Open Access   Article

Accurate Error Prediction of Sugarcane Yield Using a Regression Model

M. Mohanadevi1 , V. Vinodhini2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-7 , Page no. 66-71, Jul-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i7.6671

Online published on Jul 31, 2018

Copyright © M. Mohanadevi, V. Vinodhini . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

Citation

IEEE Style Citation: M. Mohanadevi, V. Vinodhini, “Accurate Error Prediction of Sugarcane Yield Using a Regression Model”, International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.66-71, 2018.

MLA Style Citation: M. Mohanadevi, V. Vinodhini "Accurate Error Prediction of Sugarcane Yield Using a Regression Model." International Journal of Computer Sciences and Engineering 6.7 (2018): 66-71.

APA Style Citation: M. Mohanadevi, V. Vinodhini, (2018). Accurate Error Prediction of Sugarcane Yield Using a Regression Model. International Journal of Computer Sciences and Engineering, 6(7), 66-71.

VIEWS PDF XML
95 127 downloads 11 downloads
  
  
           

Abstract

In this paper an attempt has been made to review on application of data mining techniques in the field of agriculture. India is the largest producer and consumer of sugar in the world and its most efficient crops in converting solar energy into chemical energy. Sugar-cane is an important commercial crop of the world. About 45 million sugarcane farmers, their dependents and a large agricultural force, constituting 7.5 percent of the rural population, are involved in sugar-cane cultivation, harvesting and ancillary activities. Sugar industries development is backbone to economic development of the nation. In India, Sugar industry is the second largest agro-based industry and it contributes significantly to the socio economic development of the nation. The major Sugar-cane crop growing states in India are Uttar Pradesh, Bihar, Assam, Haryana, Gujarat, Maharashtra, Karnataka and Tamil Nadu. This paper presents state of Karnataka datasets to predict less error rate on better productivity and yield using regression metrics.

Key-Words / Index Term

Agriculture data, Data mining Techniques, Weka tool,Regression Model

References

[1] Ajaykumar ,pritee sharma,”Climate change and sugarcane Productivity in india : An Econometric Analysis”,Journal of social and development sciences vol5.No.2 pp-111-122,Jun 2015 .
[2] Camps-Valls G, Gomez-Chova L, Calpe-Maravilla J, Soria-Olivas E, Martin-Guerrero JD, Moreno J., 2003, "Support vector machines for crop classification using hyperspectral data", Lect Notes Comp Sci 2652: pp. 134–141.
[3] Kumar, A., Sharma, P. & Ambrammal, S. K. (2014). “Climatic Effects on Food Grain Productivity in India: A Crop Wise Analysis”, Journal of Studies in Dynamics and Change, 1(1), 38-48.
[4] Sellam,V, Poovammal, E., “Prediction of Crop Yield using Regression Analysis”, Indian Journal of Science and Technology, Vol. 9, issue.38, pp.1- 5, 2016.
[5] Sujatha, R., Isakki, P., “A study on crop yield forecasting using classification techniques”, International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE), pp.1-4, 2016.
[6] Ankalaki, S., Chandra, N., Majumdar, J., “Applying Data Mining Approach and Regression Model to Forecast Annual Yield of Major Crops in Different District of Karnataka”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 5, issue 2, pp.25-29, 2016.
[7] Kushwaha, A.K., Sweta Bhattachrya, “Crop yield prediction using Agro Algorithm in Hadoop”, International Journal of Computer Science and Information Technology & Security (IJCSITS), Vol. 5, issue.2, pp.271-274, 2015.
[8] Rub, G., “Data Mining of Agricultural Yield Data: A Comparison of Regression Models”, 9th Industrial Conference, Vol.5633, pp.24-37, 2009..
[9] Raorane, A.A., Kulkarni R.V., “Data Mining: An effective tool for yield estimation in the agricultural sector”, International Journal of Emerging Trends & Technology in Computer Science(IJETTCS), Vol. 1, issue 2, pp.75-79, 2012.
[10] Nagarajan,”Sustainable farming practices in sugarcane cultivation”, Kisan world, A journal of agriculture and Rural Development, Vol 40, Jan 2013, pp. 28 – 31.
[11] Nazir A,Jariko,G.A. and Junejo,M.A. (2013) “Factor Affecting Sugarcane Production in Pakistan”Munich Personal RePEc Archive.http://mpra.ub.Uni-menchen.de/50359/.
[12] Dlamini,S Rugambisa,J.I.Masuku,M.B.and Belete,A.(2010),”Technical Efficiency of the small scale sugarcane faramers in Swaziland: A case study of Vuvulane and Big Bed Farmers”, African Journal of Agricultural Research,Vol.5(9).935-940.
[13] Gupta, S., Sen, P. & Srinivasan, S. (2012). “Impact of Climate Change on Indian Economy: Evidence from Food Grain Yields”, Centre for Development Economics Working Paper 218, Delhi.
[14] Srivastava, A. K. & Rai, M. K. (2012). “Sugarcane Production: Impacts of Climate Change and its Mitigation” ,Biodiversitas, 13(4), 214-227.
[15] Kumar, V., Sharma, Y. & Chauhan, S. (2011a). “Impact of Climate Change on the Growth and Production of Saccharum Offcinarum and Magnifera Indica” International Journal of Science Technology and Management, 2(1), 42-47.
[16] Geethalakshmi, V., Lakshmanan, A., Rajalakshmi, D., Jagannathan, R., Sridhar, G., Ramara, Bhuvaneswari, A. P., Gurusamy, K. L. & Anbhazhagan, R. (2011)”Climate Change Impact Assessment and Adaptation Strategies to Sustain Rice Production in Cauvery Basin of Tamil Nadu”, Current Science, 101(03). 342-347.
[17] Masters, G., Baker, P. & Flood, J. (2010)”Climate Change and Agricultural Commodities” CABI Working Paper, 02.
[18] Kalra, N., Chakraborty, D., Sharma, A., Rai, J., Monica, H. K., Subhash, C., Kumar, P., Ramesh, B. S., Barman, D., Mittal, R. B., Lal, M. & Sehgal, M. (2008).”Effect of Increasing Temperature on Yield of Some Winter Crops in Northwest India”, Current Science, 94(1), 82-88.
[19] Kapur, D., Khosla, R. & Mehta, P. B. (2009). “Climate Change: India’s Options”, Economic and Political Weekly, 36(31), 34-42.
[20] Sundar singh and Veeraputhiran,”Enhancing sugarcane productivity”, Kisanworld, A journal of Agriculture and Rural Development’, June 2000, pp. 18-19.
[21] D.Venkatesh,M.Venkateswars :”An overview of the indian sugar industry”, BIMS International Journal of social science research ISSN 2455-4839.