BACKGROUND: Bioaerosols, which include airborne bacteria, are a growing concern for public health, especially near intensive farming operations that generate high concentrations of microorganisms. Intensive farms, such as those for cattle, can release potentially pathogenic bacteria into the air, posing risks to nearby communities and farmworkers. Traditional sampling methods are often limited, as they require stationary collection points and can miss key information about how these bioaer- osols disperse. To address this issue, this study introduces a proof-of-concept drone-based system designed to monitor and sample airborne bacteria near intensive farms. RESULTS: The drone, equipped with a sampling device, was used to sample three different points near a livestock production farm. DNA extraction, which was also traditionally a limitation in microbial airborne molecular biology, was achieved after only 10 min of ying by employing an ad hoc developed DNA extraction protocol coupled with a petroleum trap and virus DNA extraction kit. The results showed that DNA was successfully extracted, and reads were checked for quality. The primary bacte- rial genera found across all sites are Acinetobacter and Bacillus. While Acinetobacter includes both commensal and mastitis- causing strains, Bacillus species such as Bacillus subtilis serve as probiotics in animal feed. Probiotic genera Lactobacillus and Bi dobacterium were also detected, alongside potentially pathogenic Staphylococcus, highlighting hygiene concerns. Unex- pected genera, including cyanobacteria from nearby water bodies, and Microvirga, typically found in arid, metal-rich soils, sug- gest environmental in uences or contaminants. CONCLUSION: Further development of this system can provide an early warning mechanism by tracking the presence and movement of harmful microorganisms in a 3D space surrounding the farms, allowing for safety and public health applications.

A drone-based system for sampling airborne bacteria near intensive farms / Marta Nerini,Marco Merlini,Sonia Renzi,Aldo D'Alessandro,Duccio Cavalieri,Giuseppe Rossi, Massimiliano Marvasi. - In: JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE. - ISSN 1097-0010. - STAMPA. - (2025), pp. 0-0. [10.1002/jsfa.70001]

A drone-based system for sampling airborne bacteria near intensive farms

Marta Nerini;Marco Merlini;Sonia Renzi;Aldo D'Alessandro;Duccio Cavalieri;Giuseppe Rossi;Massimiliano Marvasi
2025

Abstract

BACKGROUND: Bioaerosols, which include airborne bacteria, are a growing concern for public health, especially near intensive farming operations that generate high concentrations of microorganisms. Intensive farms, such as those for cattle, can release potentially pathogenic bacteria into the air, posing risks to nearby communities and farmworkers. Traditional sampling methods are often limited, as they require stationary collection points and can miss key information about how these bioaer- osols disperse. To address this issue, this study introduces a proof-of-concept drone-based system designed to monitor and sample airborne bacteria near intensive farms. RESULTS: The drone, equipped with a sampling device, was used to sample three different points near a livestock production farm. DNA extraction, which was also traditionally a limitation in microbial airborne molecular biology, was achieved after only 10 min of ying by employing an ad hoc developed DNA extraction protocol coupled with a petroleum trap and virus DNA extraction kit. The results showed that DNA was successfully extracted, and reads were checked for quality. The primary bacte- rial genera found across all sites are Acinetobacter and Bacillus. While Acinetobacter includes both commensal and mastitis- causing strains, Bacillus species such as Bacillus subtilis serve as probiotics in animal feed. Probiotic genera Lactobacillus and Bi dobacterium were also detected, alongside potentially pathogenic Staphylococcus, highlighting hygiene concerns. Unex- pected genera, including cyanobacteria from nearby water bodies, and Microvirga, typically found in arid, metal-rich soils, sug- gest environmental in uences or contaminants. CONCLUSION: Further development of this system can provide an early warning mechanism by tracking the presence and movement of harmful microorganisms in a 3D space surrounding the farms, allowing for safety and public health applications.
2025
0
0
Marta Nerini,Marco Merlini,Sonia Renzi,Aldo D'Alessandro,Duccio Cavalieri,Giuseppe Rossi, Massimiliano Marvasi
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1427953
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