Forewarning Rice Blast in India

PREFACE
Rice, the staple food crop in India, holds key to our country’s food security. It is
grown in 44 million hectares with annual production of 90 million tons. To meet
the growing demand and sustain our self sufficiency in food, we need to grow an
additional 2 million tons of rice every year. To achieve this goal, the losses due to
biotic and abiotic stresses have to be minimised. Among the biotic stresses, blast is
one of the most destructive diseases and is widely prevalent in India. It is a major
limiting factor in realizing the full yield potential of rice cultivars in plains and hilly
areas of the country.
Blast is endemic to several rice growing areas in the country due to favourable
environment during the crop season. Weather has very important role to play in the
appearance, multiplication and spread of blast pathogen. Though a lot of fragmented
information is available on the blast disease and influence of weather on its
development, no consolidated effort has been made so far, to bring these together
to develop an ideal model for rice blast forewarning. Hence, the present study was
aimed to develop database on climate and blast disease in different agro-ecological
regions of India, to identify significant weather factors conducive for incidence,
intensification and spread of pathogen and disease, and to generate / validate
weather based forecasting models and operational forewarning systems for blast
control.
The results reported in this publication ‘Forewarning Rice Blast in India’, are
generated through the National Agricultural Technology Project on ‘Development of
Weather based Forewarning Systems for Crop Pests and Diseases’ undertaken at the
Directorate of Rice Research, Hyderabad, CSK Himachal Pradesh Krishiviswavidyala,
Palampur, and Central Research Institute for Dryland Agriculture, Hyderabad. It is
expected that this publication will be useful to researchers, extension workers and
farmers in understanding the blast disease and its relationship with weather, and
adopting suitable disease management practices based on the forewarning models
developed in the project.
(B. MISHRA)
Project Director