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- Sanjeev Kumar
- J. Singh
- K. K. Singh
- L. S. Rathore
- A. K. Baxla
- S. C. Bhan
- Akhilesh Gupta
- G. B. Gohain
- R. Balasubramanian
- R. S. Singh
- R. K. Mall
- Sompal Singh
- K. K. Gill
- Ram Niwas
- Sanjay Sharma
- S. K. Behera
- Prashant
- C. N. Ghosh
- D. P. Mishra
- P. K. Mandal
- Aniket Verma
- Sumeet Mohanty
- Kanhaiya Mishra
- N. K. Bhagat
- A. K. Mishra
- M. M. Singh
- Aditya Rana
- S. Tewari
- Jitendra Pandey
- S. K. Mandal
- Parashar Mishra
- Ahsan Absar
- Archisman Dutta
- Vishal V. Sakhare
- Uday Shankar
- A. P. Thapliyal
- Pankaj Saini
- Joyesh Bagchi
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
Singh, P. K.
- A Need of Farmer-Centric Marking System for Plant Varieties in Seed Market of India
Abstract Views :447 |
PDF Views:141
Authors
Affiliations
1 Indian Institute of Sugarcane Research, Dilkusha P.O., Lucknow 226 002, IN
1 Indian Institute of Sugarcane Research, Dilkusha P.O., Lucknow 226 002, IN
Source
Current Science, Vol 107, No 8 (2014), Pagination: 1231-1232Abstract
No Abstract.- Rice (Oryza sativa L.) Yield Gap Using the CERSE-Rice Model of Climate Variability for Different Agroclimatic Zones of India
Abstract Views :405 |
PDF Views:175
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.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.
- Angus, J. F. and Zandstra, H. G., Climatic factors and the modeling of rice growth and yield. In Agrometeorology of the Rice Crop, IRRI, Los Banos, Philippines, 1979, pp. 189–199.
- Kropff, M. J., Van Laar, H. H. and Mathews, R. B. (eds), ORYZA1, an ecophysiological model for irrigated rice production. In SARP Research Proceedings, AB-DLO and TPE-WAU, Wageningen and IRRI, Los Banos, 1994, p. 110.
- Penning de Vries, F. W. T., Jnasen, D. M., Ten Berge, H. F. M. and Bakema, A. H., Simulation of Ecophysiological Processes of Growth of Several Annual Crops, PUDOC, Wageningen, 1989, p. 271.
- Whisler, F. D., Sensitivity test of the crop variables in RICEMOD, IRRI, Res., Pap. Ser., 1983, pp. 89–103.
- Attachai, J., A decision support system for rapid assessment of low land rice-based alternative in Thailand. Agric. Syst., 1995, 47, 245–258.
- Diwakar, M. C. (ed.), Rice in India during 10th Plan, Directorate of Rice Development, Patna, 2009.
- Ritchie, J. T., Wheat phasic development, In Modelling Plant and Soil System (eds Hanks, J. and Ritchie, J. T.), Agron. Mongr., ASA, CSSA, Madison, WI, USA, 1991, p. 31.
