Gradient boosting and bayesian network machine learning models predict aflatoxin and fumonisin contamination of maize in Illinois – First USA case study by Lina Castano-Duque, Martha Vaughan, James Lindsay, Kristin Barnett, Kanniah Rajasekaran

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Flavonoids Modulate <i>Aspergillus flavus</i> Proliferation and Aflatoxin Production by Lina Castano-Duque, Matthew D. Lebar, Carol Carter-Wientjes, David Ambrogio, Kanniah Rajasekaran

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Investigating the Impact of Flavonoids on <i>Aspergillus flavus</i>: Insights into Cell Wall Damage and Biofilms by Lina Castano-Duque, Matthew D. Lebar, Brian M. Mack, Jessica M. Lohmar, Carol Carter-Wientjes

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Genes and genetic mechanisms contributing to fall armyworm resistance in maize by Marilyn L. Warburton, Sandra W. Woolfolk, J. Spencer Smith, Leigh K. Hawkins, Lina Castano‐Duque, Matthew D. Lebar, W. Paul Williams

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Gradient boosting machine learning model to predict aflatoxins in Iowa corn by Emily H. Branstad-Spates, Lina Castano-Duque, Gretchen A. Mosher, Charles R. Hurburgh, Phillip Owens, Edwin Winzeler, Kanniah Rajasekaran, Erin L. Bowers

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Flavonoids Modulate the Accumulation of Toxins From Aspergillus flavus in Maize Kernels by Lina Castano-Duque, Matthew K. Gilbert, Brian M. Mack, Matthew D. Lebar, Carol H. Carter-Wientjes, Christine M. Sickler, Jeffrey W. Cary, Kanniah Rajasekaran

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Dynamic geospatial modeling of mycotoxin contamination of corn in Illinois: unveiling critical factors and predictive insights with machine learning by Lina Castano-Duque, Edwin Winzeler, Joshua M. Blackstock, Cheng Liu, Noemi Vergopolan, Marlous Focker, Kristin Barnett, Phillip Ray Owens, H. J. van der Fels-Klerx, Martha M. Vaughan, Kanniah Rajasekaran

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Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models by Lina Castano-Duque, Angela Avila, Brian M. Mack, H. Edwin Winzeler, Joshua M. Blackstock, Matthew D. Lebar, Geromy G. Moore, Phillip Ray Owens, Hillary L. Mehl, Jianzhong Su, James Lindsay, Kanniah Rajasekaran

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