Refine your search
Collections
Co-Authors
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
Subbaiah, P. Venkata
- Quality assessment of groundwater of Kadapa district, Andhra Pradesh, India for irrigation purpose and management options
Abstract Views :204 |
PDF Views:82
Authors
Affiliations
1 All India Co-ordinated Research Project on Management of Salt Affected Soils and Use of Saline Water in Agriculture, Acharya N.G. Ranga Agricultural University, Bapatla 522 101, IN
2 ICAR-Central Soil Salinity Research Institute, Karnal 132 001, IN
1 All India Co-ordinated Research Project on Management of Salt Affected Soils and Use of Saline Water in Agriculture, Acharya N.G. Ranga Agricultural University, Bapatla 522 101, IN
2 ICAR-Central Soil Salinity Research Institute, Karnal 132 001, IN
Source
Current Science, Vol 122, No 10 (2022), Pagination: 1185-1192Abstract
Water samples collected from various locations in Kadapa district, Andhra Pradesh (AP), India were analysed for quality parameters, namely reaction (pH), salinity, Ca2+, Mg2+, Na+, and K+; CO2, HCO, Cl– and SO2. The pH fell in the range 6.5–8.1, electrical conductivity (EC) from 0.4 to 11.1 (dS m–1), sodium adsorption ratio (SAR) from 0.4 to 41.2 (mmol l–1)1/2 and residual sodium carbonate (RSC) from –52.4 to 16.2 (meq l–1). The presence of positively charged ions, namely calcium, magnesium, sodium and potassium varied from 0.4 to 46.0, 1.2 to 16.4, 0.76 to 60.1 and 0.002 to 11.78 meq l–1 respectively. The concentration of bicarbonates, chlorides and sulphates varied from 0 to 2.0, 1.0 to 17.6, 0.4 to 76.0 and 0.3 to 14.8 me l–1 respectively. The dominance of ions for majority of the samples was Na+ > Ca2+ > Mg+2 > K+ for positively charged ions and HCO > Cl– > SO2 > CO for negatively charged ions. According to classification of irrigation water by the Central Soil Salinity Research Institute, Karnal, Haryana, India, 53.18% water samples is good, 21.88% marginally saline, 0.3% saline, 4.56% high SAR saline, 6.69% marginally alkaline, 7.90% alkaline and 5.47% highly alkaline. Spatial variability of pH, EC, SAR, RSC and groundwater quality in Kadapa district, AP was demonstrated using GIS maps.Keywords
Groundwater quality, ionic correlation, salinity, sodium absorption ratio, spatial variability.References
- Singh, R., Singh, A. K., Yadav, S. R., Singh, S. P., Godara, A. S., Kaledhonkar, M. J. and Meena, B. L., Effect of saline water and fertility levels on pearl millet–psyllium crop sequence under drip irrigation in arid region of Rajasthan. J. Soil Salinity Water Qual., 2019, 11(1), 56–62.
- Saleh, A., Al-Rowaih, F. and Shehata, M., Hydrogeochemical process operating within the main aquifers of Kuwait. J. Arid Environ., 1999, 42, 195–209.
- CGWB, National compilation on dynamic ground water resources of India, 2017. Central Ground Water Board, Department of Water Resources, River Development and Ganga Rejuvenation, Ministry of Jal Shakti, Government of India. Faridabad, July 2019, p. 298.
- Jackson, M. L., Soil Chemical Analysis, Prentice Hall of India Pvt Ltd, New Delhi, 1973, pp. 134–182.
- Willard, H. H., Meritt, L. L. and Dean, J. A., Instrument Methods of Analysis. D Van Nastrand Company, New York, USA, 1974, 5th edn.
- Richards, L. A., Diagnosis and Improvement of Saline and Alkali Soils, Agricultural Hand Book No. 60, USDA, Washington DC, USA, 1954, p. 160.
- Gupta, R. K., Singh, N. T. and Madhurima, S., Ground water quality for irrigation in India. Technical Bulletin No. 90, Central Soil Salinity Research Institute, Karnal, 1994, p. 23.
- Panse, V. G. and Sukhatme, P. V., Statistical Methods for Agricultural Workers, Indian Council of Agricultural Research, New Delhi, 1985, p. 361.
- Gupta, S. K., Sharma, P. C. and Chaudari, S. K., Hand Book of Saline and Alkali Soils Diagnosis and Reclamation and Management, Scientific Publishers. Jodhpur, 2019, pp. 108–136.
- Pal, S. K., Rajpaul, R., Bhat, M. and Yadav, S. S., Assessment of groundwater quality for irrigation use in Firozpur–Jhirka Block in Mewat district of Haryana, North India. J. Soil Salinity Water Qual., 2018, 10(2), 157–167.
- Kumar, S. K., Rammohan, V., Sahayam, J. D. and Jeevanandam, M., Assessment of groundwater quality and hydrogeochemistry of Manimuktha River basin, Tamil Nadu, India. Environ. Monit. Assess., 2020, 159, 341–351.
