Rebecca Nelson

Selected Publications: Research & Extension (Last 5 years)

• Aoun, M., W. Stafstrom, P. Priest, J. Fuchs, G.L. Windham, W.P. Williams, and R.J. Nelson.  2020.  Low-cost grain sorting technologies to reduce mycotoxin contamination in maize and groundnut.  Food Control:  https://doi.org/10.1016/j.foodcont.2020.107363  
• Morales, L., Repka, A., Swarts, K. L., Stafstrom, W. C., He, Y., Sermons, S. M., Yang, Q., Lopez‐Zuniga, L.O., Rucker, E., Thomason, Wade, E., Nelson, R.J., and Balint‐Kurti, P. J. (2020). Genotypic and phenotypic characterization of a large, diverse population of maize near‐isogenic lines. The Plant Journal. https://doi.org/10.1111/tpj.14787
• Nelson, R. 2020.  International agriculture's needed shift from energy intensification to agroecological intensification.  Food Policy: 101815.
• Phillips, E., F. Ngure, L. Smith, E. Makule, P.C. Turner, R. Nelson, M. Kimanya, R. Stoltzfus and N. Kassim.  2020.  Protocol for the trial to establish a causal link between mycotoxin exposure and child stunting: a cluster randomized trial.  BMC Public Health.  https://doi.org/10.1186/s12889-020-08694-6
• Nelson, R.  2020.  International plant pathology: past and future contributions to global food security.  Phytopathology 11(2): 245-253.
• Ortiz O., Thiele G., Nelson R., Bentley J.W. (2020) Participatory research (PR) at CIP with potato farming systems in the Andes: Evolution and prospects. In: Campos H., Ortiz O. (eds) The Potato Crop. Springer, Cham
• 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 (December), 1–11. https://doi.org/10.3389/fpls.2019.01550
• 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(1), 0. https://doi.org/10.2135/tppj2019.03.0006
• Falcon, Celeste; Kaeppler, SM; Spalding, EP; Miller, ND; Haase, N; Al Khalifah, N; Bohn, M; Buckler, ES; Campbell, DA; Ciampitti, I; Coffey, L; Edwards, J; Ertl, D; Flint-Garcia, S; Gore, MA; Graham, C; Hirsch, CN; Holland, JB; Jarquin, D; Knoll, J; Lauter, N; Lawrence-Dill, CJ; Lee, EC; Lorenz, A; Lynch; JP; Murray, SC; Nelson, RJ; Romay, MC; Rocheford, T; Schnable, PS; Scully, B; Smith, M; Springer, N; Tuinstra, MR; Walton, R; Weldekidan, T; Wisser, RJ; Xu, W; de Leon, N; 2019.  Relative utility of agronomic, phenological, and morphological traits for assessing genotype-by-environment interaction in maize inbreds. Crop Sci. 2020;1-20. https://doi.org/10.1002/csc2.20035
• Kolkman, J.M., J. Strable, K. Harline, D.E. Kroon, T. Wiesner-Hanks, P.J. Bradbury and R.J. Nelson.  2019.  Maize nested introgression library provides evidence for the involvement of liguless1 in resistance to northern leaf blight.  Doi: https:/doi.org/10.1101/818518. On bioRxiv: http://biorxiv.org/cgi/content/short/818518v1
• 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 Leaf Blight in UAV Images Using Deep Learning. Remote Sensing, 11(19), 1–10. https://doi.org/10.3390/rs11192209
• Bullock, D., A. Mangeni, T. Wiesner-Hanks, C. DeChant, E. Stewart, N. Kaczmar, R.J. Nelson, M.A. Gore, and H. Lipson.  2019. Automated crabgrass detection in aerial imagery with context.  arXiv preprint arXiv:1910.00652
• Doblas- Ibáñez, P., Deng, K., Vasquez, M. F., Giese, L., Cobine, P. A., Kolkman, J. M., King, H., Jamann, T.M., Balint-Kurti, P., De la Fuent, L., Mackey, D., Nelson, R.J., and Smith, L. G. 2019. Dominant, heritable resistance to Stewart’s wilt in maize is associated with an enhanced vascular defense response to infection with Pantoea stewartii. Molecular Plant-Microbe Interactions, 32(12), 1581–1597. https://doi.org/10.1094/MPMI-05-19-0129-R
