Introduction

Over the past decade, uncrewed aircraft (UA), colloquially referred to as drones, have become increasingly employed in environmental science (Villa et al. 2016; Manfreda et al. 2018). Advances in microprocessors, material development and manufacturing, battery technology, and the miniaturization of electronics and sensors have ushered in small UA (sUA) as a highly capable scientific tool that is both relatively easy to use and affordable. Multirotor UA are able to operate at low speeds, including hover, and are highly maneuverable. Hence, they can provide observations in a continuous manner or along a discontinuous trajectory at deliberately chosen points of interest. Complementing this, fixed-wing UA can cover extensive horizontal and vertical expanses at low altitudes. As a result, and especially with the stability augmentation that is now ubiquitous across this class of aircraft, UA make excellent observational platforms.

The UA’s ability to host both in-situ and remote sensing sensors has increased the breadth of their application in environmental science. Early UA adoption in the environmental sciences has been most prevalent with UA serving as a platform for a variety of remote sensors. Multispectral, hyperspectral, visible light, and thermal infrared cameras have afforded very high spatio-temporal resolution for the investigation of environmental challenges, such as water quality (Arango and Naim 2019; Baek et al. 2019; Becker et al. 2019; Castro et al. 2020; Choo et al. 2018; Kim et al. 2020; McEliece et al. 2020; Olivetti et al. 2020; O’Shea et al. 2020; Shang et al. 2017; Su 2017; Windle and Silsbe 2021; Zeng et al. 2017), harmful algal bloom (HAB) formations (Bunyon et al. 2023; Lyu et al. 2017), environmental restoration efforts (Robinson et al. 2022; White et al. 2020), tree canopy surveys (Krasylenko et al. 2023; Wu et al. 2021), and wildlife monitoring (Brunton et al. 2020; Wijayanto et al. 2023; Witt et al. 2020; Zhang et al. 2020).

Both multirotor and fixed-wing UA make impactful platforms for a variety of in-situ sensors when thoughtful consideration is given to sensor placement. To this point, UA have been used to host complementary sensors to both sample water (Hanlon et al. 2022) and aerosolized particles (Bilyeu et al. 2022) associated with HABs. UA have also provided the means for innovative strategies to detect wildfires outside of the use of cameras (Rjoub, et al. 2023; Wang et al. 2023). Atmospheric scientists have also employed UA hosted in-situ sensors to characterize micrometeorological changes brought about by wind energy (Adkins and Sescu 2017, 2018; Alaoui-Sosse et al. 2022; Li et al. 2023), the urban environment (Adkins et al. 2020, 2023; Laukys et al., 2023) and severe weather outbreaks (Frew et al. 2020; Koch et al. 2018; van den Heever et al. 2021).

The study of aerobiology focuses on biological particles, or bioaerosols, in the atmosphere and their movement over a range of spatial scales (Main 2003). At the landscape scale, aerobiology has important applications in agriculture through the dispersal of plant pathogens (Schmale and Ross 2015); in public health, through predicting exposure to pollen and other allergens (Sierra-Heredia et al. 2018); and in biogeography, such as in understanding the potential for long distance migration via aerial spore dispersal (Gage et al. 1999; Golan and Pringle 2017; Lacey 1996). The use of UA for bioaerosol sampling has been explored (Smith et al. 2015), such as for pollen and fungal spores (Crazzolara et al. 2019; Vélez-Rodríguez et al. 2020). Both multirotor (Vélez-Rodríguez et al. 2020) and fixed-wing (Schmale III et al. 2008) UA have been employed toward this end. However, prior studies used relatively complex samplers or ancillary servomechanisms. This work demonstrates a simple approach to sampling the lower atmosphere for colony-forming units (CFUs) of fungal spores and explores flight parameters that impact sampling effectiveness.

Methods

The design of the spore capture device was primarily driven by the requirement to open and close a Petri dish remotely, to maintain a seal on the dish when samples are not being collected, and to allow for easy swapping of Petri dishes between collection profiles, all while minimizing any impacts on the UA’s flight performance. The design is easily transportable and readily installed with basic tools, facilitating deployment during field campaigns in remote areas.