- 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 :346 |
PDF Views:128
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.- Dry Biomass Partitioning of Growth and Development in Wheat (Triticum aestivum L.) Crop Using CERES-Wheat in Different Agro Climatic Zones of India
Abstract Views :307 |
PDF Views:140
Authors
Affiliations
1 Agromet Service Cell, India Meteorological Department, New Delhi 110 003, IN
2 School of Climate Change and Agri Meteorology, Punjab Agricultural University, Ludhiana 141 004, IN
3 Department of Agri Meteorology, CCSHAU, Hisar 125 004, IN
4 Department of Geophysics, Banaras Hindu University, Varanasi 221 005, IN
5 Department of Soil Science & Chemistry, College of Agriculture, Indore 452 001, IN
1 Agromet Service Cell, India Meteorological Department, New Delhi 110 003, IN
2 School of Climate Change and Agri Meteorology, Punjab Agricultural University, Ludhiana 141 004, IN
3 Department of Agri Meteorology, CCSHAU, Hisar 125 004, IN
4 Department of Geophysics, Banaras Hindu University, Varanasi 221 005, IN
5 Department of Soil Science & Chemistry, College of Agriculture, Indore 452 001, IN
Source
Current Science, Vol 113, No 04 (2017), Pagination: 752-766Abstract
The CERES-wheat crop growth simulation model has been calibrated and evaluated for two wheat cultivars (PBW 343 and PBW 542) for three sowing dates (30 October, 15 November and 30 November) during 2008-09 and 2009-10 to study partitioning of leaf, stem and grains at Ludhiana, Punjab, India. The experimental data and simulated model data were analysed on partitioning of leaf, stem and grains, and validated. It was found that the model closely simulated the field data from phenological events and biomass. Simulated biological and grain yield was in accordance with-field experiment crop yield within the acceptable range. The correlation coefficient between field-experiment and simulated yield data and biomass data varied significantly from 0.81 and 0.96. The model showed overestimation from field-experimental yield for both cultivars. The cultivar PBW 343 gave higher yield than cultivar PBW 542 on 15 November during both years. The model performance was evaluated and it was found that CERES-wheat model could predict growth parameters like days to anthesis and maturity, biomass and yield with reasonably good accuracy (error less than 8%) and also correlation coefficient between field-experimental and simulated yield data and biomass data varied from 0.94 and 0.95. The results showed that the correlation coefficient between simulated and districts yield varied from 0.41 to 0.78 and also significantly at all six selected districts. The results may be used to improve and evaluate the current practices of crop management at different growth stages of the crop to achieve better production potential.Keywords
Biomass Partitioning, Genetic Coefficient, Phenology Stages, Soil Parameters.References
- Curtis, B. C., Rajaram S. and Macpherson, H. G., Bread wheat improvement and production. FAO, Plant protection and production series no. 30, 2002, p. 77.
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- Singh, N. and Sontakke, N. A., On climatic fluctuations and environmental changes of Indo-Gangetic plains, India. Clim. Chnage, 2002, 52, 287–313.
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- Pannu, R. K., Singh, D. P., Singh, D. and Chaudhary, B. D., Contribution of plant parts of the total biomass as affected by environments in Indian mustard (Brassica juncea (L). Czern and Coss). Ann. Biol., 1996, 12, 368–376.
- Pannu, R. K., Singh, D. P., Singh, D., Chaudhary, B. D. and Sharma, H. C., Partitioning co-efficient of plant parts under different growth stages and environments in Indian mustard (Brassica juncea (L). Czern and Coss). Haryana Agric. University J. Res., 1997, 27, 31–37.
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- Singh, P. K., Singh, K. K., Bhan, S. C., Baxla, A. K., Akhilesh Gupta, R., Balasubramanian and Rathore, L. S., Growth and yield prediction of Rice DSSAT v 4.5 Model for the climate conditions of South Alluvial Zone of Bihar (India). J. Agrometeorol., 2015, 17(2), 194–198.
- Singh, K. K., Baxla, A. K., Singh, P. K., Reports of wheat yield predication at F2 level using CERES-wheat model for rabi 2014–15. ASC, IMD, New Delhi, 2015.
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- Singh, K. K., Baxla, A. K., Mall, R. K., Singh, P. K., Balasubramanian, R. and Garg, S., Wheat yield predication using CERES-Wheat model for decision support in agro-advisory. J. Vayu Mandal., 2010, 35&36(1-4), 2010, 97–109.
- Singh, P. K., Singh, K. K., Baxla, A. K., Kumar, B., Bhan, S. C. and Rathore, L. S., Crop yield predication using–Rice v 4.5 model for the climate variability of different agroclimatic zone of south and north-west plane zone of Bihar (India). Mausam, 2014, 65(4), 529–538.
- Singh, P. K., Singh, K. K., Baxla, A. K. and Rathore, L. S., Impact of climatic variability on wheat predication using DSSATv4.5 (CERES-Wheat) model for the different agroclimatic zones in India. Springer, 2015, 45, 55.
