Plant Phenomics Phridays: Recent Episodes
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Plant Phenomics Phridays is hosted by The Midwest Big Data Hub Digital Agriculture Spoke and the University of Nebraska Quantitative Life Sciences Initiative. This is a continuation of the series hosted by Iowa State University over the summer (http://www.bcb.iastate.edu/plant-phenomics-phridays-seminar-3). In this series of weekly seminars, challenges and opportunities in the plant sciences will be addressed using novel approaches from diverse disciplines. Speakers in this seminar series include statisticians, biologists, data scientists, and engineers.
Areas of Research and Professional Interest: Generation, analysis and management of agricultural information/data Application of UAS/drone and aerial imagery in agriculture Prediction and management of crop abiotic and biotic stresses Extension Interests: Promote adoption of emerging agricultural technologies Improve understanding and utility of agricultural big data
Research Interests: Unfavorable environmental conditions such as drought, high and low temperature stress, salinity, and flooding result in heavy crop yield losses in the U.S. and worldwide. These stressful conditions are increasingly associated with a shift in agriculture to marginal lands and erratic climatic changes. Dr. Walia's research interest is in understanding how plants adapt to these environmental stresses. I am particularly interested in the physiological and molecular characterization of crop responses to drought, heat and salt stress. Plant responses to stress depend on the developmental stage at which the stressful conditions arise.
Research in the lab focuses on stress tolerance during developmental stages that are particularly sensitive to abiotic stresses resulting in yield and biomass losses, using genomics, biochemical, computational and physiological approaches to elucidate the mechanisms involved in abiotic stress tolerance in cereals such as wheat, maize, and rice among others. The overall research goal is to discover genes and genetic variants that can be used to improve crop performance in sub-optimal growing conditions.
Dr. Qiu's research interest is mainly on high-dimensional statistical inference and its application in genetic analysis with particularly focus on testing and estimating large covariance matrices, testing sparse and weak treatment effects among large amounts of genes, and multi-group classification under high dimensionality. Dr. Xu's research interests include non-parametric and semi-parametric statistical methods, functional data analysis, survival analysis, measurement error, etc.
"Dr. Xu's current research interest is on machine learning and its applications in agriculture and biology especially in plant image phenotyping, imaging genetics and integrative data analysis".
Research Interests: Plant metabolic engineering Vitamin C metabolism Plant stress tolerance Phytoremediation Plant high throughput phenotyping
Yufeng Ge, Biological Systems Engineering, University of Nebraska: Areas of Research and Professional Interest Sensor-based plant phenotyping Optoelectronic sensor development in agriculture VIS/NIR/MIR Spectroscopy Agricultural remote sensing and image analysis Precision agriculture and spatial statistics Teaching Interests Measurement and control in agriculture Proximal and remote sensing/Spectroscopy Optoelectronic sensor design
James Schnable, Agronomy & Horticulture, University of Nebraska-Lincoln: Area of Focus Computational Biology Research Interests Cross-species functional genomics High throughput phenotyping