Image Phenotyping of Spring Barley ( L.) RIL Population Under Drought: Selection of Traits and Biological Interpretation.

Image-based phenotyping is a non-invasive method that permits the dynamic evaluation of plant features during growth, which is especially important for understanding plant adaptation and temporal dynamics of responses to environmental cues such as water deficit or drought. The aim of the present study was to use high-throughput imaging in order to assess the variation and dynamics of growth and development during drought in a spring barley population and to investigate associations between traits measured in time and yield-related traits measured after harvesting. Plant material covered recombinant inbred line population derived from a cross between European and Syrian cultivars.

Mapping of quantitative trait loci for traits linked to fusarium head blight in barley.

Fusarium head blight (FHB) is a devastating disease occurring in small grain cereals worldwide. The disease results in the reduction of grain yield, and mycotoxins accumulated in grain are also harmful to both humans and animals. It has been reported that response to pathogen infection may be associated with the morphological and developmental traits of the host plant, e.

Chlorophyll Fluorescence Parameters of Hulled and Hull-less Barley ( L.) DH Lines Inoculated with .

Barley worldwide is affected seriously by Fusarium seedling blight (FSB) and Fusarium head blight (FHB) diseases caused by the species The objective of this study was to facilitate the resistance of hulled and hull-less barley at different growth stages to according to direct parameters: disease rating (DR), fresh weight of leaves and roots, kernel weight per spike, kernel number per spike, plump kernels, and indirect parameters - chlorophyll fluorescence (CF). Plate assay, greenhouse and field tests were performed on 30 spring barley doubled haploid (DH) lines and their parents infected with . Direct parameters proved that hulled genotypes show less symptoms.

A Chronically Implantable Neural Coprocessor for Investigating the Treatment of Neurological Disorders.

Developing new tools to better understand disorders of the nervous system, with a goal to more effectively treat them, is an active area of bioelectronic medicine research. Future tools must be flexible and configurable, given the evolving understanding of both neuromodulation mechanisms and how to configure a system for optimal clinical outcomes. We describe a system, the Summit RC+S "neural coprocessor," that attempts to bring the capability and flexibility of a microprocessor to a prosthesis embedded within the nervous system.

Integrating Brain Implants With Local and Distributed Computing Devices: A Next Generation Epilepsy Management System.

Brain stimulation has emerged as an effective treatment for a wide range of neurological and psychiatric diseases. Parkinson's disease, epilepsy, and essential tremor have FDA indications for electrical brain stimulation using intracranially implanted electrodes. Interfacing implantable brain devices with local and cloud computing resources have the potential to improve electrical stimulation efficacy, disease tracking, and management.