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Full-Text Articles in Life Sciences

Automatic Identification And Monitoring Of Plant Diseases Using Unmanned Aerial Vehicles: A Review, Krishna Neupane, Fulya Baysal-Gurel Sep 2021

Automatic Identification And Monitoring Of Plant Diseases Using Unmanned Aerial Vehicles: A Review, Krishna Neupane, Fulya Baysal-Gurel

Agricultural and Environmental Sciences Faculty Research

Disease diagnosis is one of the major tasks for increasing food production in agriculture. Although precision agriculture (PA) takes less time and provides a more precise application of agricultural activities, the detection of disease using an Unmanned Aerial System (UAS) is a challenging task. Several Unmanned Aerial Vehicles (UAVs) and sensors have been used for this purpose. The UAVs’ platforms and their peripherals have their own limitations in accurately diagnosing plant diseases. Several types of image processing software are available for vignetting and orthorectification. The training and validation of datasets are important characteristics of data analysis. Currently, different algorithms and …


Predicting Transcriptional Responses To Cold Stress Across Plant Species, Xiaoxi Meng, Zhikai Liang, Xiuru Dai, Yang Zhang, Samira Mahboub, Daniel W. Ngu, Rebecca Roston, James Schnable Mar 2021

Predicting Transcriptional Responses To Cold Stress Across Plant Species, Xiaoxi Meng, Zhikai Liang, Xiuru Dai, Yang Zhang, Samira Mahboub, Daniel W. Ngu, Rebecca Roston, James Schnable

Center for Plant Science Innovation: Faculty and Staff Publications

Although genome-sequence assemblies are available for a growing number of plant species, gene-expression responses to stimuli have been cataloged for only a subset of these species. Many genes show altered transcription patterns in response to abiotic stresses. However, orthologous genes in related species often exhibit different responses to a given stress. Accordingly, data on the regulation of gene expression in one species are not reliable predictors of orthologous gene responses in a related species. Here, we trained a supervised classification model to identify genes that transcriptionally respond to cold stress. A model trained with only features calculated directly from genome …