• Morales, L., C.T. Zila, D.E. Moreta, M.M. Arbelaez, P.G. Balint-Kurti, J.B. Holland and R.J. Nelson.  2019.  Diverse mechanisms of resistance to Fusarium verticillioides infection and fumonisin contamination in four maize recombinant inbred line families.  Toxins 11(2), 86; https://doi.org/10.3390/toxins11020086
• Ortiz, O., R. Nelson, M. Olanya, G. Thiele, R. Orrego, W. Pradel, R. Kakehunzire, G. Woldegiorgis, J. Gabriel, J. Vallejo, and X. Kaiyun.  2019.  Human and technical dimensions of potato IPM using farmer field schools: CIP and partners’ experience with potato late blight management.  Journal of Integrated Pest Management 10 (1): 4.  https://doi.org/10.1093/jipm/pmz002
• Lopez-Zuniga, L.O., P. Wolters, S. Davis, T. Weldekidan, J. Kolkman, R. Nelson, K. Hooda, E. Rucker, W. Thomason, R. Wisser and P. Balint-Kurti.  2019.  Using maize chromosome segment substitution line populations for the identification of loci associated with multiple disease resistance.  G3: Genes, Genomes, Genetics 9 (1): 189-201; https://doi.org/10.1534/g3.118.200866
• Mutiga, S., N. Chepkwony, O. A. Hoekenga, S.A. Flint-Garcia and R.J. Nelson. 2019. The role of ear environment in post-harvest susceptibility of maize to toxigenic Aspergillus flavus.  Plant Breeding 138(1): 38-50.  DOI: 10.1111/pbr.12672
• Klessig, D.F., M. Manohar, S. Baby, A. Koch, W. Danquah, B. Wiseborn, E. Luna, H.-J. Park, J.M. Kolkman, B.G. Turgeon, and R. Nelson.  2019.  Nematode ascaroside enhances resistance in a broad spectrum of plant–pathogen systems.  Journal of Phytopathology 167 (5): 265-272.
• Minker, Katharine R; M. L. Biedrzycki; A. Kolagunda; S. Rhein; F. J. Perina; S. S. Jacobs; M. Moore; T. M. Jamann; Q.Yang; R. Nelson; 2018.  Semiautomated confocal imaging of fungal pathogenesis on plants: Microscopic analysis of macroscopic specimens. Microscopy Research and Technique 81 (2): 141-152.
• Al Khalifah, N., D. A. Campbell, C. M. Falcon, J. M. Gardiner, N. D. Miller, M. C. Romay, R. Walls, R. Walton, C-T. Yeh, M. Bohn and R. Nelson. 2018.  Maize Genomes to Fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets. BioMed Central, BMC research notes 11 (1): 452.
• Morales, L., Marino, T.P., Wendt, A.J., Fouts, J.Q., Holland, J.B., and Nelson, R.J.  2018.  Dissecting symptomatology and fumonisin contamination produced by Fusarium verticillioides in maize ears
• Phytopathology, 5 Nov 2018, DOI: 10.1094/PHYTO-05-18-0167-R
• 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 symptoms. BMC Research Notes In Press doi: 10.1186/s13104-018-3548-6
• Mideros, S.X., Chung, C.-L., Wiesner-Hanks, T., Poland, J., Wu, D., Fialko, A.A., Turgeon, G., Nelson, R., 2018. Determinants of virulence and in-vitro development colocalize on a genetic map of Setosphaeria turcica.   Phytopathology. doi:10.1094/PHYTO-01-17-0021-R
• Nelson, R., T. Wiesner-Hanks, R. Wisser and P. Balint-Kurti. 2017. Navigating complexity to breed disease-resistant crops. Nature Genetics Reviews. doi:10.1038/nrg.2017.82
• Gage et al. … R. Nelson, … N. de Leon. 2017. The effect of artificial selection on phenotypic plasticity in maize. Nature Communications. DOI: 10.1038/s41467-017-01450-2 [40 authors mostly in alphabetical order]
• DeChant, C., Wiesner-Hanks, T., Chen, S., Stewart, E.L., Yosinski, J., Gore, M.A., Nelson, R., Lipson, H. 2017.  Automated identification of norther leaf blight-infected maize plants from field imagery using deep learning.  In press, Phytopathology. PHYTO11160417R. doi:10.1094/PHYTO-11-16-0417-R
