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Lina Castano-Duque
Food and Feed Safety Research
Research Plant Pathologist

Phone: (504) 286-4556
Fax:

(Employee information on this page comes from the REE Directory. Please contact your front office staff to update the REE Directory.)

Projects
Development of Aflatoxin Resistant Corn Lines Using Omic Technologies
In-House Appropriated (D)
  Accession Number: 440095
Generating Input Features for Modeling Mycotoxin Outbreaks in the USA
Non-Assistance Cooperative Agreement (S)
  Accession Number: 444250
Evaluate the Role of Volatile Organic Compounds (VOCs) in Plant-Fungal Interactions, especially Corn-Aspergillus Interaction
Non-Assistance Cooperative Agreement (S)
  Accession Number: 444518
Corn-environment Interactions and Their Impact and Aflatoxin Contamination in Different Geographical Corn-growing Regions of Texas
Non-Assistance Cooperative Agreement (S)
  Accession Number: 446867
Modeling to Forecast Mycotoxin Breakout in U.S.-Grown Maize
Non-Assistance Cooperative Agreement (S)
  Accession Number: 439725

Publications (Clicking on the reprint icon Reprint Icon will take you to the publication reprint.)
Investigating the impact of flavonoids on aspergillus flavus: Insights into cell wall damage and biofilms Reprint Icon - (Peer Reviewed Journal)
Castano-Duque, L.M., Lebar, M.D., Mack, B.M., Lohmar, J.M., Carter Wientjes, C.H. 2024. Investigating the impact of flavonoids on aspergillus flavus: Insights into cell wall damage and biofilms. The Journal of Fungi. 10(9). 665. https://doi.org/10.3390/jof10090665.
Predicting fumonisins in Iowa corn: gradient boosting machine learning Reprint Icon - (Peer Reviewed Journal)
Branstad-Spates, E., Castano-Duque, L.M., Mosher, G., Hurburgh, Jr, C., Rajasekaran, K., Owens, P.R., Winzeler, H.E., Bowers, E. 2024. Predicting fumonisins in Iowa corn: gradient boosting machine learning. Cereal Chemistry. https://doi.org/10.1002/cche.10824.
Genomic and metabolomic diversity within a familial population of Aspergillus flavus - (Peer Reviewed Journal)
Dynamic geospatial modeling of mycotoxin contamination of corn in Illinois: unveiling critical factors and predictive insights with machine learning Reprint Icon - (Peer Reviewed Journal)
Castano-Duque, L.M., Winzeler, H.E., Blackstock, J.M., Cheng, L., Vergopolan, N., Focker, M., Barnett, K., Owens, P.R., Van Der Fels-Klerx, I., Vaughan, M.M., Rajasekaran, K. 2023. Dynamic geospatial modeling of mycotoxin contamination of corn in Illinois: unveiling critical factors and predictive insights with machine learning. Frontiers in Microbiology. 14. Article 1283127. https://doi.org/10.3389/fmicb.2023.1283127.
Gradient boosting machine learning model to predict aflatoxins in Iowa corn Reprint Icon - (Peer Reviewed Journal)
Branstad-Spates, E.H., Castano-Duque, L.M., Mosher, G.A., Hurburgh, Jr., C.R., Owens, P.R., Winzeler, H.E., Rajasekaran, K., Bowers, E.L. 2023. Gradient boosting machine learning model to predict aflatoxins in Iowa corn. Frontiers in Microbiology. 14. Article 1248772. https://doi.org/10.3389/fmicb.2023.1248772.
Predictive models to manage mycotoxin outbreaks in the USA - (Abstract Only)
Predictive models to manage mycotoxin outbreaks in the USA - (Abstract Only)
Inclusive collaboration across plant physiology and genomics: now is the time! Reprint Icon - (Other)
Baxter, I., Ainsworth, E.A., Brooks, M.D., Castano-Duque, L.M., Londo, J.P., Washburn, J.D., McElrone, A.J., Coyne, C.J., et al. 2023. Inclusive collaboration across plant physiology and genomics: now is the time! Plant Direct. 7(5). Article e493. https://doi.org/10.1002/pld3.493.
Genes and genetic mechanisms contributing to fall armyworm resistance in maize Reprint Icon - (Peer Reviewed Journal)
Warburton, M.L., Woolfolk, S.W., Smith, J.S., Hawkins, L.K., Castano-Duque, L.M., Lebar, M.D., Williams, W.P. 2023. Genes and genetic mechanisms contributing to fall armyworm resistance in maize. The Plant Genome. 16(2):e20311. https://doi.org/10.1002/tpg2.20311.
Flavonoids modulate Aspergillus flavus proliferation and aflatoxin production Reprint Icon - (Peer Reviewed Journal)
Castano-Duque, L., Lebar, M.D., Carter-Wientjes, C., Ambrogio, D., Rajasekaran, K. 2022. Flavonoids modulate Aspergillus flavus proliferation and aflatoxin production. The Journal of Fungi. 8(1):1211. https://doi.org/10.3390/jof8111211.
Gradient boosting and bayesian network machine learning models predict aflatoxin and fumonisin contamination of maize in Illinois – First USA case study Reprint Icon - (Peer Reviewed Journal)
Castano-Duque, L., Vaughan, M., Lindsay, J., Barnett, K., Rajasekaran, K. 2022. Gradient boosting and bayesian network machine learning models predict aflatoxin and fumonisin contamination of maize in Illinois – First USA case study. Frontiers in Microbiology. 13. Article 1039947. https://doi.org/10.3389/fmicb.2022.1039947.
Flavonoids modulate the accumulation of toxins from Aspergillus flavus in maize kernels Reprint Icon - (Peer Reviewed Journal)
Castano-Duque, L.M., Gilbert, M.K., Mack, B.M., Lebar, M.D., Carter-Wientjes, C.H., Sickler, C.M., Cary, J.W., Rajasekaran, K. 2021. Flavonoids modulate the accumulation of toxins from Aspergillus flavus in maize kernels. Frontiers in Plant Science. 12:761446. https://doi.org/10.3389/fpls.2021.761446.