737 Statements and Declarations 738 Data and code availability 739 All sampling data, modeling code, and simulation results are made available in the 740 Virginia Tech Data repository: 741 https://figshare.com/s/54a308163b60865d55bf. 742 Competing interests 743 The authors have no competing interests to declare. 744 Funding 745 This work is supported in part by the Biotechnology Risk Assessment Program, project 746 award no. 2019-33522-29989, from the U.S. Department of Agriculture’s National 747 Institute of Food and Agriculture. 748 References 749 Adamov
Open resource ↗figshare · pdf-layout-page:28 lines:1-46Paper record
From Field to Sky: Measurement and Modeling of Transgenic Switchgrass Pollen Dispersal in the Atmosphere
9 Mar 2026 · 10.21203/rs.3.rs-8768887/v1
Abstract
Abstract Accurate tracking and measurement of pollen dispersal in the atmosphere are essential for assessing cross-pollination risks, particularly in the case of genetically engineered (GE) crops. We conducted a series of unique release-recapture field studies with GE switchgrass in Oliver Springs, Tennessee, USA. Two hundred transgenic switchgrass plants ({\it Panicum virgatum L.} `Performer') were planted at the center of a clear-cut field, with one block of 100 plants expressing orange fluorescent protein (OFP) under a maize ubiquitin promoter (PvUBI1) and another block of 100 plants expressing OFP driven by a maize pollen-specific promoter (Zm13). Pollen was sampled from the atmosphere using fixed (ground-based) and mobile (drone-based) sampling devices at different distances from the source field, with Lagrangian Stochastic dispersal simulations run for sampling periods using high-resolution wind measurements. The pollen emission rate was estimated by combining simulated and measured pollen concentrations, and strong diurnal trends were observed. Diurnal emission rate trends were positively correlated with wind speed, temperature, and vapor pressure deficit, while negatively correlated with relative humidity. In low-wind meandering conditions, incorporating changing wind direction into the dispersal modeling improved pollen emission rate estimation and model-measurement comparisons. This study assesses the effectiveness of high and low volume pollen samplers in relation to source strength up to 1 km from the source, enhancing understanding of pollen measurement techniques. Additionally, it is a proof-of-concept for drone-based pollen sampling and GMO pollen tracking using fluorescence measurements. Results from our experiments have significant implications for cross-pollination risk assessment, prediction, and management of airborne allergens.
Code and data availability
The authors state that all sampling data, modeling code, and simulation results from this switchgrass pollen dispersal study are publicly available in a Virginia Tech figshare repository. The GitHub 3D-printing files are cited prior work (Powers et al. 2018), not a paper-specific asset.
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