• Yang, Q., He, Y., Kabahuma, M., Chaya, T., Kelly, A., Borrego, E., Bian, Y., El Kasmi, F., Yang, L., Teixeira, P., Kolkman, J., Nelson, R., Kolomiets, M., L Dangl, J., Wisser, R., Caplan, J., Li, X., Lauter, N., Balint-Kurti, P., 2017. A gene encoding maize caffeoyl-CoA O-methyltransferase confers quantitative resistance to multiple pathogens. Nature Genetics 49, 1364–1372.
• Stasiewicz, M.J., Falade, T.D.O., Mutuma, M., Mutiga, S.K., Harvey, J.J.W., Fox, G., Pearson, T.C., Muthomi, J.W., Nelson, R., 2017. Multi-spectral kernel sorting to reduce aflatoxins and fumonisins in Kenyan maize. Food Control. 78: 203-214.
• Smith, L.E., Mbuya, M.N.N., Prendergast, A.J., Turner, P.C., Ruboko, S., Humphrey, J.H., Nelson, R., Chigumira, A., Kembo, G., Stoltzfus, R.J., 2017. Determinants of recent aflatoxin exposure among pregnant women in rural Zimbabwe. Mol Nutr Food Res 61. doi:10.1002/mnfr.201601049
• Mutiga, S.K., Morales, L., Angwenyi, S., Wainaina J., Harvey, J., Das, B., Nelson, R. 2017. Association between agronomic traits and aflatoxin accumulation in diverse maize lines grown under two soil nitrogen levels in Eastern Kenya. Field Crops Research. 205: p. 124-134.
• Michelmore, R., Coaker, G., Bart, R., Beattie, G., Bent, A., Bruce, T., Cameron, D., Dangl, J., Dinesh-Kumar, S., Edwards, R., Eves-van den Akker, S., Gassmann, W., Greenberg, J.T., Hanley-Bowdoin, L., Harrison, R.J., Harvey, J., He, P., Huffaker, A., Hulbert, S., Innes, R., Jones, J.D.G., Kaloshian, I., Kamoun, S., Katagiri, F., Leach, J., Ma, W., McDowell, J., Medford, J., Meyers, B., Nelson, R., Oliver, R., Qi, Y., Saunders, D., Shaw, M., Smart, C., Subudhi, P., Torrance, L., Tyler, B., Valent, B., Walsh, J., 2017. Foundational and Translational Research Opportunities to Improve Plant Health. MPMI 30, 515–516. doi:10.1094/MPMI-01-17-0010-CR
• Wiesner-Hanks, T., & Nelson, R. 2016. Multiple Disease Resistance in Plants. https://doi.org/10.1146/annurev-phyto-080615-100037
• Nelson, R.  2016.  Sorting technologies to rehabilitate toxic maize.  Outlooks on Pest Management.  DOI: 10.1564/v27_dec_00
• Nelson, R., Coe, R., & Haussmann, B. I. G. 2016. Farmer research networks as a strategy for matching diverse options and contexts in smallholder agriculture. Experimental Agriculture, 1–20. https://doi.org/10.1017/S0014479716000454
• Smith, L., Stasiewicz, M., Hestrin, R., Morales, L., Mutiga, S., & Nelson, R. 2016. Examining environmental drivers of spatial variability in aflatoxin accumulation in Kenyan maize: potential utility in risk prediction models. African Journal of Food, Agriculture, Nutrition and Development, 16(3), 11086–11105. https://doi.org/10.18697/ajfand.75.ILRI09
• Liu, X., J. Cook, S. Melia-Hancock, K. Guill, C. Bottoms, A. Garcia, O. Ott, R. Nelson, J. Recker, P. Balint-Kurti, S. Larsson, N. Lepak, E. Buckler, L. Trimble, W. Tracy, M.D. McMullen and S.A. Flint-Garcia.  2015.  Expanding maize genetic resources with pre-domestication alleles: maize-teosinte introgression populations.  The Plant Genome Accepted paper, posted 10/05/2015, doi:10.3835/plantgenome2015.07.0053
• Benson, J.A., J.A. Poland, B.M. Benson, E.L. Stromberg and R.J. Nelson.  2015.  Resistance to Gray Leaf Spot of Maize: Genetic Architecture and Mechanisms Elucidated through Nested Association Mapping and Near-Isogenic Line Analysis. PLoS genetics 11.3 (2015): e1005045-e1005045.
• Mutiga, S.K., V. Hoffmann, J. W. Harvey, M. G. Milgroom, and R. J. Nelson.  2015.  Assessment of aflatoxin and fumonisin contamination of maize in western Kenya.  Phytopathology 105(9): 1250-1261.

