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Thursday 11 August 2016

Stempedia: a weather-based model to explore and manage the risk of lentil Stemphylium blight disease

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Title 

Stempedia: a weather-based model to explore and manage the risk of lentil Stemphylium blight disease

  • Author 
  • Moin U. Salam 
  • Tapan K. Day
  • Ashraf U. Ahmed
  • Bodrun Nessa
  • A. H. M. Mahfuzul Haque
  • Subash Subedi
  • Al Imran Malik
  • M. Matiur Rahman
  • William Erskine

Abstract

Lentil Stemphylium blight is a fungal disease threatening sustainable lentil-based cropping in South Asia including Bangladesh. A weather-based model ʻStempediaʼ was developed to understand the risk of the disease. Daily maximum temperature and sunshine hours are the two most important parameters of the model. When tested with field data from Bangladesh and Nepal, the model simulated the disease severity well both without (R 2 = 0.89, n = 17) and with (R 2  = 0.80, n = 18) fungicide application scenarios. As a result, Stempedia was subjected to experimentation to explore the risk and risk management options related to the disease under Bangladesh conditions. Taking Gazipur - a central regional district - as an example, the model identified that, predominantly, gradual reductions in sunshine hours (or, increased cloudiness) during the early part of the ‘disease susceptible window’ had increased the disease severity over the last 30 years. The model simulated Ishurdi, a north-western regional district, as more disease prone than Gazipur and Jessore, a south-eastern regional district. Stempedia simulated seasonal variability of the disease and predicted reduced severity with delayed sowing, the magnitude of which differed between regions. Stempedia also predicted financial returns with three foliar applications of an effective fungicide but this depended on the timing of application. The best financial return occurred with an early fungicide application, as soon as the disease appeared during initiation of flowering, followed by further application(s) if a disease-producing environment was expected. We conclude that the model has potential to assess regional and seasonal risks of this disease and to determine risk aversion by manipulating sowing time. This model can further be used to formulate the principle of foliar fungicide application to achieve financial gain.


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For further details log on website :
http://link.springer.com/article/10.1007/s13313-016-0434-3

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