Plant Sciences Commons^™

Statistical And Machine Learning Methods Evaluated For Incorporating Soil And Weather Into Corn Nitrogen Recommendations, Curtis J. Ransom, Newell R. Kitchen, James J. Camberato, Paul R. Carter, Richard B. Ferguson, Fabián G. Fernández, David W. Franzen, Carrie A. M. Laboski, D. Brenton Myers, Emerson D. Nafziger, John E. Sawyer, John F. Shanahan

John E. Sawyer

Nitrogen (N) fertilizer recommendation tools could be improved for estimating corn (Zea mays L.) N needs by incorporating site-specific soil and weather information. However, an evaluation of analytical methods is needed to determine the success of incorporating this information. The objectives of this research were to evaluate statistical and machine learning (ML) algorithms for utilizing soil and weather information for improving corn N recommendation tools. Eight algorithms [stepwise, ridge regression, least absolute shrinkage and selection operator (Lasso), elastic net regression, principal component regression (PCR), partial least squares regression (PLSR), decision tree, and random forest] were evaluated using a dataset …

Comparing The Fieldscout Greenindex+ Chlorophyll Sensing App To The Minolta Spad Meter, Jessica D. Pille, John E. Sawyer, Daniel W. Barker

John E. Sawyer

With the improvement of mobile computing, the company Spectrum Technologies, Inc. has developed a precision Ag App which adapts an iPod, iPad, or iPhone camera to select for specific wavelengths of light from a corn leaf (Zea mays L.) in comparison to accompanying board for light/color comparison. The App computes a Dark Green Color Index (DGCI), indicating leaf greenness, which relates to the amount of chlorophyll and thus, indirectly, leaf nitrogen (N) content. The question posed for this study is: How accurate and convenient is the App compared to a proven technology, the Minolta 502 Soil-Plant Analysis Development (SPAD) meter; …

Tal Effector-Nucleotide Targeter (Tale-Nt) 2.0: Tools For Tal Effector Design And Target Prediction, Erin L. Doyle, Nicholas J. Booher, Daniel S. Standage, Daniel F. Voytas, Volker P. Brendel, John K. Vandyk, Adam J. Bogdanove

John K. VanDyk

Transcription activator-like (TAL) effectors are repeat-containing proteins used by plant pathogenic bacteria to manipulate host gene expression. Repeats are polymorphic and individually specify single nucleotides in the DNA target, with some degeneracy. A TAL effector-nucleotide binding code that links repeat type to specified nucleotide enables prediction of genomic binding sites for TAL effectors and customization of TAL effectors for use in DNA targeting, in particular as custom transcription factors for engineered gene regulation and as site-specific nucleases for genome editing. We have developed a suite of web-based tools called TAL Effector-Nucleotide Targeter 2.0 (TALE-NT 2.0;https://boglab.plp.iastate.edu/) that enables design of custom …

The Plant Ontology Database: A Community Resource For Plant Structure And Developmental Stages Controlled Vocabulary And Annotations, Shulamit Avraham, Chih-Wei Tung, Katica Ilic, Pankaj Jaiswal, Elizabeth A. Kellogg, Susan Mccouch, Anuradha Pujar, Leonore Reiser, Seung Yon Rhee, Martin M. Sachs, Mary L. Schaeffer, Lincoln Stein, Peter Stevens, Leszek Vincent, Felipe Zapata, Doreen Ware

Peter Stevens