FACTORS INFLUENCING THE PROFITABILITY OF SUGARCANE PRODUCTION IN TAMIL NADU

R. Dhanabal; Dr. K. Rajesh

FACTORS INFLUENCING THE PROFITABILITY OF SUGARCANE PRODUCTION IN TAMIL NADU

Authors

R. Dhanabal

Ph.D., Research Scholar, PG & Research Department of Economics, National College (Autonomous), Tiruchirappalli - 620 001, India.

Dr. K. Rajesh

Assistant professor & Research Advisor, PG & Research Department of Economics, National College (Autonomous), Tiruchirappalli – 620 001, India.

Keywords:

Sugarcane Production, Tamil Nadu, Profitability, Cost Benefit Analysis, Market Dynamics, Government Policies, Technological Innovation

Synopsis

This study explores the multifaceted factors that influence the profitability of sugarcane production in Tamil Nadu, India. By analyzing various economic, environmental, and social dimensions, it offers insights into the challenges and opportunities faced by sugarcane farmers in the region. Firstly, the study investigates the cost structure of sugarcane cultivation, including inputs such as land, labor, seeds, fertilizers, and machinery. It examines how efficient cost management practices can significantly impact the overall profitability of sugarcane farming. Secondly, market dynamics play a crucial role in determining profitability. The study delves into factors such as demand-supply dynamics, price fluctuations, and market integration, shedding light on their implications for farmer incomes. Government policies constitute another significant aspect influencing profitability. Analysis of policies related to minimum support prices, subsidies, and procurement mechanisms provides insights into their effects on farmer profitability and market stability. Moreover, technological innovation emerges as a key determinant of profitability. The study evaluates the adoption of modern agricultural technologies, such as mechanization and biotechnology, and their potential to enhance productivity and efficiency in sugarcane farming. Lastly, the study considers environmental and social dimensions. It examines the environmental footprint of sugarcane cultivation, including issues such as water usage, soil health, and pesticide management. Additionally, it discusses social factors such as labor dynamics, gender roles, and community welfare, emphasizing their significance in shaping the profitability of sugarcane production. Through a comprehensive analysis of these factors, this study provides valuable insights for policymakers, researchers, and practitioners seeking to promote sustainable and profitable sugarcane farming practices in Tamil Nadu.

References

[1] FAO. (2020). Agricultural innovation and technology adoption: Issues and policy options. Food and Agriculture Organization of the United Nations. https://doi.org/10.4060/ca9191en

[2] Government of Tamil Nadu. (n.d.). Department of Agriculture. https://www.tn.gov.in/department/3

[3] International Labour Organization. (2020). Labour standards in agriculture: Promoting labour rights, safety and health, and combatting child labour. International Labour Organization.https://www.ilo.org/wcmsp5/groups/public/---ed_norm/---relconf/documents/meetingdocument/wcms_755688.pdf

[4] Kadam, S. B., & Jadhav, A. S. (2015). Sugarcane cultivation: The need for sustainable approach. Journal of Pharmacognosy and Phytochemistry, 4(4), 88-94.

[5] Ministry of Agriculture & Farmers Welfare. (2020). Agricultural statistics at a glance 2019. Government of India. http://agricoop.nic.in/sites/default/files/ASAG%202019_0.pdf

[6] Pimentel, D., & Burgess, M. (2013). Soil erosion threats to food production. Agriculture, 3(3), 443-463. https://doi.org/10.3390/agriculture3030443

[7] Sarker, P. K., & O'Connor, K. M. (2018). Effects of climate change on sugarcane production. Sugar Tech, 20(4), 435-448. https://doi.org/10.1007/s12355-018-0602-1

[8] Singh, S. P., Pandey, S. K., & Jaiswal, U. S. (2019). Sugarcane production technologies. Springer. https://doi.org/10.1007/978-3-030-16857-4

[9] Sugarcane Breeding Institute. (n.d.). Sugarcane varieties. Indian Council of Agricultural Research. https://www.sugarcane.res.in/index.php/sugarcane-varieties

[10] World Bank. (2020). Agriculture and rural development. World Bank Group. https://www.worldbank.org/en/topic/agriculture/overview

[11] RAJKUMAR, R., & SUDHA, G. (2013). FIBROMYALGIA–AN OUTCOME OF WORK LIFE IMBALANCE.

[12] Senthilkumar, K., & Rajkumar, R. (2019). A study on women entrepreneurship in Tanjore region. International Conference on Management Research, 2(2), 9-13.

[13] Senthilkumar, K., & Rajkumar, R. (2018). Analysis of consumer behaviour towards various cement brands grades with special reference to Thanjavur district. International Conference on Management Research, 1(1), 4-8.

[14] Sudha, G., & Rajkumar, R. (2014). Influence of gender on better balance. Journal of Business Studies, 1(SPL), 47-54. University of Jaffna.

[15] Sudha, G., & Rajkumar, R. (2012). Work life balance for working women - Is it so tough. Sankhya - International Journal of Management and Technology, 3(2), 100-103. SIMS Publication.

[16] Senthilkumar, K., K. Iyyappan, and S. Subramaniam. "Customer awareness on electronic banking in Thanjavur town—An empirical study." 2012-International Conference on Management Issues in Emerging Economies (ICMIEE). IEEE, 2012.

[17] Senthilkumar, K. (2014). Medical tourism: Changing scenario in health care sector. Holy Grace Management Review, 6(1), 118-122.

[18] Senthilkumar, K. (2014). Analysis of consumer behavior towards various cement brands & grades with special reference to Thanjavur district. Emerging Paradigms in Management Research, 3(2), 4-9.

