Data for: Development of a Portable Paper-based Biosensor for the Identification of Genetically Modified Corn (Zea mays) and Soybean (Glycine max)

Paper title: Development of a Portable Paper-based Biosensor for the Identification of Genetically Modified Corn (Zea mays) and Soybean (Glycine max)
Authors: Bilal Ahmed1, Bibek Raut2, Adele Pauley3, Josiah Levi Davidson1,4, Sam Yang3, Mohit S. Verma1, 2, 4*
Affiliations:
1Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, USA, 47907
2Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA, 47907
3Bayer Crop Science Division, St. Louis, MO, USA 63167
4Birck Nanotechnology Center, Purdue University, West Lafayette, IN, USA, 47907

This dataset supports the manuscript titled "Development of a Portable Paper-based Biosensor for the Identification of Genetically Modified Corn (Zea mays) and Soybean (Glycine max)" published in Biosensors and Bioelectronics. It includes raw and processed data from loop-mediated isothermal amplification (LAMP) assays using both genomic DNA and crude leaf extracts of genetically modified (GM) and non-GM corn and soy. The dataset contains: (1) Fluorescent quantitative LAMP (qLAMP) amplification curves data, (2) Normalized hue index (NHI) data from time-lapse image scans of microfluidic paper-based analytical device (μPAD)-LAMP cartridges, and (3) Receiver operating characteristic (ROC) curves data. Data are organised into files by panel number of figures (both main and supplementary figures). Image analysis Python scripts used for data extraction are also provided with a set of time-lapse images, for users to run with Python scripts.