Apparatus design and hosting

A commercial off‐the‐shelf (COTS) quadcopter-style UA (DJI Inspire II) was used to host the spore collection device. The platform lends itself well to the mission requirements with a payload capacity (710 g) that well exceeds the mass of the capture device (145 g), and offers augmented flight stability, ease of use, and the ability to both hover and execute a pre-defined flight plan autonomously. To simplify development, minimize the size of the apparatus, and keep sample collection straightforward, the collection device was designed to be attached to the UA’s retractable landing gear.

Importantly, the design exploits the UA’s ability to cycle the landing gear remotely to open and close the Petri dish, thus removing the requirement for any sort of ancillary servo and associated command and control link. Using this design strategy, the remote pilot can open the Petri dish by raising the landing gear and securely close the Petri dish by lowering the gear. This strategy ensures that spore samples are not collected until the desired portion of the flight plan, and that contamination of the collection medium does not occur during launch or recovery of the UA. To protect the Petri dish during its opening and closing, each side of the dish is secured to the respective portion of the mounted apparatus by Velcro.

The computer-aided design (CAD) drawing of the apparatus is shown in Fig. 1a. Figure 1b shows the apparatus mounted with the gear fully extended and the Petri dish fully closed. The lefthand portion of the apparatus was attached to the UA by reusing screw holes for the UA’s camera gimbal. These two screws securely mount one side of the apparatus while minimizing any additional material weight and simplifying assembly of the device in the field (Fig. 1c). The attachment of the other side of the apparatus to the main gear was accomplished using a flange with four readily accessible screw holes (Fig. 1a). This second attachment, likewise, made for a simple and lightweight connection point to the UA. With weight being the main driver behind most aircraft design considerations, the collection device was printed with standard polylactic acid (PLA) filament and a honeycomb infill to reduce the overall weight. The fully configured UA is shown ready for takeoff in Fig. 1d.

Fig. 1
figure 1

a CAD model of spore capture device. b Spore capture device hosted on the multirotor UA. c The spore capture apparatus was designed for easy assembly and disassembly in the field with basic tools. d The fully configured UA ready for takeoff with the landing gear fully extended downward and the Petri dish fully closed

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Spore capture trials

A series of exploratory experiments were conducted to test the deployment of the capture device while mounted to the UA and to gain insight into what parameters impact the capturing of spores.

Study area

The experiment was undertaken in an agriculture field located within a humid subtropical climate zone (Daytona Beach, Florida, USA). Figure 2 shows the 31-hectare field where the investigation took place. The field is bound by a combination of woods, composed of both palm and hardwood trees, to the west and south, additional agricultural plots to the north, and wetlands to the east. The topography of the area is generally flat and an interstate highway runs north–south adjacent to the eastern edge of the operational area. The field is used for cattle grazing and is largely composed of pasture grass and was dry over the operational period.

Fig. 2
figure 2

Aerial image of the operational (outlined in red) and surrounding area where measurements were made. Image courtesy of Google Earth

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Mission planning

A suite of 13 flight plans (Supplementary Material Table S1) were created to investigate how exposure time (three treatment levels), orientation of the Petri dish to the prevailing wind (two treatment levels), altitude (four treatment levels), and medium hardness (four treatment levels) impact the number of spores captured. All 13 flights were flown back-to-back over the period of three hours, hence allowing for a quasi steady state assumption to be made for the ambient environment.

The baseline flight plans consisted of horizontal transects defined by either length or time depending on the parameter of interest for the given flight (“dynamic flight” in Fig. 3). All flights were flown at 2.24 m/s (5 mph). Flight plans were constructed so that the UA’s nose always remained orthogonal to the flight path vector of the UA and with the agar side of the Petri dish aligned with the flight path vector. This effectively resulted in the UA flying sideways and the agar side of the Petri dish always facing the direction of travel.

Fig. 3
figure 3

Test parameters for spore capture investigation. Parameter levels were held at the indicated baselines when testing over a given parameter range. 1Altitude and orientation to wind did not change for ground-level reference. 2Wind direction was not standardized except in the orientation to wind trials, which had a modified flight protocol. More details about flight protocols are found in Supplementary Material Table S1

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In addition to the baseline flight plans, two reference samples were collected simultaneously with each flight. First, a reference UA was flown in a stationary hover adjacent to the dynamic flight plan of the first UA. The hovering UA hosted a similar Petri dish, with the same open and shut times, as the dynamic UA. Second, an additional Petri dish was set up at ground level, adjacent to the operational area. This Petri dish was housed in an open-top box and placed on a tabletop elevated 1 m above the ground. The test parameters are shown in Fig. 3. A full test matrix with details of each UA’s flight plan and the objective for each flight is available in the Supplementary Material Table S1.

