Speaker
Description
Plasma agriculture exploits low-temperature plasmas to generate Reactive Oxygen and Nitrogen Species (RONS) that enhance seed germination [1, 2], stimulate plant growth [3], improve post-harvest preservation [4, 5], and reduce pesticide residues [5]. Large-scale deployment requires quantitative understanding and control of plasma-driven reactive chemistry across gas and liquid phases, a demand reinforced by the growing interest in Plasma-Activated Water (PAW) [6].
This calls for spatially and temporally resolved diagnostics that link discharge physics, reactive species production, transport and gas–liquid transfer. We present a multi-diagnostic framework for custom-made atmospheric-pressure dielectric barrier discharge (DBD) reactors operating in ambient air for agricultural applications.
Optical Emission Spectroscopy (OES) monitored discharge dynamics. The N2 FNS/SPS intensity ratio served as an indicator of the reduced electric field E/N, correlating operating conditions with RONS production regimes. Electric Field Induced Second Harmonic generation (EFISH) provided non-intrusive, time- and space-resolved measurement of the electric field in the active plasma region, giving an independent validation of the E/N trends inferred from OES and linking discharge electrical properties to reactive species generation.
Laser-Induced Fluorescence tracked NO and OH. The rapid decay of OH marks the active plasma region. Absolute NO concentrations were obtained, and the spatial profiles reveal the balance between production, transport and loss. Raman spectroscopy was assessed as a label-free, multi-species diagnostic for NO₃⁻, NO₂⁻ and H₂O₂, the key RONS in PAW. Colorimetric assays validated the Raman results, showing monotonic increases of all species with treatment time and concurrent acidification. FT-IR spectroscopy provided complementary gas-phase analysis, confirming nitrogen oxides and other long-lived species in the afterglow and effluent gases.
Together, these diagnostics connect discharge physics to application-relevant chemistry and provide a basis for reactor optimization, scale-up and predictive control of plasma treatments.
References
[1] Aceto D. et al., 2024, Front. Phys. 12, 1455481;
[2] Ambrico P.F. et al., 2017, J. Phys. D 50, 305401;
[3] Aceto D. et al., 2024, Front. Phys. 12, 1399910;
[4] Rotondo P.R. et al., 2025, Sci. Rep. 15, 5536;
[5] Aceto D. et al., 2025, Chem. Biol. Technol. Agric. 12, 151;
[6] Thirumdas R. et al., 2018, Trends in Food Science & Technology 77, 21-31.