Efficacy of PCR-bassed techniqes and remote sensing technology for detecting potato brown rot infection caused by R. solanacearum

Abstract

Bacterial wilt of potatoes (Solanum tuberosum) caused by Ralstonia solanacearum phylotype II sequevar I (race 3 biovar 2), is one of the most serious diseases of potatoes. This study aimed to detect such deteriorations through the remotely sensed data. In this regard, naturally infested potato fields at Abo Alkhawi, Al Tayareya and Om Saber villages at Behera governorate, Egypt, were used for selective isolation of R. solanacearum. On Semi Selective South Africa (SMSA) medium, 30 isolates were randomly screened and tested by immunofluorescence antibody staining (IFAS) and confirmed biologically by tomato plantlets (cv. Pinto) reaction. All isolates showed positive results with Real-time PCR. Based on the phylotype specific multiplex (Pmx)-PCR data, all isolates in concern were R. solanacearum and affiliated to phylotype II as 372-bp amplicon. Spectral indices were applied on the Landsat 8 and RapidEye satellite images acquired in January and April 2019 including Normalized Difference Moisture Index (NDMI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Salinity Index (NDSI) and Modified Chlorophyll Absorption Ratio Index (MCARI). Results from the remote sensing analyses showed medium to relatively high salinity and moisture content of soils concerned. Moreover, plants chlorophyll levels are in medium levels which is not typical to condition associated with usual circumstances. Further investigation, in a greater academic depth, are needed for pathological field surveys.

Identificação aprimorada de seringais infestados por fitonematoides no município de Prata, MG, por sensoriamento remoto

“…O uso do NDVI como ferramenta para diagnosticar a presença e severidade de infecções causadas por nematoides tem sido estudado em diversas culturas, inclusive na seringueira (MARTINS et al, 2017;DUARTE et al, 2019;BALABEL et al, 2020;GROOVER;LAWRENCE, 2020;LEMES et al, 2020;VIERA-TORRES et al, 2020) Em estudo recente, Lemes et al (2020), já apresentavam resultados demonstrando que o sensoriamento remoto seria capaz de diferenciar um seringal não infestado de um infestado pelo nematoide de galha M. exigua, em especial por meio do uso do índice NDVI.…”