Numerical Estimation of Agricultural Raised Bed Microwave Disinfection. Issue 10 (4th October 2018)

• Record Type: Journal Article
• Authors: Casu, Sergio; Fanti, Alessandro; Lodi, Matteo Bruno; Spanu, Michele; Desogus, Francesco; Mazzarella, Giuseppe
• Is Part Of: Radio science. Volume 53:Issue 10(2018)
• Page Start: 1176
• Page End: 1186
• Publication Date: 2018-10-04
• Subjects: bioagriculture -- microwave disinfection -- pest control -- nonlinear FDTD -- microwave heating -- dielectric soil properties; Radio meteorology -- Periodicals; Radio wave propagation -- Periodicals; 621.38405
• DOI: 10.1029/2018RS006539
• Languages: English
• ISSNs: 0048-6604

Abstract

Abstract: The use of electromagnetic fields to solve issues related to agriculture is an interesting, cost‐effective, and eco‐friendly possibility to be explored. One of the most promising applications is the disinfection of soils obtained by microwave‐induced heating. This work deals with the nonlinear computational modeling of such microwave heating of soils in metal raised bed cultivations within a greenhouse. By modeling the dielectric properties of soil, in terms of composition, moisture content, and actual temperature, and accounting for the exact thermal and electromagnetic conditions in raised beds inside the greenhouse, several realistic and nonlinear multiphysics simulations were carried out. The disinfection is directed to fungi, such as Sclerotium rolfsii, and weeds, for example, ryegrass and fleabane. The effectiveness of the proposed procedure is quantified and critically discussed exploiting analytical thermal death kinetics of soilborne plant pathogens and compared to the solarization technique. Key Points: A nonlinear numerical model to investigate the feasibility of employing microwave to thermally inactivate soil pathogens is presented Propagation in agricultural raised beds is described using transmission‐line representation and temperature dependence of soil dielectric properties is taken into account Death kinetics of fungi Sclerotium rolfsii is quantified from the calculated spatio‐temporal temperature distribution for different kinds of soil