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Balasubramanian, R.
- Rice (Oryza sativa L.) Yield Gap Using the CERSE-Rice Model of Climate Variability for Different Agroclimatic Zones of India
Abstract Views :297 |
PDF Views:128
Authors
P. K. Singh
1,
K. K. Singh
1,
L. S. Rathore
1,
A. K. Baxla
1,
S. C. Bhan
1,
Akhilesh Gupta
2,
G. B. Gohain
1,
R. Balasubramanian
3,
R. S. Singh
4,
R. K. Mall
4
Affiliations
1 Agromet Service Cell, India Meteorological Department, Lodhi Road, New Delhi 110 003, IN
2 Deparment of Science and Technology, New Delhi 110 016, IN
3 Agrimet Pune, New Delhi 411 005, IN
4 Banaras Hindu University, Varanasi 221 005, IN
1 Agromet Service Cell, India Meteorological Department, Lodhi Road, New Delhi 110 003, IN
2 Deparment of Science and Technology, New Delhi 110 016, IN
3 Agrimet Pune, New Delhi 411 005, IN
4 Banaras Hindu University, Varanasi 221 005, IN
Source
Current Science, Vol 110, No 3 (2016), Pagination: 405-413Abstract
The CERES (crop estimation through resource and Environment Synthesis)-rice model incorporated in DSSAT version 4.5 was calibrated for genetic coefficients of rice cultivars by conducting field experiments during the kharif season at Jorhat, Kalyani, Ranchi and Bhagalpur, the results of which were used to estimate the gap in rice yield. The trend of potential yield was found to be positive and with a rate of change of 26, 36.9, 57.6 and 3.7 kg ha-1 year-1 at Jorhat, Kalyani, Ranchi and Bhagalpur districts respectively. Delayed sowing in these districts resulted in a decrease in rice yield to the tune of 35.3, 1.9, 48.6 and 17.1 kg ha-1 day-1 respectively. Finding reveals that DSSAT crop simulation model is an effective tool for decision support system. Estimation of yield gap based on the past crop data and subsequent adjustment of appropriate sowing window may help to obtain the potential yields.Keywords
Agroclimatic Zones, Genetic Coefficients, Rice Model, Yield Gap.Full Text
References
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- Singh, P. K., Singh, K. K., Baxla, A. K., Rathore, L. S., Kumar, B., Balasubramanian, R. and Tyagi, B. S., Crop yield prediction using CERES-rice model for the climate variability of South Bihar alluvial zone of Bihar (India). AP Chapter of Association of Agrometeorologists National Symposium on Agro Meteorology, at Central Research Institute for Dry land Agriculture (CRIDA), Hyderabad, 2013, pp. 22–23.
- Singh, P. K., Singh, K. K., Baxla, A. K. and Rathore, L. S., Impact of climatic variability on Rice productivity using CERES-rice models Eastern plain zone of Uttar Pradesh. In Third International Agronomy Congress on ‘Agriculture Diversification, Climate Change Management and Livelihoods’, IARI, New Delhi, 26–30 November 2012 and extended summaries vol. (2), 2012, pp. 236– 237.
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- Akula, B., Estimating wheat yields in Gujarat using WTGROWS and INFOCROP models. Ph D thesis, Anand Agriculture University, Sardar Krishinagar, Anand, Gujarat, India, 2003.
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- Impact of Observed Climate Change on the Classification of Agroclimatic Zones in India
Abstract Views :211 |
PDF Views:73
Authors
N. Chattopadhyay
1,
A. K. Sahai
1,
P. Guhathakurta
1,
S. Dutta
1,
A. K. Srivastava
1,
S. D. Attri
2,
R. Balasubramanian
1,
K. Malathi
1,
Swati Chandras
1
Affiliations
1 India Meteorological Department, Shivajinagar, Pune 411 005, IN
2 India Meteorological Department, New Delhi 110 003, IN
1 India Meteorological Department, Shivajinagar, Pune 411 005, IN
2 India Meteorological Department, New Delhi 110 003, IN
Source
Current Science, Vol 117, No 3 (2019), Pagination: 480-486Abstract
The classification of agroclimatic zones in India was made in the 1990s for identifying priorities and developing strategies for location-specific and need-based research as well as overall agricultural development in the country. Long-term climatic parameters, particularly temperature and rainfall along with soil and crop information were used for the classification of agroclimatic zones. It has been documented with a fair degree of accuracy that overall climate is changing, particularly with respect to temperature over the Indian region. Thus it is anticipated that in the recent past, climate change may be reflected in the agroclimatic zones as well and ultimately affect the criteria of their classification based on climatic parameters. The objective of the present study is to examine the trends and spatial/temporal variability of temperature, rainfall, rainy days, and heavy rainfall in different agroclimatic zones of the country, which may help in better understanding of the further initiatives on reclassification of agroclimatic zones, if required. Using various long-term gridded data from 1985 and instrumental datasets starting from 1951 to 1980, studies have been made to observe changes in different components of the climatic variables, i.e. temperature and rainfall. It has been observed that there are significant changes in temperature and rainfall, both temporally and spatially, across India and there is a definite shift in temperature and rainfall patterns in the recent past compared to 1951–1980. It has also been inferred that there is a need to reconsider the classification of agroclimatic zones in India under the scenario of observed climate changes in the country.Keywords
Agroclimatic Zones, Classification, Climatic Parameters, Climate Change.Full Text
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