Agricultural Science Digest

  • Chief EditorArvind kumar

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Agricultural Science Digest, volume 36 issue 4 (december 2016) : 261-266

Classification of agricultural productivity index of Cauvery delta zone using artificial neural network

G. Manimannan*1, C. Arulkumar2, R. Lakshmi Priya3
1<p>Department of Statistics, DRBCCC Hindu College,&nbsp;Pattabiram, Chennai-60 072, Tamilnadu, India.</p>
Cite article:- Manimannan*1 G., Arulkumar2 C., Priya3 Lakshmi R. (2016). Classification of agricultural productivity index of Cauvery deltazone using artificial neural network . Agricultural Science Digest. 36(4): 261-266. doi: 10.18805/asd.v0iOF.4436.

In this study a novel trial was made to classify the Agriculture Productivity Index (API) for the major crops of Cauvery Delta Zone (CDZ) using neural network and statistical methods. At present the CDZ includes, Tanjavur, Tiruvarur, Nagapattinam, Tiruchirapalli, Pudukottai and Ariyalur districts. The crops grown in the Cauvery delta zone were categorized into four major groups such as, cereals, pulses, oilseeds and cash crops. The data for the period of 2003 to 2012 were collected from the Department of Economics and Statistics, Chennai, Tamilnadu. Enyedi’s method was adopted to calculate the API and based on the index the regions were classified by neural network method using Learning Vector Quantization (LVQ). The classification was cross validated statistically, using Multivariate Discriminant Analysis (MDA). The classification results achieved 83% in LVQ and 97% MDA respectively in the entire period of study. The results are obtained as Greater Productivity Regions (GPR), Moderate Productivity Regions (MPR) and Lesser Productivity Regions (LPR)  and are plotted in Tamil Nadu spatial map with different colours. 

  1. Anderson TW (1984) An Introduction to Multivariate Statistical Analysis, 2/e, John Wiley and Sons, Inc., New York.

  2. Jasbir Singh, Dhillon S S (2002) Agricultural Geography, Tata McGraw Hill Publishing Company Limited, New Delhi.

  3. Kalpana Sahoo, Narayan Sethi (2012) Investigating the Impact of Agriculture and Industrial Sector on Economic Growth of India

  4. Industrial Sector on Economic Growth of India. OIDA International Journal of Sustainable Development 05:05, pp. 11-22.

  5. Kohonen T (2001) Learning vector quantization. Springer Berlin Heidelberg.

  6. Shafi M (1983) Agricultural Productivity and Regional Imbalances – A study of Uttar Pradesh. Concept Publishing Company, New Delhi.

  7. Anonymous, (2016). Season and Crop Report, Tamilnadu (Various Issues), published by Department of Economics and Statistics, Chennai.

  8. Anonumous (2012-13). Statistical Hand Book of Tamilnadu (2012-2013), Department of Economics and Statistics, Chennai. (


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