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Spatial assessment of climate variability effects on coconut crops in Tamil Nadu State — a case study

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Abstract

Coconut production from the small plantation crop holders of rural areas plays an essential role in the Indian economy. Tamil Nadu is the state which holds the pride of being the largest makers of coconut in the nation. Climatic conditions of the state ensure the considerable production for several years. At present, variability in climate worsens the survival conditions of coconut palm. This paper makes the spatial assessment of climate variability effects on coconut crop felt in Dindigul and Attur Taluks of Dindigul District, Tamil Nadu State, through applying geospatial technologies. This study is carried out by analyzing the climatic parameters and coconut production statistics for the years 2005 to 2014. The proposed area of study has 4,488.16 hectares of coconut plantations on rural areas out of 1,39,415 hectares of total surface area. Increased temperature trends and poorest rainfall patterns faced during the years 2009–2013 influenced coconut productivity negatively on account of lowering the ground water levels. Spatial damage assessment is carried out by using LISS III, IV and high-resolution images. It is identified that the inter-annual disparity of coconut production of 2010–2014 could be evidenced the aberrations due to continuous decline in seasonal rainfall and heavy summer air temperature conditions. This trend was not altered the favorable environs for flowering and growing of coconuts but it claimed lives of coconut trees. Results have showed that the climate and production are interrelated and the annihilation of rural economy because of loss of coconut lives could not be recoverable.

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Data will be made available on reasonable request.

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References

  • Abah RC, Petja BM (2016) Assessment of potential impacts of climate change on agricultural development in the Lower Benue River Basin. Environ Monit Assess 188:683

    Article  Google Scholar 

  • Aggarwal, P.K., Swaroopa Rani, D.N., (2009). Assessment of climate change impacts on wheat production in India. In: Aggarwal, P.K. (Ed.), Global climate change and Indian agriculture – case studies from ICAR Network Project. ICAR, New Delhi: 5–12.

  • Al-doski, J , Mansor, S.B, Shafri, H.Z (2013), ‘Support vector machine classification to detect land cover changes in Halabja City, Iraq’, 2013 IEEE Business Engineering and Industrial Applications Colloquium (BEIAC), IEEE, 353–358.

  • Anwar MR, Liu DL, Macadam I (2013) Adapting agriculture to climate change: a review. Theoret Appl Climatol 113:225–245

    Article  Google Scholar 

  • Barnwal P, Kotani K (2013) Climatic impacts across agricultural crop yield distributions: An application of quantile regression on rice crops in Andhra Pradesh, India. Ecol Econ 87:95–109

  • Byjesh K, Naresh Kumar S, Aggarwal PK (2010) Simulating impacts, potential adaptation and vulnerability of maize to climate change in India. Mitn Adaptn Strat Global Change 15:413–431

    Article  Google Scholar 

  • Coconut Development Board, Handbook and online resources.

  • Chen C, Wang E, Yu Q, Zhang Y (2010) Quantifying the effects of climate trends in the past 43 years (1961–2003) on crop growth and water demand in the North China Plain. Clim Change 100:559–578

    Article  Google Scholar 

  • Chinniah M, Suresh G (2013) Coconut cultivation in Tamil Nadu- an economic analysis. Int J Sci Res 2:62–63

    Google Scholar 

  • Choi Y (2014) ErshadSharifahmadian and ShahramLatifi Bruno (2014), Quality assessment of image fusion methods in transform domain. Int J on Inf Theory 3(1):7–18

    Google Scholar 

  • Keely Dinse (2012), Climate variability and climate change, Michigan Sea Grant.

  • Foody GM, Mathur H (2004) A relative evaluation of multiclass image classification by support vector machines. IEEE Trans Geosci Remote Sens 42(6):1335–1343

    Article  Google Scholar 

  • Ganeshkumar B, Gopala Krishna GVT (2020) Spatiotemporal variability of temperature and its extremes over an agro-ecological region of Tamil Nadu. India Polish J of Environ Stud 29(5):3561–3568

    Article  Google Scholar 

  • Gopala Krishna GVT, Regil R (2014) Agricultural land suitability analysis of a river basin area using remote sensing and GIS. Int J of Geospatial Eng and Technol 1:37–42

    Google Scholar 

  • Haris AVA, Biswas S, Chhabra V, Elanchezhian R, Bhatt BP (2013) Impact of climate change on wheat and winter maize over a sub-humid climatic environment. Curr Sci  206–214

  • Hebbar K.B., Balasimha D., Thomas G.V. (2013) Plantation crops response to climate change: coconut perspective. Climate-Resilient Horticulture: Adaptation and Mitigation Strategies. Springer, India: 177–187.

