ABSTRACT
Tobacco (Nicotiana tabacum L.) is an important industrial crop from the Solanaceae family cultivated for its leaves in approximately 100 countries worldwide. In South Africa (SA), tobacco is grown in five of its nine provinces: Limpopo, North West, Western Cape, Eastern Cape, and Mpumalanga. The producer price for unmanufactured tobacco is approximately US$3570/ton annually (FAO, 2021). Emerging and recurrent plant viruses such as tomato spotted wilt orthortospovirus (TSWV) have seriously affected tobacco production yield and quality. Between November 2018 to April 2019 growing season, large thrips (order Thysanoptera) populations were observed in tobacco fields throughout South Africa's major tobacco-growing areas, and plants were showing severe necrosis, yellowing, stunted growth, ringspot, and leaf curling symptoms, which are usually associated with plant virus infections. The disease incidence was estimated at 30%, as per visual observations. Twenty-two symptomatic leaf tissue samples were collected from tobacco farms in Limpopo, Northwest, and Western cape provinces. Samples were initially screened using the double-antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA) with LOEWE®Fast Kit (LOEWE®, Germany), which detectsTSWV, groundnut ringspot orthotospovirus (GRSV), and tomato chlorotic spot orthotospovirus (TCSV). Nineteen of these samples tested positive for orthortospoviruses. Subsequently, a reverse transcription-polymerase chain reaction was performed on all ELISA-positive samples using orthotospovirus-specific primers gM410 & gM870c targeting the NSm gene (Chen et al., 2012). All samples were positive for orthotospoviruses, as indicated by the presence of a 500bp amplicon. Nineteen purified PCR products were sequenced in the forward and reverse directions using Sanger sequencing at the KwaZulu-Natal Research and Innovation Sequencing Platform (KRISP; South Africa). The sequences were aligned using Muscle in MEGA version X (Kumar et al., 2018) to generate the consensus sequences that were then subjected to the standard nucleotide basic local alignment search tool (blastn) on the NCBI website. Blastn analysis showed that 16 of the 19 samples matched TSWV nucleotide sequences, while three of the sequences; LP14 (accession number OL505552), LP18 (accession number OL505553), and NW4 (accession number OL505554), had a nucleotide sequence identity of 96,38%, 96,97% and 97,29% with the GSRV isolate SA-05 (accession number MH742957; Silva et al., 2019) from South Africa, respectively. This is the first report of GRSV infecting tobacco after TSWV was reported in SA. Previously, GSRV was reported on soybean and groundnut in South Africa by Petersen and Morris in (2002) and Silva et al. in (2019). The results from this study lay a foundation for more detailed studies on GRSV, which will result in the development of effective and sustainable control strategies to manage GRSV diseases on tobacco in SA.
ABSTRACT
Mesoplatys ochroptera Stål, Exosoma and Ootheca spp. seriously damage sesbania, Sesbania sesban (L.) Merril, a multipurpose leguminous tree widely used in tropical agroforestry. This is discouraging farmers from expanding the planting of sesbania in various agroforestry systems in eastern and south-central Africa. Rapid methods are needed for estimation of population densities of these beetles for decision making in pest management. A study was conducted with the objectives of determining the existence of any positive relationship between the occupancy and abundance of Mesoplatys, Exosoma and Ootheca and determining the model that best predicts abundance from occupancy for rapid estimation of population densities. The Poisson model assuming spatial randomness, the negative binomial distribution (NBD) model assuming spatial aggregation, the Nachman model without any distribution assumption, and a General model incorporating spatial variance-abundance and occupancy-abundance relationships were fitted to data on adult M. ochroptera, Exosoma and Ootheca from western Kenya, southern Malawi and eastern Zambia. Very strong variance to abundance relationships were observed in the spatial pattern of all three beetles. The occupancy-abundance relationships were also positive and strong in all beetles. The occupancy and abundance predicted by the four models were closest to the observed at lower densities compared with higher beetle densities. At higher population densities, the NBD and the General model gave better fit for M. ochroptera and Exosoma. For Ootheca populations, the Poisson and NBD models gave better fit at higher population densities. The relationships established here can be used as guide to estimate beetle densities for decision-making in pest management.