- Naidu, M. V. S., Subbaiah, P. V., Radhakrishna, Y. and Kaledhonkar, M. J., Evaluation of ground water quality for irrigation in various mandals of Nellore district in Andhra Pradesh. J. Indian Soc. Soil Sci., 2020, 68(3), 288–297.
- Subbaiah, P. V., Naidu, M. V. S., Radhakrihsna, Y. and Kaledhonkar, M. J., Groundwater quality assessment for Chittoor district of Andhra Pradesh for irrigation purpose and management options. J. Soil Salinity Water Qual., 2020, 12(1), 1–14.
- Houatmia, F. et al., Assessment of groundwater quality for irrigation and drinking purposes and identification of hydro-geochemical mechanisms evolution in northeastern, Tunisia. Environ. Earth Sci., 2016, 75, 746; https://doi.org/10.1007/s12665/016-5441-8
- Loizidou, M. and Kapetanios, E. G., Effect of leachate from landfills on underground quality. Sci. Total Environ., 1993, 128, 69–81.
- Sridharan, M. and Nathan, D. S., Groundwater quality assessment for domestic and agriculture purposes in Puducherry region. Appl. Water Sci., 2017, 7, 4037–4053.
- Isaac, R. K., Khura, T. K. and Wurmbrand, J. R., Surface and subsurface water quality appraisal for irrigation. Environ. Monit. Assess., 2009, 159, 465–473.
- Bhat, M. A., Wani, S. A., Singh, V. K., Sahoo, J., Dinesh, T. and Ramprakash, S., An overview of the assessment of groundwater quality for irrigation. J. Agric. Sci. Food Res., 2018, 9(1), 1–9.
- Ayers, R. S. and Westcot, D. W., Water quality for the irrigation. Irrigation Drainage Paper No. 29, Food and Agriculture Organization of the United Nations, Rome, 1976.
- Jalali, M., Groundwater geochemistry in the Alisadr, Hamadan, western Iran. Environ. Monit. Assess., 2010, 166, 359–369.
- https://www.mapsofindia.com/maps/andhrapradesh/andhrapradeshdistrict.htm (assessed on 2 June 2021).
- Estimation of energetics and energy-use efficiency of rice–green gram sequence in the coastal zone of Andhra Pradesh, India
Abstract Views :126 |
PDF Views:62
Authors
Affiliations
1 Department of Agronomy, Agricultural College, Bapatla 522 101, India, IN
2 Polytechnic, Acharya N.G. Ranga Agricultural University, Lam, Guntur 522 034, India, IN
3 AICRP on Sailine Water Scheme, Agricultural College Farm, Bapatla 522 101, India, IN
4 Department of Crop Physiology, Agricultural College, Bapatla 522 101, India, IN
1 Department of Agronomy, Agricultural College, Bapatla 522 101, India, IN
2 Polytechnic, Acharya N.G. Ranga Agricultural University, Lam, Guntur 522 034, India, IN
3 AICRP on Sailine Water Scheme, Agricultural College Farm, Bapatla 522 101, India, IN
4 Department of Crop Physiology, Agricultural College, Bapatla 522 101, India, IN
Source
Current Science, Vol 124, No 8 (2023), Pagination: 946-955Abstract
A field experiment was conducted at the Agricultural College, Bapatla, AP, India during kharif and rabi seasons from 2019 to 2021 using different establishment and nutrient treatments. The objectives of this study were to evaluate the energetics between the treatments in the rice–green gram. The results indicated that the input and output energy were the highest in the conventional and the lowest in the minimum tillage. Highest total energy productivity and energy use efficiency were recorded with the reduced tillage. In case of nutrient management, the highest input, output energy and energy productivity and energy use efficiency were recorded with inorganic fertilizer + cured poultry manure treatments. It can be concluded that the reduced tillage with the application of inorganic fertilizer + cured poultry manure is the best in the constraints-prone coastal zone with limited irrigation facilities due to low requirement of non-renewable energyKeywords
Coastal zone, crop establishment methods, energy use efficiency, energy productivity, rice and green gram.References
- Gautham Priyanka, G., Sharma, G. D., Ranchana, R. and Lal, B., Effect of integrated nutrient management and spacing on growth parameters, nutrient content and productivity of rice under system of rice intensification. Int. J. Res. Stud. Biosci., 2013, 2(3), 53–59.
- www.rkmp.co.in
- www.Indiastat.com
- Mangal Deep, Mahender Kumar, R., Saha, S. and Singh, A., Rice based cropping systems for enhancing productivity of food grains in India: decadal experience of AICRP. Indian Farm., 2018, 68(01), 27–30.
- Panse, V. G. and Sukhatme, P. V., Statistical Methods for Agricul-tural Workers, Indian Council of Agricultural Research, New Delhi, 1989.
- Gomez, K. A. and Gomez, A. A., Statistical Procedures for Agri-cultural Research (2nd edn), John Wiley and Sons, New York, USA, 1984, p. 680.
