Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1-the summer 2015 and winter 2016 growing seasons-of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project's goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first and most comprehensive project of its kind to date, these lessons are particularly salient to researchers embarking on agricultural research with UAVs

Dissociation of amyloid fibrils of α-synuclein and transthyretin by pressure reveals their reversible nature and the formation of water-excluded cavities

Protein misfolding and aggregation have been linked to several human diseases, including Alzheimer's disease, Parkinson's disease, and systemic amyloidosis, by mechanisms that are not yet completely understood. The hallmark of most of these diseases is the formation of highly ordered and β-sheet-rich aggregates referred to as amyloid fibrils. Fibril formation by WT transthyretin (TTR) or TTR variants has been linked to the etiology of systemic amyloidosis and familial amyloid polyneuropathy, respectively. Similarly, amyloid fibril formation by α-synuclein (α-syn) has been linked to neurodegeneration in Parkinson's disease, a movement disorder characterized by selective degeneration of dopaminergic neurons in the substantia nigra. Here we show that consecutive cycles of compression–decompression under aggregating conditions lead to reversible dissociation of TTR and α-syn fibrils. The high sensitivity of amyloid fibrils toward high hydrostatic pressure (HHP) indicates the existence of packing defects in the fibril core. In addition, through the use of HHP we are able to detect differences in stability between fibrils formed from WT TTR and the familial amyloidotic polyneuropathy-associated variant V30M. The fibrils formed by WT α-syn were less susceptible to pressure denaturation than the Parkinson's disease-linked variants, A30P and A53T. This finding implies that fibrils of α-syn formed from the variants would be more easily dissolved into small oligomers by the cellular machinery. This result has physiological importance in light of the current view that the pathogenic species are the small aggregates rather the mature fibrils. Finally, the HHP-induced formation of fibrils from TTR is relatively fast (≈60 min), a quality that allows screening of antiamyloidogenic drugs

Gartner hype cycle cartoon of the subjective value and development stage of various technologies discussed here.

<p>Most of the base technologies are mature and productive, but the integration of all of these technologies is new and likely over-hyped.</p

Sensor configuration used in this project.

<p>Sensor configuration used in this project.</p