  • Hebbar R, Ravishankar H. M., ShivamTrivedi, Subramoniam S.R., Uday Raj and V.K. Dadhwal, (2014), Object oriented classification of high resolution data for inventory of horticultural crops, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-8, 2014ISPRS Technical Commission VIII Symposium, 09 – 12 December 2014, Hyderabad, India

  • Jalota SK, Kaur H, Kaur S, Vashisht BB (2013) Impact of climate change scenarios on yield, water and nitrogen-balance and -use efficiency of rice wheat cropping system. Agric Water Manag 116:29–38

    Article  Google Scholar 

  • Jayathilaka PMS, PeeyushSoni SR, Perret JHPW (2011) Spatial assessment of climate change effects on crop suitability for major plantation crops in Sri Lanka. Reg Environ Change 12:55–68

    Article  Google Scholar 

  • Kendall MG (1975) Rank correlation methods. Griffin, London, UK

    Google Scholar 

  • Krishnan P, Swain DK, Chandra Bhaskar B, Nayak SK, Dash RN (2007) Impactof elevated CO2 and temperature on rice yield and methods of adaptation as evaluated by crop simulation studies.Agriculture. Ecosyst & Environ 122:233–242

    Article  Google Scholar 

  • Kumar A, Sharma P (2013) Impact of climate variation on agricultural productivity and food security in rural India (No. 2013-43). Econ Discuss Pap

  • Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259

    Article  Google Scholar 

  • Naresh Kumar S, Aggarwal PK (2013) Climate change and coconut plantations in India: impacts and potential adaptation gains. Agric Syst 117:45–54

    Article  Google Scholar 

  • Naveen F, Rabia S (2013) Temporal analysis of rice yield and climatic trends in Pakistan. World Appl Sci J 24(10):1330–1338

  • Olusina, J.O. and O.M. Odumade (2012), Modeling climatic variation parameters of Nigeria using the statistical downscaling approach, FIG Working Week. Rome, Italy, 6–10 May 2012

  • Parvatha RP (2015) Impacts of climate change on agriculture. Climate resilient agriculture for ensuring food security. Springer, New Delhi, pp 43–90

    Google Scholar 

  • Shakeel A. Khan, Sanjeev Kumar, M.Z. Hussain and N. Kalra (2009) Climate change, climate variability and Indian agriculture: impacts vulnerability and adaptation strategies climate change and crops, Environmental Science and Engineering

  • Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor T, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK/New York

  • Statistical Handbook, Department of Economics and Statistics, Government of Tamil Nadu.

  • Surase RR, Kale KV (2015) Multiple crop classification using various support vector machine kernel functions. INt J of Eng Res and Appl 5(1):103–109

    Google Scholar 

  • Szuster BW, Chen Qi, Borger M (2011) A comparison of classification techniques to support land cover and land use analysis in tropical coastal zones. Appl Geogr 31(2011):525–532

    Article  Google Scholar 

  • Tao F, Yokozawa M, Zhang Z (2009) Modelling the impacts of weather and climate variability on crop productivity over a large area: a new process-based model development, optimization, and uncertainties analysis. Agric for Meteorol 149:831–850

    Article  Google Scholar 

  • Utpala Parthasarathy, Das M.M. and Muralidharan K.(2008). A comparative account of coconut cultivation in Assam and Kerala.Indian Coconut Journal.vol.xxxvi No-11:9–14.

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Authors and Affiliations

  1. Department of Civil Engineering, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, 624 622, India

    Ganeshkumar B &  Gopala Krishna GVT

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  1. Ganeshkumar B
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  2. Gopala Krishna GVT
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Contributions

Both the authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Ganeshkumar B and Gopala Krishna GVT. The first draft of the manuscript was written by Ganeshkumar B and Gopala Krishna GVT commented on previous versions of the manuscript. Authors read and approved the final manuscript.

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Correspondence to Ganeshkumar B.

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Ganeshkumar B, Gopala Krishna GVT Spatial assessment of climate variability effects on coconut crops in Tamil Nadu State — a case study. Theor Appl Climatol 148, 121–129 (2022). https://doi.org/10.1007/s00704-022-03941-9

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  • DOI: https://doi.org/10.1007/s00704-022-03941-9

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