The data collection flights required pre-planned missions for precise control of the aircraft during the flight. These missions were built and executed in the DJI Ground Station Pro (GSPro) iOS application. DJI GSPro allows for the creation of pre-planned GPS waypoint flights, which are autonomously executed on-site. GSPro also allows for control of the aircraft’s flight speed, orientation, direction, rotation speed, and altitude. The use of this software ensured a more consistent approach across all data collection flights.

Sampling flight execution

The spore capture device accommodated Petri dishes with a 90 mm diameter and 15 mm depth. Dichloran Rose-Bengal Chloramphenicol (DRBC) was used as a collection and growth medium in the Petri dishes, as it is commonly used for impaction air samplers and is effective at selectively isolating airborne fungal spores without bacterial growth (Mentese et al. 2017). The loading of the Petri dish onto the UA was undertaken carefully so that the dish was never opened and exposed to the ambient environment before data collection began.

After loading the Petri dish, pre-launch checklists were conducted and the UA was launched on the pre-programmed mission. The landing gear legs remained extended throughout ascent to the mission’s first waypoint. Once the UA arrived at the first mission waypoint, it autonomously rotated to place the nose orthogonal to the ensuing flight path vector and retracted its gear, hence opening the Petri dish. During the data collection phase, the UA translated autonomously between the two previously defined waypoints. At the conclusion of the data collection mission, the landing gear was extended, hence closing the Petri dish. Following recovery of the UA, the Petri dish was promptly removed from the UA and sealed with tape.

Colony counting

Petri dishes were kept sealed and incubated in a temperature-controlled environment of 23 °C for 82 h. Colony-forming units (CFUs) were quantified by counting the number of discrete fungal colonies on each dish after the incubation period.

Statistical analysis

Petri dish colony counts for each experiment were fit to separate generalized linear mixed models for each experiment. Models assumed a Poisson distribution with a log link. All models also included an intercept offset random effect that grouped concurrent samples (i.e., the concurrent ground reference, hovering UA reference, and dynamic UA flight) to account for shared variability due to environmental conditions or other outside factors (see Equation S1 Supplementary Material). An interaction effect (flight x treatment) was included to fit separate treatment effects for dynamic flight samples, hovering flight reference samples, and ground reference samples. Analyses were conducted with the statistical software R (R Core Team 2022). Contrasts between the dynamic flight and hover flight and ground references were calculated from the model results using the “emmeans” package (Lenth 2022). A full description of statistical packages and outputs is given in the Supplementary Material.

Results

One set of trials was conducted in August 2022 and a second set was conducted in November 2022, each spanning from the middle to late morning of the day. On each of these days, high pressure dominated the region and produced partly cloudy skies. August temperatures ranged between 31 and 33 °C, with relative humidity ranging from 52 to 66%; November temperatures ranged between 22 and 25 °C, with relative humidity ranging between 70 and 75%. Surface winds on each day were from the southwest between 2 and 4 m/s.

The experiments in Supplemental Table S1 were replicated in the August and November trials, except for the growth medium trials, which were only conducted in November. In total, 66 Petri dishes were collected, representing 22 trials. Each trial included the dynamic UA flight with simultaneous collection of ground and hovering UA reference samples. Supplementary Fig. S1 shows an example set of Petri dish results. Two ground reference dishes had to be excluded from analysis because they had abnormally high colony counts (> 70 colonies), likely due to contamination.

The mean colony counts for the dynamic flights and the simultaneous reference samples across all experiments were estimated using a mixed-effects model with experiment and trial groups as random effects (Supplemental Table S2). Ground reference Petri dishes across all experiments had an average of 6.0 colonies, with a 95% confidence interval (CI) of 3.8–9.4. Hover UA flights collected a mean of 13.6 colonies (CI 8.9–21.5). Dynamic flights collected a mean of 20.2 colonies (CI 13.1–31.2).The dynamic flight and reference hover flight colony counts were on average 3.38 and 2.32 times greater than the ground reference (p < 0.001). Further, dynamic flight colony counts were greater than that of the hover reference by 1.46 times (p < 0.001). More information on post-hoc marginal effects tests is found in Supplementary Table S3.