- Singh, P. K. et al., Rice (Oryza sativa L.) yield gap using the CERES-rice model of climate variability for different Agroclimatic zones of India. Curr. Sci., 2016, 110(3), 405–413.
- Singh, P. K., Singh, K. K., Bhan, S. C., Baxla, A. K., Akhilesh Gupta, Balasubramanian, and Rathore, L. S., Growth and yield prediction of Rice DSSAT v 4.5 Model for the climate conditions of South Alluvial Zone of Bihar (India). J. Agrometeorol., 2015, 17(2), 194–198.
- Slump Test:Laboratory and Numerical Simulation-Based Approach for Consistency of Mill Tailings Paste
Abstract Views :339 |
PDF Views:112
Authors
S. K. Behera
1,
Prashant
1,
C. N. Ghosh
1,
D. P. Mishra
2,
P. K. Mandal
1,
Aniket Verma
1,
Sumeet Mohanty
3,
Kanhaiya Mishra
1,
P. K. Singh
1
Affiliations
1 CSIR-Central Institute of Mining and Fuel Research, Dhanbad 826 015, IN
2 Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, IN
3 Birla Institute of Technology and Science, Hyderabad 500 078, IN
1 CSIR-Central Institute of Mining and Fuel Research, Dhanbad 826 015, IN
2 Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, IN
3 Birla Institute of Technology and Science, Hyderabad 500 078, IN
Source
Current Science, Vol 117, No 2 (2019), Pagination: 235-241Abstract
Solid-to-water proportion decides the effectiveness of paste backfill in terms of transportation characteristics during mine backfilling. This article highlights various laboratory tests conducted to determine the optimum solid-to-water ratio. Also, numerical simulation was carried out using computational fluid dynamics technique (ANSYS FLUENT) to understand the slump lifting process and variation in volume of the paste with time. The optimum slump and spread for lead–zinc mill tailings paste were in the range 190– 200 mm and 330–340 mm respectively. The optimum water content in the paste fill for this study was found to be 23 wt%. Results show that the solid percentage is inversely related with slump and spread. Also, an optimum slump lifting speed needs to be maintained for accurate values of slump and spread.Keywords
Computational Fluid Dynamics Modelling, Mill Tailings, Paste Fill, Slump Test.References
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- Haiqiang, J., Fall, M. and Cui, L., Yield stress of cemented paste backfill in sub-zero environments: experimental results. Miner. Eng., 2016, 92, 141–150.
- Blasting Technique for Stabilizing Accident-Prone Slope for Sustainable Railway Route
Abstract Views :426 |
PDF Views:139
Authors
Affiliations
1 CSIR-Central Institute of Mining and Fuel Research, Barwa Road, Dhanbad 826 015, IN
2 Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, IN
1 CSIR-Central Institute of Mining and Fuel Research, Barwa Road, Dhanbad 826 015, IN
2 Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, IN
Source
Current Science, Vol 118, No 6 (2020), Pagination: 901-909Abstract
Konkan Railway has many unstable slopes along the 741 km long route from Roha to Thokur in the states of Maharashtra, Goa and Karnataka in India. Frequent cases of boulder fall, slope failure and landslide used to occur on the track during the rainy season. Such cases have resulted in several severe train accidents, traffic interruptions, loss of lives and assets. Hence the Konkan Railway Corporation deployed several geotechnical measures such as wire-netting, retaining wall, rock bolting and shotcreting for stability enhancement. However, none of these measures proved effective and accidents continued. Finally, the Konkan Railway Corporation decided to redesign the cut-slopes using blasting. Excavation of hard rock for its removal without damaging the existing track (2– 3 m away from the slope) and disrupting the traffic, was a daunting task. An unplanned blast would have resulted in the closure of the route for hours. The present study explains the method in which entire cutting was redesigned by formation of 5 to 2 m wide berms at an interval of 6 m bench height from rail track level using novel direction controlled blasting technique. Further, stability of the cut-slope, before and after exacavation, has been determined using kinematic analysis and 3D numerical modelling. Similar technique can be adopted to widen or stabilize an active transportation route in hills.Keywords
