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Co-Authors
- P. K. Singh
- K. K. Singh
- L. S. Rathore
- A. K. Baxla
- S. C. Bhan
- G. B. Gohain
- R. Balasubramanian
- R. S. Singh
- R. K. Mall
- Sompal Singh
- G. Bala
- Anil V. Kulkarni
- S. Pratibha
- Nisha Mendiratta
- H. K. Mittal
- A. Mukhopadhyay
- Neeraj Sharma
- Rajiv Tayal
- Ashutosh Sharma
- Rajiv K. Tayal
- Neelima Alam
- G. V. Raghunath Reddy
- Vineet Saini
- J. B. V. Reddy
- Ranjith Krishna Pai
- Ligy Philip
- Prasada Raju
- T. Pradeep
- Perminder Jit Kaur
- Monika Agarwal
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Gupta, Akhilesh
- Rice (Oryza sativa L.) Yield Gap Using the CERSE-Rice Model of Climate Variability for Different Agroclimatic Zones of India
Abstract Views :418 |
PDF Views:184
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
- Patel, H. R. and Shekh, A. M., Yield gap and trend analysis of wheat using CERES-wheat model in three districts of Gujarat state. J. Agrometeorol., 2006, 8(1), 28–39.
- Patel, V. J., Patel, H. R. and Pandey, V., Estimation of wheat yield gap in Anand and Panchmahal districts using CERES-wheat model. J. Agrometeorology. (Spec. Issue-part-2), 2008, 393–397.
- Bell, M. A. and Fischer, R. A., Using yield predication to assess yield grains: a case study for wheat. Field Crops Res., 1994, 36, 161–166.
- Aggarwal, P. K. and Kalra, N., Analysing the limitation set by climatic factors, genotype and water and nitrogen availability on productivity of wheat II. Climatic potential yield and management strategies. Field Crops Res., 1994, 38, 93–103.
- Aggarwal, P. K., Hebbar, K. B., Venugopalan, M. V., Rani, S., Bala, A., Biswal, A. and Wani, S. P., Quantification of yield gaps in rain-fed rice, wheat, cotton and mustard in India. Global theme on agro ecosystems, report no. 43 and page 36, ICRISAT, Hyderabad, 2008.
- Pathak, H. et al., Trend of climatic potential and on-farm yield of rice and wheat in the Indo-Gangetic Plains. Field Crops Res., 2003, 80, 223–234.
- Wickham, T. H., Predicting yield in lowland rice through a water balance model in Philippine irrigation systems: research and operations. International Rice Research Institute (IRRI), Los Banos, Philippines, 1973, pp. 155–181.
- Ahuja, S. P., Computer simulation of primary production of semiaquatic system using rice (Oryza sativa). Analysis and modeling of the physics of biological–climatological coupling. Ph D thesis, University of California, Devis, 1974.
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- Singh, K. K., Baxla, A. K., Singh, P. K. and Balasubramanian, R., A report on database for rice cultivars used in CERES-rice crop simulation model in different agroclimatic zones of India, Agromet Service Cell, New Delhi, 2010.
- 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.
- Sinha, S. K., Singh, G. B. and Rai, M., Decline in Crop Productivity in Harayana and Punjab: Myth or Reality? Indian Council of Agricultural Research, New Delhi, 1998, p. 89.
- Bhandari, A. L., Ladha, J. K., Pathak, H., Padre, A. T., Dawe, D. and Gupta, R. K., Trend of yield and soil nutrient status in longterm rice–wheat experiment in the Indo-Gangetic Plains of India. Soil Sci. Soc. Am. J., 2002, 66, 162–170.
- Yadav, R. L., Diwivedi, B. S., Orsad, K., Tomar, O. K., Shurapali, N. J. and Pandey, P. S., Yield trends and changes in soil organic-C and available NPK in a long-term rice–wheat system under integrated use of manures and fertilizers. Field Crops Res., 2000, 68, 219–246.
- Akula, B., Estimating wheat yields in Gujarat using WTGROWS and INFOCROP models. Ph D thesis, Anand Agriculture University, Sardar Krishinagar, Anand, Gujarat, India, 2003.
- Mall, R. K. and Srivastava, M. K., Prediction of potential and attainable yield of wheat: a case study on yield gap. Mausam, 2002, 53, 45–52.
