.A. 2015. Closing the divide between human nutrition and plant breeding. Crop Science 55:1437-1448. doi:10.2135/cropsci2014.08.0555

Lipka, A.E., Kandianis, C.B., Hudson, M.E., Yu, J., Drnevich, J., Bradbury, P.J., and Gore, M.A. 2015. From association to prediction: statistical methods for the dissection and selection of complex traits in plants. Current Opinion in Plant Biology 24:110-118. doi:10.1016/j.pbi.2015.02.010

Hinze, L.L., Fang, D.D., Gore, M.A., Scheffler, B.E., Yu, J.Z., Frelichowski, J., and Percy, R.G. 2015. Molecular characterization of the Gossypium diversity reference set of the US national cotton germplasm collection. Theoretical and Applied Genetics 128:313-327. doi:10.1007/s00122-014-2431-7


Dabbert, T.A. and Gore, M.A. 2014. Challenges and perspectives on improving heat and drought stress resilience in cotton. The Journal of Cotton Science 18:393-409.

Owens, B.F., Lipka, A.E., Magallanes-Lundback, M., Tiede, T., Diepenbrock, C.H., Kandianis, C.B., Kim, E., Cepela, J., Mateos Hernandez, M., Buell, C.R., Buckler, E.S., DellaPenna, D., Gore, M.A., and Rocheford, T. 2014. A foundation for provitamin A biofortification of maize: Genome-wide association and genomic prediction models of carotenoid levels. Genetics 198:1699–1716. doi:10.1534/genetics.114.169979

Yurchenko, O.P., Park, S., Ilut, D.C., Inmon, J.J., Millhollon, J.C., Liechty, Z., Page, J.T., Jenks, M.A., Chapman, K. D., Udall, J. A., Gore, M. A., and Dyer, J. M. 2014. Genome-wide analysis of the omega-3 fatty acid desaturase gene family in Gossypium. BMC Plant Biology 14:312.

Peiffer, J.A., Romay, M.C., Gore, M.A., Flint-Garcia, S.A., Zhang, Z., Millard, M.J., Gardner, C.A.C., McMullen, M.D., Holland, J.B., Bradbury, P.J., and Buckler, E.S. 2014. The genetic architecture of maize height. Genetics 196:1337-1356.

Gore, M.A., Fang, D.D., Poland, J.A., Zhang, J., Percy, R.G., Cantrell, R.G., Thyssen, G., and Lipka, A.E. 2014. Linkage map construction and quantitative trait locus analysis of agronomic and fiber quality traits in cotton. The Plant Genome 7:1-10.

Sanchez, P.L., Chen, M.-K., Pessarakli, M., Hill, H.J., Gore, M.A., and Jenks, M.A. 2014. Effects of temperature and salinity on germination of non-pelleted and pelleted guayule (Parthenium argentatum A. Gray) seeds. Industrial Crops and Products 55:90-96.

Sanchez, P.L., Costich, D.E., Friebe, B., Coffelt, T.A., Jenks, M.A., and Gore, M.A. 2014. Genome size variation in guayule and mariola: Fundamental descriptors for polyploid plant taxa. Industrial Crops and Products 54:1-5.

Fang, H., Zhou, H., Sanogo, S., Lipka, A.E., Fang, D.D., Percy, R.G., Hughs, S.E., Jones, D.C., Gore, M.A., and Zhang, J. 2014. Quantitative trait locus analysis of Verticillium wilt resistance in an introgressed recombinant inbred population of Upland cotton. Molecular Breeding 33:709-720.

Tyagi, P., Gore, M.A., Bowman, D.T., Campbell, B.T., Udall, J.A., and Kuraparthy, V. 2014. Genetic diversity and population structure in the US Upland cotton (Gossypium hirsutum L.). Theoretical and Applied Genetics 127:283-295.

Andrade-Sanchez, P., Gore, M.A., Heun, J.T., Thorp, K.R., Carmo-Silva, A.E., French, A.N., Salvucci, M.E., and White, J.W. 2014. Development and evaluation of a field-based high-throughput phenotyping platform. Functional Plant Biology 41:68-79.


Angelovici, R., Lipka, A.E., Deason, N., Gonzalez–Jorge, S., Lin, H., Cepela, J., Buell, R., Gore, M.A., and DellaPenna, D. 2013. Genome-wide analysis of branched-chain amino acid levels in Arabidopsis seed. The Plant Cell 25:4827-4843.

Gonzalez-Jorge, S., Ha, S.-H., Gilliland, L.U., Little, H., Zhou, A., Magallanes-Lundback, M., Lipka, A.E., Cepela, J., Buell, R., Gore, M.A., and DellaPenna, D. 2013. CAROTENOID CLEAVAGE DIOXYGENASE4 is a negative regulator of β-carotene content in Arabidopsis seed. The Plant Cell 25:4812-4826.

Lipka, A.E., Gore, M.A., Magallanes-Lundback, M., Mesberg, A., Lin, H., Tiede, T., Chen, C., Buell, C.R., Buckler, E.S., Rocheford, T., and DellaPenna, D. 2013. Genome-wide association study and pathway level analysis of tocochromanol levels in maize grain. G3: Genes| Genomes| Genetics 3:1287-1299.

Chandler, K., Lipka, A.E., Owens, B.F., Li, H., Buckler, E.S., Rocheford, T., and Gore, M.A. 2013. Genetic analysis of visually scored orange kernel color in maize. Crop Science 53:189-200.

Yu, J., Yu, S., Gore, M., Wu, M., Zhai, H., Li, X., Shuli, F., Song, M., and Zhang, J. 2013. Identification of quantitative trait loci across interspecific F2, F2:3 and testcross populations for agronomic and fiber traits in tetraploid cotton. Euphytica 191:375-389.