- Shahana, F., Balazzii Naaiik, R. V. T., Soundharya, B., Vijaya Lak-shmi, D. and Venkataiah, M., Evaluation of rice (Oryza sativa L.)-based cropping systems for productivity and profitability in the ver-tisols of Telangana, India. Curr. Sci., 2022, 122(6), 699–704.
- Roy, D. C., Ray, M., Sarkar, U. and Patra, B. C., Bio-energy, pro-ductivity and economics of rice (Oryza sativa)-based cropping systems in coastal flood plain of West Bengal, India. Int. J. Bioresour. Stress Manage., 2015, 6(1), 001–006.
- Smil, V., Energy in Nature and Society: General Energetics of Complex Systems, The MIT Press, Cambridge, Mass, USA, 2008.
- Kumar, S. M. G. K., Mishra, V. N., Maruti Sankar, G. R., Patil, S. K., Srivastav, L. K., Thakur, D. S. and Srinivasa Rao, C. H., Soil test based optimum fertilizer dose for attaining yield targets rice under midland Alfisols of eastern India. Commun. Soil Sci. Plant Anal., 2015, 46, 2177–2190.
- Sarkar, U., Rahman, M. M., Nahar, U. A. and Ahmed, M. N., Soil test based inorganic fertilizer and integrated plant nutrition system for rice cultivation in Inceptisols of Bangladesh. Agriculturists, 2016, 14(1), 3342.
- Tuti, M. D., Energy budgeting of colocasia-based cropping systems in the Indian sub-Himalayas. Energy, 2012, 45, 986–993.
- Khan, M. A. and Hossain, S. M. A., Study on energy input, output and energy use efficiency of major jute based cropping pattern. Bangladesh J. Sci. Indust. Res., 2007, 42(2), 195–202.
- Mittal, V. K., Mittal, J. P. and Dhawan, K. C., Research digest on energy requirements in agricultural Section. Energy Requirement Scheme Report, Indian Council of Agricultural Research (ICAR), New Delhi, 1985.
- Devasenapati, P., Senthilkumar, G. and Shanmugam, P. M., Energy management in crop production. Indian J. Agron., 2008, 54(1), 80–90.
- Mohammadshirazi, A., Akram, A., Rafiee, S., Mousavi-Avval, S. H. and Bagheri, K. E., An analysis of energy use and relation bet-ween energy inputs and yield in tangerine production. Renew. Sus-tain. Energy Rev., 2012, 16, 4515–4521.
- Heideri, M. D. and Omid, M., Energy use pattern and econometric models of major greenhouse vegetable productions in Iran. Energy, 2011, 36, 220–225.
- Ziaei, S. M., Mazloumzadeh, S. M. and Jabbary, M. A., Comparison of energy use and productivity of wheat and barley (case study). J. Saudi Soc. Agric. Sci., 2015, 14, 19–25.
- Esengun, K., Gunduz, O. and Erdal, G., Input–output energy analysis in dry apricot production of Turkey. Energy Conver. Manage., 2007, 48, 592–598.
- Mobtaker, H. G., Keyhani, A., Mohammadi, A., Rafiee, S. and Akram, A., Sensitivity analysis of energy inputs for barley produc-tion. Agric., Ecosyst. Environ., 2010, 137, 367–372.
- Imrana, M., Ozçatalbas, O. and Khalid Bashir, M., Estimation of energy efficiency and greenhouse gas emission of cotton crop in South Punjab, Pakistan. J. Saudi Soc. Agric. Sci., 2020, 19, 216–224.
- Zangeneh, M., Omid, M. and Akram, A., A comparative study on energy use and cost analysis of potato production under different farming technologies in Hamdan Province of Iran. Energy, 2010, 35, 2927–2933.
- Mousavi-Avval, S. H., Rafiee, S., Jafari, A. and Mohammadi, A., Energy flow modeling and sensitivity analysis of inputs for canola production in Iran. J. Clean. Prod., 2011, 19, 1464–1470.
- Mousavi-Avval, S. H., Rafiee, S. and Mohammadi, A., Optimiza-tion of energy consumption and input costs for apple production in Iran using data envelopment analysis. Energy, 2011, 36, 909–916.
- Rafiee, S., Mousavi-Avval, S. H. and Mohammadi, A., Modeling and sensitivity analysis of energy inputs for apple production in Iran. Energy, 2010, 35, 3301–3306.
- Unakitan, G., Hurma, H. and Yilmaz, F., An analysis of energy use efficiency of canola production in Turkey. Energy, 2010, 35, 3623–3627.
- Ozkan, B., Akcaoz, H. and Fert, C., Energy input–output analysis in Turkish agriculture. Renew. Energy, 2004, 29, 39–51.
- Nabavi-Pelesaraei, A., Abdi, R. and Rafiee, S., Neural network modeling of energy use and greenhouse gas emissions of watermelon production systems. J. Saudi Soc. Agric. Sci., 2016, 15, 38–47.
- Zahedi, M., Eshghizadeh, H. R. and Mondani, F., Energy use efficiency and economic analysis in cotton production in an arid region: a case study for Isfahan Province, Iran. Int. J. Energy Econ. Policy, 2014, 4(1), 43–52.