Influence of meteorological factors on atmospheric fungal spores over crop canopy of rice in West Bengal, India with reference to major fungal diseases

Abstract

Rice is a major cereal crop and staple food for the people of India. Fungal spores in the atmosphere are considered to be one of the most potent bio-pollutants, which are pathogenic to rice crops having direct impact on our food security. The aim of the present study was to assess the concentration of airborne fungal spores over a paddy field in relation to meteorological parameters and disease severity with an objective to prepare an efficient forecasting system for most important fungal diseases. Volumetric aero-mycological survey was carried out by Burkard personal sampler and Andersen sampler that were operated for three consecutive kharif (rainy) seasons (2015-2017) at weekly intervals over a rice field in W est Bengal, India. The meteorological parameters during the investigation period were recorded at the nearest meteorological station. The concentrations of culturable and non-culturable spore types varied in different growth phases. The dominant genera trapped by Burkard sampler were Cladosporium sp. (9.97%), Memnoneilla sp (6.60%), Trichoconis sp (5.63%), Stemphyllium sp. (5.65%), smut spores (5.65%), Helminthosporium sp. (5.22%), Trichoderma viride (5.02%), Pyricularia sp. (4.75%). Among the 18 mould types recorded by Andersen sampler, Aspergillus niger (8.95 %) was the most dominant one, followed in the degree of prevalence by Aspergillus clavatus (6.98%), Penicillium claviformae (6.11%), Trichoderma lignorum (5.50%), Penicillium expansum (5.44%), Alternaria alternata (5.43%) and Fusarium oxysporium (4.33%). A statistical correlation was calculated among the fungal spore loads with the five meteorological parameters, which would be beneficial to predict the spore concentration with the respective meteorological parameters. The total spore count exhibited a negative correlation with maximum temperature, minimum temperature, relative humidity, rain fall and wind speed but positively correlated with age of the plant. The regression model based on the spore count and meteorological variables supplemented by host factors is found to be useful for prediction of rice diseases. Three major fungal diseases were considered with the concentration of the respective fungal pathogens. Relationship between the disease scales along with the growth phases were also recorded.