Lipka, A.E., Tian, F., Wang Q., Peiffer, J., Li, M., Bradbury, P.J., Gore, M.A., Buckler, E.S., and Zhang, Z. 2012. GAPIT: genome association and prediction integrated tool. Bioinformatics 28:2397-2399.

Thorp, K., Andrade-Sanchez, P., Gore, M., White, J., and French, A. 2012. Information technologies for field-based high-throughput phenotyping. Resource-Engineering and Technology for a Sustainable World 19:8-9.

Chia, J., Song, C., Bradbury, P., Costich, D., De Leon, N., Doebley, J., Elshire, R., Gaut, B., Geller, L., Glaubitz, J., Gore, M., Guill, K., Holland, J., Hufford, M., Lai, J., Li, M., Liu, X., Lu, Y., McCombie, R., Nelson, R., Poland, J.A., Prasanna, B.M., Phyäjärvi, T., Rong, T., Sekhon, R., Sun, Q., Tenaillon, M., Tian, F., Wang, J., Xu, X., Zhang, Z., Kaeppler, S.M., Ross-Ibarra, J., McMullen, M.D., Buckler, E.S., Zhang, G., Xu, Y., and Ware, D. 2012. Maize HapMap2 identifies extant variation from a genome in flux. Nature Genetics 44:803-807.

Carmo-Silva, E.A., Gore, M.A., Andrade-Sanchez, P., French, A.N., Hunsaker, D.J., and Salvucci, M.E. 2012. Decreased CO2 availability and inactivation of Rubisco limit photosynthesis in cotton plants under heat and drought stress in the field. Environmental and Experimental Botany 83:1-11.

White, J.W., Andrade-Sanchez, P., Gore, M.A., Bronson, K.F., Coffelt, T.A., Conley, M.M., Feldmann, K.A., French, A.N., Heun, J.T., Hunsaker, D.J., Jenks, M.A, Kimball, B.A., Roth, R.L., Strand, R.J., Thorp, K.R., Wall, G.W., and Wang, G. 2012. Field-based phenomics for plant genetics research. Field Crops Research 133:101-112.

Gore, M.A., Percy, R.G., Zhang, J., Fang, D.D., and Cantrell, R.G. 2012. Registration of the TM-1/NM24016 cotton recombinant inbred mapping population. Journal of Plant Registrations 6:124-127.


Gore, M.A., Coyle, G., Friebe, B., Coffelt, T.A., and Salvucci, M.E. 2011. Complex ploidy level variation in guayule breeding programs. Crop Science 51:210-216.

Setter, T.L., Yan, J., Warburton, M., Ribaut, J.-M., Xu, Y., Sawkins, M., Buckler, E.S., Zhang, Z., and Gore, M.A. 2011. Genetic association mapping identifies single nucleotide polymorphisms in genes that affect abscisic acid levels in maize floral tissues during drought. Journal of Experimental Botany 62:701-716.

Gore, M. 2011. Molecular plant breeding. Field Crops Research 123:183-184.


Zhang, Z., Ersoz, E., Lai, C.-Q., Todhunter, R.J., Tiwari, H.K., Gore, M.A., Bradbury, P.J., Yu, J., Arnett, D.K., Ordovas, J.M., and Buckler, E.S. 2010. Mixed linear model approach adapted for genome-wide association studies. Nature Genetics 42:355-360.

Li, Q., Yang, X., Bai, G., Warburton, M., Mahuku, G., Gore, M., Dai, J., Li, J., and Yan, J. 2010. Cloning and characterization of a putative GS3 ortholog involved in maize kernel development. Theoretical and Applied Genetics 120:753-763.


Gore, M.A., Chia, J.-M., Elshire, R.J., Sun, Q., Ersoz, E.S., Hurwitz, B.L., Peiffer, J.A., McMullen, M.D., Grills, G.S., Ross-Ibarra, J., Ware, D.H., and Buckler, E.S. 2009. A first generation haplotype map of maize. Science 326:1115-1117.

Gore, M.A., Wright, M.H., Ersoz, E.S., Bouffard, P., Szekeres, E.S., Jarvie, T.P., Hurwitz, B.L., Narechania, A., Harkins, T.T., Grills, G.S., Ware, D.H., and Buckler, E.S. 2009. Large-scale discovery of gene-enriched SNPs. The Plant Genome 2:121-133.


Zhu, C., Gore, M., Buckler, E.S., and Yu, J. 2008. Status and prospects of association mapping in plants. The Plant Genome 1:5-20.


Buckler, E., and Gore, M. 2007. An Arabidopsis haplotype map takes root. Nature Genetics 39: 1056-1057.

Gore, M., Bradbury, P., Hogers, R., Kirst, M., Verstege, E., van Oeveren, J., Peleman, J., Buckler, E., and van Eijk, M. 2007. Evaluation of target preparation methods for single-feature polymorphism detection in large complex plant genomes. Crop Science 47: S135–S148.


Hayes, A.J., Jeong, S.C., Gore, M.A., Yu, Y.G., Buss, G.R., Tolin, S.A., and Saghai Maroof, M.A. 2004. Recombination within a nucleotide-binding-site/leucine-rich-repeat gene cluster produces new variants conditioning resistance to soybean mosaic virus in soybeans. Genetics 166: 493-503.


Padidam, M., Gore, M., Lu, D. L., and Smirnova, O. 2003. Chemical-inducible, ecdysone receptor-based gene expression system for plants. Transgenic Research 12: 101-109.


Gore, M.A., Hayes, A.J., Jeong, S.C., Yue, Y.G., Buss, G.R., and Saghai Maroof, M.A. 2002. Mapping tightly linked genes controlling potyvirus infection at the Rsv1 and Rpv1 region in soybean. Genome 45: 592-599.