National Academy of Agricultural Sciences (NAAS)
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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706 Issues : 12 per year Publisher : Excellent Publishers Email : editorijcmas@gmail.com / submit@ijcmas.com Editor-in-chief: Dr.M.Prakash Index Copernicus ICV 2018: 95.39 NAAS RATING 2020: 5.38 |
India is second most populous country after China which houses 15% of global population (census 2011) within 2.42% of geographical land area of world. The ever growing population and improving economic condition pressurize to produce and supply higher quantity of food grains. However, the country’s agriculture production is not increasing but somewhere stagnated, this increasing demand for food grain production. Agriculture sector therefore needs much attention to decrease this gap between increasing demand and production. Wheat, the staple cereal crop in world, is grown in 220.38 million hectare contributing 27.21% of total cereal grain production. In India, wheat is grown in an area of about 29.06 million hectares with a production of 86.87 million ton (FAO, 2011). The yield of wheat increased after sixties and early seventies bringing the green revolution in India. In recent years, production of wheat crop in response to the increasing application rates of the input resources is experiencing a declining trend. The decline in yield is mainly due to shortening of growth period, decrease in photosynthesis ability and increase in respiration demanding more irrigation water supply. Crop simulation models can provide an alternative, less time-consuming and inexpensive means of determining the optimum management option (Nitrogen and irrigation requirements) under varied soil and climatic conditions. Crop growth modeling has emerged as a powerful tool for optimizing crop yield and identifying critical factors, contributing to yield under varying climate change. In this context, dynamic mechanistic models CERES (Crop Environment Resource Synthesis)-Wheat available in Decision Support System for Agrotechnology Transfer (DSSAT) can be used for predicting growth and yield of wheat (Triticum aestivum L.) under different nitrogen and water management conditions. Our present study focuses the performance evaluation of CERES wheat model and use of the model for analysis of climate change impact on wheat yield. Keeping these in view the present study was formulated with the objectives of Calibration and validation of CERES-wheat model.
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