- Impact of Projected Climate Change on Rice (Oryza sativa L.) Yield Using CERES-Rice Model in Different Agroclimatic Zones of India
Abstract Views :357 |
PDF Views:136
Authors
P. K. Singh
1,
K. K. Singh
1,
S. C. Bhan
1,
A. K. Baxla
1,
Sompal Singh
2,
L. S. Rathore
1,
Akhilesh Gupta
3
Affiliations
1 Agromet Service Cell, India Meteorological Department, Lodhi Road, New Delhi 110 003, IN
2 Department of Agriculture Meteorology, Punjab Agriculture University, Ludhiana 141 004, IN
3 Department of Science and Technology, New Delhi 110 016, IN
1 Agromet Service Cell, India Meteorological Department, Lodhi Road, New Delhi 110 003, IN
2 Department of Agriculture Meteorology, Punjab Agriculture University, Ludhiana 141 004, IN
3 Department of Science and Technology, New Delhi 110 016, IN
Source
Current Science, Vol 112, No 01 (2017), Pagination: 108-115Abstract
Climate change is projected to alter the growing conditions of rice crop in different regions of India. Crop growth simulation model (DSSATv4.6) was calibrated and evaluated with four rice cultivars: PR 118 in Amritsar, Ludhiana; HKR 126 in Hisar and Ambala; Pant 4 in Kanpur and Sugandha-1126 in Modipuram on different sowing dates. The average yield of the selected optimum dates was 6391, 6531, 7751, 7561, 4347 and 4131 kg/ha for Amritsar, Ludhiana, Hisar, Ambala, Modipuram and Kanpur respectively. Both temperature and CO2 have increased. The combined effect of temperature and CO2 indicates decreased yield rate in the future decades. The present study shows that rice yield will decrease in the future and this may be due to increase in temperature. According to projection results, for all the locations average yield is higher in the decade 2010, except Amritsar in the decade 2030 and Ludhiana in the decade 2050. The average yield at Hisar, Ambala, Modipuram and Kanpur in 2010 was 7744, 7654, 4347 and 4021 kg/ha respectively. Amritsar and Ludhiana showed maximum average yield of 6880 and 6877 kg/ha respectively, in the decade 2030. Such yield reductions in rice crops due to climate change are mediated through reduction in crop duration, grain number and grain filling duration. These projections nevertheless provide a direction of likely change in crop productivity in future climate change scenarios.Keywords
Agroclimatic Zones, Climate Change, Crop Simutation Models, Rice.Full Text
- Geoengineering and India
Abstract Views :617 |
PDF Views:132
Authors
G. Bala
1,
Akhilesh Gupta
2
Affiliations
1 Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bengaluru 560 012, IN
2 Climate Change Programme, Department of Science and Technology, New Delhi 110 016, IN
1 Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bengaluru 560 012, IN
2 Climate Change Programme, Department of Science and Technology, New Delhi 110 016, IN
Source
Current Science, Vol 113, No 03 (2017), Pagination: 376-377Abstract
The national roundtable discussion on geoengineering was held recently in Delhi. While research on geoengineering is fairly advanced in the international arena, very little R&D efforts have been undertaken in India. Hence, the Department of Science and Technology (DST) has recently launched a Major R&D project (MRDP) at Centre for Amospheric and Oceanic Sciences (CAOS), Indian Institute of Science (IISc) to undertake climate modelling experiments in order to generate strategic knowledge on stratospheric aerosol geoengineering. The primary objective of convening the roundtable discussion on geoengineering was to seek views of the experts and policy makers on the issue of whether and how geoengineering is likely to impact India.Full Text
- Himalayan Cryosphere
Abstract Views :467 |
PDF Views:144
Authors
Affiliations
1 Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru 560 012, IN
2 Climate Change Programme, Department of Science and Technology, New Delhi 110 016, IN
1 Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru 560 012, IN
2 Climate Change Programme, Department of Science and Technology, New Delhi 110 016, IN
Source
Current Science, Vol 115, No 1 (2018), Pagination: 17-17Abstract
The glaciers and seasonal snow melt feed numerous Indian rivers originating from the Himalaya and support millions of people. However, snow and glaciers are sensitive to climate change and the ongoing climate change will potentially affect water availability for millions of people living in North India. Therefore, comprehensive understanding of factors and processes affecting the Himalayan cryosphere is necessary.Full Text
- Indian Science and Conflict of Interest
Abstract Views :392 |
PDF Views:127
Authors
Affiliations
1 Department of Science and Technology, New Delhi 110 016, IN
1 Department of Science and Technology, New Delhi 110 016, IN
Source
Current Science, Vol 115, No 6 (2018), Pagination: 1020-1020Abstract
This is in response to the editorial titled ‘Is Indian science ready to tackle conflict of interest in a rational way?’ by E. Arunan.Full Text
References
- Arunan, E., Curr. Sci., 2018, 114, 1385– 1386.
