Xf-Rovim. A Field Robot to Detect Olive Trees Infected by Xylella Fastidiosa Using Proximal Sensing

Abstract

The use of remote sensing to map the distribution of plant diseases has evolved considerably over the last three decades and can be performed at different scales, depending on the area to be monitored, as well as the spatial and spectral resolution required. This work describes the development of a small low-cost field robot (Remotely Operated Vehicle for Infection Monitoring in orchards, XF-ROVIM), which is intended to be a flexible solution for early detection of Xylella fastidiosa (X. fastidiosa) in olive groves at plant to leaf level. The robot is remotely driven and fitted with different sensing equipment to capture thermal, spectral and structural information about the plants. Taking into account the height of the olive trees inspected, the design includes a platform that can raise the cameras to adapt the height of the sensors to a maximum of 200 cm. The robot was tested in an olive grove (4 ha) potentially infected by X. fastidiosa in the region of Apulia, southern Italy. The tests were focused on investigating the reliability of the mechanical and electronic solutions developed as well as the capability of the sensors to obtain accurate data. The four sides of all trees in the crop were inspected by travelling along the rows in both directions, showing that it could be easily adaptable to other crops. XF-ROVIM was capable of inspecting the whole field continuously, capturing geolocated spectral information and the structure of the trees for later comparison with the in situ observations.

A Lack of “Environmental Earth Data” at the Microhabitat Scale Impacts Efforts to Control Invasive Arthropods That Vector Pathogens

“…Although weather radars have detected mass migrations of invasive insects [17], as yet remotely sensed data cannot directly characterize IAVP geographical distributions. There are promising proximal sensing methods that use reflectance data from cameras that can detect and differentiate between multiple fruit fly species, including those that vector crop pathogens [18] (see also [19] for an interesting application of proximal sensing of an invasive pathogenic plant bacterium). However, mapping IAVP distribution in real-time is often less desirable than preempting the potential geographic distribution, as surveillance and control are more efficient if implemented prior to the establishment of a species [11,12,20].…”

Robot de campo para detectar enfermedades en cultivos hortícolas mediante imágenes multiespectrales

“…Por otro lado, la reducción de precios y la miniaturización hacen que los sistemas aéreos no tripulados (UAV) sean cada vez más populares para una rápida monitorización a nivel de cultivo en cualquier momento. A nivel de hoja, la información espectral se puede recopilar con una alta resolución espacio-temporal utilizando sensores manuales o montados en vehículos agrícolas [4]. Este trabajo tiene como objetivo ayudar en la detección temprana de cultivos infectados por CaLsol a nivel de planta y cultivo, utilizando sensores de detección proximal de alta resolución montados en un robot eléctrico diseñado y desarrollado a medida para este fin.…”

XF-ROVIM, un robot para la detección de enfermedades en campo mediante teledetección. Aplicación a la detección de Xylella fastidiosa

“…Este trabajo presenta el desarrollo de un robot de campo, XF-ROVIM [5], que incorpora equipos para el sensado remoto. Este robot se está utilizando para la detección temprana de Xf y se ha probado en campos de olivos potencialmente infectados por Xf en la región de Apulia (Italia).…”