Blasting, Kinematic Analysis, Numerical Modelling, Railway Track, Slope Rockmass Removal, Stabilization.References
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- Specific blasting technique for tunnelling in hot zones
Abstract Views :260 |
PDF Views:119
Authors
Affiliations
1 CSIR-Central Institute of Mining and Fuel Research, Barwa Road, Dhanbad 826 001, IN
1 CSIR-Central Institute of Mining and Fuel Research, Barwa Road, Dhanbad 826 001, IN
Source
Current Science, Vol 121, No 9 (2021), Pagination: 1227-1234Abstract
Encountering hot zones while excavating tunnels for hydropower projects in the Himalaya, India, is a challenge for civil engineers. Blasting within the hot rock mass can pose serious threats due to possibility of temperature-induced unintended detonation of explosives. Moreover, the paucity of a suitable rock-blasting method for these hot zones sometimes compels engineers to realign the tunnel. Such a realignment is costly and time-consuming. A temperature of 50–98°C was encountered while excavating the rock mass for head race tunnel of Karchham–Wangtoo Hydro-Electric Project, Himachal Pradesh, India. The Directorate General of Mine Safety, India, suggests that blast-holes with temperature greater than 80°C must not be charged and blasted. Similarly, the use of electric or non-electric detonators is discouraged above 70°C because of premature detonation. Hence excavation works were suspended for tunnel construction. A unique drill and blast method has been adopted for blasting the hot strata in the tunnel. The technique described in this study can be easily followed in similar situations for tunnel-rock excavationKeywords
Excavation sequence, geothermal energy, hot zone, quenching, tunnel blastingReferences
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- Hot Springs of Demchok, Ladakh, India
Abstract Views :190 |
PDF Views:104
Authors
Parashar Mishra
1,
Ahsan Absar
2,
Archisman Dutta
1,
Vishal V. Sakhare
3,
Uday Shankar
2,
A. P. Thapliyal
4,
Pankaj Saini
5,
P. K. Singh
4,
Joyesh Bagchi
4
Affiliations
1 Geological Survey of India, Northern Region, Lucknow 226 024, India; Institute of Science, Banaras Hindu University, Varanasi 221 005, India., IN
2 ONGC Energy Centre, SCOPE Minar, Lakshmi Nagar, Delhi 110 092, India., IN
3 Geological Survey of India, Central Region, Nagpur 440 006, India., IN
4 Geological Survey of India, Northern Region, Lucknow 226 024, India., IN
5 Geological Survey of India, Gangtok 737 101, India., IN
1 Geological Survey of India, Northern Region, Lucknow 226 024, India; Institute of Science, Banaras Hindu University, Varanasi 221 005, India., IN
2 ONGC Energy Centre, SCOPE Minar, Lakshmi Nagar, Delhi 110 092, India., IN
3 Geological Survey of India, Central Region, Nagpur 440 006, India., IN
4 Geological Survey of India, Northern Region, Lucknow 226 024, India., IN
5 Geological Survey of India, Gangtok 737 101, India., IN
Source
Current Science, Vol 124, No 9 (2023), Pagination: 1104-1107Abstract
In this study, two thermal springs are reported from the Demchok area in Ladakh, India. These are characterized by water having low total dissolved solids (TDS) content (~250 mg/l) as well as high pH (9.5) and surface temperature (75°C). Although these hot springs and their medicinal properties are known to locals, they have not been scientifically studied. Relatively low TDS despite high temperature could be due to sluggish ion-exchange processes in the geothermal reservoir. Such a situation might have developed because of the high water-to-rock ratio and/or smaller residence time of the geothermal fluid in the reaction zone.Keywords
Geothermal Zone, Hot Springs, Ion-Exchange Process, Medicinal Properties, Water–Rock Ratio.References
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