- Subrahmanyan, R., Curr. Sci., 2018, 115(2), 193.
- Swarup, G., Curr. Sci., 2018, 115(3), 369.
- Mohan, P. and Brakaspathy, R., Curr. Sci., 2018, 114(9), 1835–1839.
- Sanjay Bajpai (1965–2021)
Abstract Views :253 |
PDF Views:135
Authors
Ashutosh Sharma
1,
Rajiv K. Tayal
1,
Akhilesh Gupta
1,
Neelima Alam
1,
G. V. Raghunath Reddy
1,
Vineet Saini
1,
J. B. V. Reddy
1,
Ranjith Krishna Pai
1,
Ligy Philip
2,
Prasada Raju
3,
T. Pradeep
4
Affiliations
1 Department of Science and Technology, New Delhi 110 016, IN
2 Department of Civil Engineering, Indian Institute of Technology Madras, Chennai 600 036, IN
3 Industrial Consultancy and Sponsored Research, Indian Institute of Technology Madras, Chennai 600 036, India (former Scientist, DST), IN
4 Department of Chemistry, Indian Institute of Technology Madras, Chennai 600 036, IN
1 Department of Science and Technology, New Delhi 110 016, IN
2 Department of Civil Engineering, Indian Institute of Technology Madras, Chennai 600 036, IN
3 Industrial Consultancy and Sponsored Research, Indian Institute of Technology Madras, Chennai 600 036, India (former Scientist, DST), IN
4 Department of Chemistry, Indian Institute of Technology Madras, Chennai 600 036, IN
Source
Current Science, Vol 120, No 11 (2021), Pagination: 1790-1791Abstract
No Abstract.Keywords
No Keywords.Full Text
- SERB-SURE Scheme in India: Early Indicators and Recommendations
Abstract Views :251 |
PDF Views:77
Authors
Affiliations
1 Department of Science and Technology, Centre for Policy Research, Indian Institute of Science, Bengaluru, IN
2 Science and Engineering Research Board, New Delhi 110 016, IN
3 Department of Science and Technology, and Science and Engineering Research Board, New Delhi 110 016, IN
1 Department of Science and Technology, Centre for Policy Research, Indian Institute of Science, Bengaluru, IN
2 Science and Engineering Research Board, New Delhi 110 016, IN
3 Department of Science and Technology, and Science and Engineering Research Board, New Delhi 110 016, IN
Source
Current Science, Vol 125, No 9 (2023), Pagination: 934-938Abstract
State-level institutes have an important role in strengthening the national STI ecosystem. SERB-SURE scheme was launched in 2022 to support research at state-level institutes to strengthen the national STI ecosystem. The scheme also promotes researchers with no ongoing/completed project proposals under SERB and thus is a platform to appraise the upcoming talent pool of the country. The details of proposals submitted and recommended have been gathered from the PRISM website and SERB online portal. The present article quantitatively analyses the trend of project proposal submission and approval based on parameters such as gender, state, institute type and subject area between the financial year 2022–23. Based on these early indicators, some recommendations for promoting research at state-level institutes are provided here.Keywords
Government Programme, Research in India, Schemes, Science, SERB, SURE, Technology.Full Text
References
- AISHE 2021; https://aishe.gov.in/aishe/home
- Research and Development Statistics, 2022–23; www.nstmis-dst.org
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- Agarwal, M., Role of J.C. Bose Fellowship in empowering women scientists in India. Curr. Sci., 2022, 123(11), 1305–1308.
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- Chakraborty, K., Upadhyaya, N. and Upadhyay, R. S., Explored publication pattern of the top twenty NIRF-2020 ranked Indian institutions: an evaluative study. Libr. Philos. Pract., 2021, 5385, 1–18; https://digitalcommons.unl.edu/libphilprac
- Banshal, S. K., Singh, V. K., Base, A. and Muhuri, P. K., Comparing research performance of Indian Institutes of Technology. Curr. Sci., 2019, 116(8), 1304–1313.
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- Kanaujia, A., Nandy, A., Singh, P. and Singh, V. K., Mapping the research output from Indian states, Curr. Sci., 2023, 124(11), 1245–1255.