Authors
Chunzhi Lu, Ming Liu, Junzi Zhu, Chengwei Yang, Yuanyuan Huang, Sheng Pu, Jiaen Su, Xingyu Zi, Yuling Zhang, Juan Li, Wenqiang Mei
Published in
Frontiers in plant science. Volume 17. Pages 1935872. Epub Sep 25, 2026.
Abstract
Tomato spotted wilt is an important viral constraint on tobacco production, but the direction and magnitude of future climate effects remain uncertain. This systematized narrative review evaluates evidence linking climate drivers with cultivated tobacco physiology, tomato spotted wilt virus (TSWV), thrips-vector ecology, weed reservoirs, surveillance, and management. Direct multifactorial experiments that simultaneously manipulate climate, TSWV, tobacco, and vector species are scarce; therefore, the synthesis explicitly separates direct tobacco evidence from evidence derived from other TSWV hosts, vector-only studies, general plant-stress physiology, and proposed mechanisms. Available tobacco studies show that long-term growth temperature, acute heat exposure, and progressive soil-water deficit alter photosynthesis, pigment metabolism, stomatal conductance, reactive oxygen species, and antioxidant responses, but they do not by themselves demonstrate enhanced TSWV replication or systemic movement. Field and vector studies indicate that weather can alter thrips development, survival, dispersal, and the temporal coincidence between viruliferous adults and susceptible tobacco, although responses are nonlinear and differ among Frankliniella fusca, Frankliniella occidentalis, Thrips tabaci, regions, and populations. We synthesize quantitative exposure ranges, identify confirmed and extrapolated pathways, compare diagnostic and surveillance options, and define a climate-adaptive management framework. The evidence supports region-specific risk assessment rather than a universal assumption that warmer or drier seasons will necessarily increase epidemics. Priority research requires factorial tobacco-TSWV-vector experiments, standardized physiological and virological endpoints, and independent validation of forecasting models.
PMID:
42877656
Bibliographic data and abstract were imported from PubMed on 16 Oct 2026.
Read full publication at:
Please sign in
to see all details.
Advertisement
Stats
- Recommendations n/a n/a positive of 0 vote(s)
- Views 5
- Comments 0