[19] Senthilkumar, K. (2012). A comparative study on innovation management of health care services in rural India with other developing countries of Asia. In Conference Proceedings of Strategic Trends on Innovations & Creativity in Management Practices, 2(1), 31.

[20] Senthilkumar, K. (2012). Challenges and opportunities with special reference to Indian cement industry. Sankhya International Journal of Management and Technology, 3(1), 252-255.

[21] Senthilkumar, K. (2011). Evolution and evaluation of Indian cement industry. International Journal of Applied Management Research (IJAMR), 3(1), 779-784. IJAMR.

[22] Kasthuri, S., and A. Nisha Jebaseeli. "An artificial bee colony and pigeon inspired optimization hybrid feature selection algorithm for twitter sentiment analysis." Journal of Computational and Theoretical Nanoscience 17.12 (2020): 5378-5385.

[23] Kasthuri, S., and A. Nisha Jebaseeli. "Study on social network analysis in data mining." International Journal of Analytical and Experimental Modal Analysis (IJAEMA),(UGC CARE-A Journal), Impact Factor 6.3 11.VIII (2019): 111-116.

[24] Kasthuri, S., and A. Nisha Jebaseeli. "Review analysis of Twitter sentimental data." Bioscience Biotechnology Research Communications (BBRC),(UGC CARE Journal-Web of Science), Special Issue 13.6 (2020): 209-214.

[25] Kasthuri, S., and A. Nisha Jebaseeli. "Social network analysis in data processing." Adalya Journal,(UGC CARE-B Journal–Web of Science), Impact Factor 5 (2020): 260-263

[26] Kasthuri, S., and A. Jebaseeli Nisha. "Review on social network analysis in data mining." Infokara Res 8.12 (2019): 1168-1172.

[27] Ambika, G., and D. P. Srivaramangai. "A study on security in the Internet of Things." Int. J. Sci. Res. Comput. Sci. Eng. Inform. Technol 5.2 (2017): 12-21.

[28] Ambika, G., and P. Srivaramangai. "Encrypted Query Data Processing in Internet Of Things (IoTs): CryptDB and Trusted DB." (2018).

[29] Ambika, G. "Advanced Human Activity Recognition: Leveraging Adaptive Neural Networks and Diverse Machine Learning Algorithms on IoT Data." Fuzzy Systems and Soft Computing, vol. 19, no. 02(V), 2024, pp. 11–17.

[30] G. Ambika, “IoTCryptDB: Encrypted query data processing in Internet of Things,” International Journal of Scientific Research in Computer Science Applications and Management Studies, vol. 7, no. 4, p. 18, Jul. 2018.

[31] Ambika, G. "Processing Over Encrypted Query Data in Internet of Things (IoTs): CryptDBs, MONOMI and SDB." International Journal on Recent and Innovation Trends in Computing and Communication, vol. 6, Issue-8, 2018, p. 8.

[32] Shanti, M. A., and K. Saravanan. "Knowledge data map—A framework for the field of data mining and knowledge discovery." International Journal of Computer Engineering & Technology 8.5 (2017): 67-77.

[33] Shanti, M. A., and K. Saravanan. "An Effect of Data Mining Techniques in Public Healthcare-A Case Study." International Journal of Civil Engineering and Technology 9.9 (2018): 115-122.

[34] Shanti, M. A. "A Study to Analyse the Quality of Work Life with Special Reference to Private Sector Bank Employees in Kumbakonam Town of Thanjavur District." Our Heritage, vol. 68, 2020.

[35] Shanti, M. A. "Earthquake Prediction Using SVM Based Time Predictable Technique." International Journal of Computer Sciences and Engineering (IJCSE), vol. 7, no. 4, 2019, pp. 2347–2693.

[36] Shanti, M. A., and K. Saravanan. "Wartortle—A Data Mining and Knowledge Discovery Suite for Data Analysis and Reporting." International Journal of Applied Engineering Research, vol. 13, no. 10, 2018, pp. 7835–7841.

[37] Amalarethinam, George. "DI, Vaaheedha Kfatheen. S,“Max-min Average Algorithm for Scheduling Tasks in Grid Computing Systems”." International Journal of Computer Science and Information Technologies 3.2 (2012): 3659-3663.

[38] Amalarethinam, G. D. I., and V. S. Kfatheen. "Max-Min average algorithm for scheduling tasks in grid computing systems." International Journal of Computer Science and Information Technologies 3.2 (2014): 3659-62.

[39] Sumathy, P., and Ahilan Chandrasekaran. "An Optimized Image Pre-Processing Technique for Face Emotion Recognition System." Annals of the Romanian Society for Cell Biology 25.6 (2021): 6247-6261.

[40] Agilan, C. "A Comprehensive Survey on Emotion Recognition Techniques Using Image Processing." Indian Journal of Natural Sciences, vol. 16, no. 90, 2025, pp. 96569-96579. Indian Journal of Natural Sciences.

[41] Agilan, C. "Enhancing Human Emotion Detection through Optimization-Driven CNN Models." Indian Journal of Natural Sciences, vol. 16, no. 90, 2025, pp. 96422-96433. Indian Journal of Natural Sciences.

[42] Agilan, C. "Energy Efficient Clustering and Dynamic Slot Allocation for Wireless Sensor Networks." IEEE Explore, vol. 1109, ACOIT62457, 2024, https://ieeexplore.ieee.org/xpl/conhome/10939027/proceeding.

[43] Agilan, C. "Optimization-Based Clustering Feature Extraction Approach for Human Emotion Recognition." The Scientific Temper, vol. 15, no. spl.04, 2024, pp. 24-31. Web of Science.