Forecasting tomato's foe: Predicting groundnut bud necrosis disease using extended range weather dynamics

G Senbagavalli; Ga Dheebakaran; NK Sathyamoorthy; P Renukadevi; S Kokilavani; B Kannan; KP Ragunath

doi:10.14719/pst.5947

Authors

G Senbagavalli Agro Climate Research Centre, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0002-6035-2329
Ga Dheebakaran Agro Climate Research Centre, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0002-0603-192X
NK Sathyamoorthy Agro Climate Research Centre, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0002-7296-4808
P Renukadevi Department of Plant Pathology, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0001-9665-1681
S Kokilavani Agro Climate Research Centre, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0003-3548-6146
B Kannan Department of Soil and Water Conservation Engineering, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0003-2330-0893
KP Ragunath Centre for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0002-7851-4437

DOI:

https://doi.org/10.14719/pst.5947

Keywords:

epidemiology, GBNV, PCA, thrips, tomato, weather

Abstract

Tomato (Solanum lycopersicum L.), a staple vegetable crop in the Solanaceae family, suffers significant yield losses due to the Groundnut Bud Necrosis Virus (GBNV). This thrips-transmitted virus can cause up to 100% yield reduction depending on the stage of infection. A study conducted in Coimbatore, Tamil Nadu, India during the summer of 2023 and 2024, investigated the epidemiology of GBNV. Using weather correlation analysis and Principal Component Analysis (PCA), key weather factors influencing the spread of thrips and GBNV were identified. In 2023, the thrips population peaked in mid-April, followed by GBNV incidence in early May. In 2024, thrips peaked in early May, with GBNV incidence reaching its highest levels in the third week of May. This demonstrated a direct correlation between thrips population dynamics and GBNV progression, although variations in timing with observed between the two years. The analysis highlighted temperature and relative humidity as consistent, critical weather parameters influencing thrips populations and GBNV incidence, particularly with two-week time lags. By correlating weather conditions with thrips and GBNV incidence across various time lags, this study contributes to the development of an extended-range weather forecast-based GBNV forewarning system. Such a system enhances preparedness and response strategies, mitigating the impact of GBNV on tomato crops and promoting food security. This multidisciplinary approach supports sustainable farming practices in the face of climate uncertainties while bolstering agricultural resilience.

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