Flight time experiment results suggest that UA-mounted Petri dishes collected more CFUs than the ground reference, with an increasing trend with time (Fig. 4a). However, these effects were not significantly different from zero (ɑ = 0.05), though the trend was marginally significant for hover flights (p = 0.096). Contrasts between trends were not significantly different (Supplemental Table S5).

Fig. 4
figure 4

Modeled results based on experiments varying Petri dish sampling parameters compared between a reference Petri dish at ground level (exposed for the same duration as flights), a reference Petri dish on a hovering flight, and a Petri dish on a dynamic flight. Experiments varied flight/exposure time (a), orientation with respect to wind (b), flight altitude (c), and % agar in the Petri dish medium (d). Note that altitude values for ground reference samples in (c) refer to the altitude of the paired flights taken simultaneously with the ground reference; all ground samples were taken at a height of 1.5 m

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With the Petri dish oriented away from wind, UA hover and dynamic flight results were not significantly different from the ground reference. When the Petri dish was oriented towards the wind, the dynamic UA flight collected more CFUs, though the model could only distinguish a marginally significant difference (p = 0.088) from concurrent ground references (Supplemental Table S7, Fig. 4b).

Based on model-estimated 95% confidence intervals (Fig. 4c), more CFUs were collected at lower altitudes by the UA-mounted Petri dishes compared to the ground reference samples taken at the same time. At the highest altitude, UA and reference Petri dishes were no longer significantly different. Model trends could not be significantly distinguished from zero, but estimated trends contrasted significantly between dynamic flight, hover reference flight, and ground reference (p < 0.01, Supplemental Table S9).

The effect of agar concentration was modeled logarithmically (Fig. 4d). The model fit increasing trends with higher % agar for the hovering flight and ground reference samples, which were significant (p = 0.042) and marginally significant (p = 0.088), respectively (Supplemental Table S11). Colony counts in dynamic flight Petri dishes were generally high across all concentrations without a significant trend, and contrasts between dynamic flight and reference trends were also not significant.

Discussion

Understanding the movement of biological agents in the atmosphere has important implications in landscape-scale studies in biogeography, agricultural pathogens, and human allergens (Main 2003). Multirotor UA collection of bioaerosols is a potent method of sample collection in such aerobiological studies. The apparatus presented in this short communication is low-cost and simple to operate, which could lower barriers to entry in research and facilitates replicated sampling over broad scales. A range of parameters were explored to determine possible protocol effects on sampling effectiveness. Generally, the results of these trials demonstrated that UA flights are successful at sampling colony-forming fungal spores from the lower atmosphere, as compared to the ground-level and hovering flight references, though more testing is required to better determine how these and other effects impact bioaerosol collection.

The approach in this preliminary study has some potential advantages over previous setups. The necessity to maintain consistent altitude, speed, and sampling pattern can be challenging for fixed wing aircraft (Schmale III et al. 2008) but these parameters can be controlled more precisely with a multirotor UA. Further, by using the UA landing gear to open and close the Petri dish, the design eliminates the remotely controlled servo devices in prior designs (Maldondo-Ramirez et al. 2005; Schmale III et al. 2008; Keller and Shields 2014; Vélez-Rodríguez et al. 2020). This reduces the weight and cost of the sampling apparatus and simplifies communication. Aside from Petri dishes, the only materials required were 3D printing resin and tank (FormLabs, Boston, MA), Velcro tape, and four M3 nuts and bolts, totaling approximately 70 USD.

Even with a simpler approach, this study found results comparable to those of other UA-based collection methods that also used mounted Petri dishes. For example, Vélez-Rodríguez et al. (2020) recovered between 15 and 115 CFUs on Petri dishes mounted to a quadcopter-style UA flown on five-minute flights at an altitude of 120 m in Puerto Rico. Earlier studies using Petri dishes mounted on fixed-wing UA have recovered per-plate averages ranging from three to 200 CFU during 15-min flights, depending on time of day and environmental conditions (Maldondo-Ramirez et al. 2005; Keller and Shields 2014).