Grant portfolio of over 13.5 million since 2011

• Resistance and Trade-offs: Using Near-Isogenic Lines to Characterize Maize Disease Resistance Loci. Funded by the Cornell University NY Ag Exp Station Hatch Fund: $105,000.00. 2019-2022
• Support for Collaborative Crop Research Program. Funded by Cornell University McKnight Foundation and The Bill & Melinda Gates Foundation: $993,436.00. 8/1/2019 - 7/31/2021. 
• Trial to Establish Casual Linkage Between Mycotoxin Exposure and Child Stunting. Funded by The Bill & Melinda Gates Foundation: $4,995,639.00. 6/21/17 - 4/30/2022. 
• Support for Collaborative Crop Research Program. Funded by the Cornell University McKnight Foundation and The Bill & Melinda Gates Foundation. 8/1/2016 - 7/31/2019. 
• NRI: Deep Learning UVAS for High-Throughput Agricultural Disease Phenotyping. Funded by the National Science Foundation: $233,571.00 for Nelson, $1,149,273.00 for team. 8/01/2015 - 7/31/2019. 
• Analysis of the Mechanism and Utility of Increased Pathogen Resistance in Maize Pani Mutants. Funded by the Univ. California San Diego, AFRI-Foundation Program: $83,835.00. 2/1/15 - 1/31/19. 
• GEPR: Genetic and histological dissection of phenotypic variation in quantitative resistance to maize diseases. Funded by NSF-PGRP, OSP# 64014: $600,000 for Nelson; with Wisser et al. 11/14/2011-11/13/2016.
• Cornell University Start-Up Funds. Funded by Cornell University: $250,000.00. 8/1/2011 - 7/31/2016. 
• Support for Collaborative Crop Research Program. Funded by Cornell University McKnight Foundation and The Bill & Melinda Gates Foundation: $2,500,000.00. 8/1/2011 - 7/31/2016. 
• Defining the mechanisms of quantitative disease resistance loci in maize. Funded by the Cornell University NY Ag Exp Station Hatch Fund: $60,000.00. 10/01/11 - 9/30/14. 
• Integrative Graduate Education and Research Traineeships (IGERT): Food Systems and Poverty Reduction. Funded by NSF:  $3,194,094 for team (with Barrett et al.). 7/01/09 - 6/30/14. 
• Stories of crop evolution, biodiversity and domestication and methods of genomic assisted crop improvement for curricula development. Funded by USDA-AFRI 1890 Capacity: $45,000 for Nelson (with Mazourek et al.). 9/01/2010 - 8/31/2013. 
• Capacity and Action for Aflatoxin Reduction in Eastern Africa: Establishing a Regional Mycotoxin Analytical Platform and its Application in Reducing Aflatoxin Contamination of Kenyan and Tanzanian Maize. Funded by the Government of Australia: $75,150 for Nelson and Milgroom contributions (sub-contractor with Harvey et al.; grant awarded to Biosciences east and central Africa). 2011-2013. 

Courses Taught

IARD/DSOC 1100: Perspectives in International Agriculture and Rural Development

Co-taught with Sarah Giroux

The course will enable students to understand the significant issues in international agriculture and rural development. We review global challenges and opportunities related to poverty and hunger from various perspectives, and consider alternative strategies for improving the productivity and sustainability of agricultural systems, and reducing poverty, hunger, and malnutrition. The course includes lectures that give a broad overview of each topic, accompanied by discussions and readings on selected issues. The class is not intended to be an in-depth analysis of any one of these topics; instead, it provides a sample of perspectives. For most of the topics we cover, there are semester-long classes, internships, job opportunities, and more at Cornell. If you want advice or information on how to follow up, please ask us. To acquire more in-depth knowledge of a place and topic(s) of interest, each student will pick a focus issue for their poster and paper assignments (see below for more; each assignment will be discussed further in class). Students will select their focus issue and work both with peers and on their own throughout the semester to explore their topic.

VTPMD_6121: Food Systems and Health 

Co-taught with Katie Fiorella

Students will explore the complex interconnections of food systems and public health needs and learn from interdisciplinary experts and professionals in the fields of local and international public health, economics, sociology, and environment.

The goal of this course is to introduce students to connections between food systems and health. The course uses concepts, theories and methods from multiple disciplines. In addition, this course will provide those students in the Food Systems & Health concentration of the MPH program with a common base knowledge. Much of the material will push many students well outside their comfort zone; this is to be expected, indeed embraced. By familiarizing students with the basic concepts and terms in disciplines with which they will likely need to interact, the course will help students find the connections among the concepts, methods and themes of the various disciplines engaged in the study of food systems, poverty reduction, and public health. Given this orientation, most classes are instructor-led, but typically with substantial student engagement in discussion of key readings and identification of key research topics sparked by readings and concepts.