The experiments of this study inferred spore capture efficiency relatively, by comparing the dynamic flight to hovering and ground references. Previous studies using Petri dishes mounted on fixed-wing UA have established efficiency models for those samplers based on theory, allowing the calculation of CFU concentrations, in part from the volume of air sampled (Aylor et al. 2006). These models assume that the volume of sampled air is a function of the area of the Petri dish and the UA flight speed and sampling duration. However, with this design and similar configurations using multirotor UA (Vélez-Rodríguez et al. 2020), the total volume sampled may be influenced by additional airflow dynamics that could differ between dynamic and hovering flights (Crazzolara et al. 2019). Further, capture efficiency is influenced by the Stokes’ number of the airborne particles (Aylor et al. 2006), which increases as a function of a particle’s diameter, density, and velocity, and determines whether it is deposited from the airstream (Mainelis 2020). More research is needed to understand these effects on spore capture (Fig. 5).

Fig. 5
figure 5

Hypothesized mechanisms affecting bioaerosol collection based on trial results. These include competing sources of airflow (a), height of sample collection (b), and particle size and Petri dish collection medium (c)

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As with any other research tool, an understanding of limitations is necessary for effective application. The results of the UA flight experiments and prior work by others suggest some hypotheses on how different protocol parameters impact collection (Fig. 5), as summarized below.

Effects of competing airflow (Fig. 5a)

Different sources of airflow may predominate depending on the flight of the multirotor UA. Stationary hover flights expose the Petri dish to air drawn down through the rotors from above the UA and recirculate it with smaller portions of entrained air adjacent to the UA. Dynamic flights better offset the recirculated air from above the UA with the volume of air along the flight path, as rotor-induced flow is advected away from the UA. Dynamic flights may therefore sample the horizontal transect of the flight path, while hovering flights may sample the vertical column of air above the UA. Depending on the relative orientation of the Petri dish, wind could further interact with these competing forces by mixing particles from upwind, as demonstrated in smoke experiments by Crazzolara et al. (2019). Under the trial conditions of this study, windspeed may not have been strong enough to overcome rotor flow of the hovering UA but may have increased the variability in the results for the dynamic UA flight (Fig. 4b). Wind direction was not accounted for in other experiments and may have also contributed to observed variability.

Effect of flight altitude (Fig. 5b)

The number of CFUs collected increased closer to the ground (Fig. 4c), which generally reflects reported altitude distributions of fungal spores in other studies (Li et al. 2010). However, the density and diversity of bioaerosols may be influenced by seasonal and meteorological factors that are still being understood (Rodríguez-Rajo et al. 2005; Li et al. 2010). Nevertheless, multirotor UA-based aerobiological sampling offers an advantage over previous methods based on conventional fixed-wing aircraft. Multirotor UA can operate at lower altitudes that are impractical and unsafe for crewed aircraft and can maintain a consistent altitude during sampling, which is important for accurate models of bioaerosol transport (Schmale III et al. 2008).

Spore size and Petri dish medium (Fig. 5c)

The physical and biological characteristics of the spores can influence collection efficiency. The colonies cultured from the experiments suggest that most of the captured spores were molds such as the genus Penicillium (Supplemental Fig. S1), which typically have aerodynamic diameters of 1–10 um (Yamamoto et al. 2012). However, future work should determine the capture efficiency of this setup as related to spore size, for example through comparison with multirotor-based collection methods that have established efficiency, such as with a more sophisticated impactor sampler (Crazzolara et al. 2019).

Petri dishes with higher agar content tended to result in more CFUs (Fig. 4d). In contrast to the trends reported here, Juozaitis et al. (1994) found that higher agar concentration decreased collection efficiency, due to lower medium stickiness. On the other hand, increased agar concentration has also been found to promote fungal growth through hyphae and spore production (Reponen et al. 1998; Hotz et al. 2023). The possible counteracting effects of medium stickiness and colony growth promotion should be considered when developing sampling protocols that involve culturing colonies, though this effect should be investigated further.

However, if culturing on the collection medium is not part of the protocol (e.g., non-viable spores or pollen sampling), then alternative methods of quantification to colony counting are needed, such as flow cytometry or qPCR. Moreover, these methods of sampling are compatible with collecting spores and analysis of communities of unculturable fungi, such as rust fungi, using metabarcoding approaches with DNA sequencing. For example, using dissolvable matrix such as gellan gum could allow all spores to be collected from the surface of the Petri dishes.

These possible mechanisms should inform the planning of collection flight protocols and interpreting the resulting samples, though additional testing would be beneficial for making more robust recommendations on the importance of these effects. Nevertheless, given the accessible design and ease of application of the collection apparatus described here, this low-cost UA-based aerobiological sampling method could facilitate broader investigations into landscape-scale dynamics of bioaerosols.