Trends and dynamics of turmeric markets in India

S Aruna Prabha; N Venkatesa Palanichamy; D Murugananthi; K M Shivakumar; M Kalpana; M Balakrishnan

doi:10.14719/pst.6080

Authors

S Aruna Prabha Department of Agricultural and Rural Management, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0002-0605-8903
N Venkatesa Palanichamy Agriculture College and Research Institute, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0002-1273-7347
D Murugananthi Directorate of Agribusiness Development, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0002-0134-6631
K M Shivakumar Department of Agricultural Economics, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0001-8561-5511
M Kalpana Office of the Dean (Agri), Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0002-0201-6968
M Balakrishnan Department of Food Process Engineering, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0003-0148-2809

DOI:

https://doi.org/10.14719/pst.6080

Keywords:

price cycle, price trend, seasonal index, turmeric

Abstract

As the leading global producer and consumer of turmeric, India has several major markets, including Erode, Nizamabad, Duggirala, and Sangli. Turmeric prices have exhibited cyclical patterns and fluctuations, significantly impacting farmers' incomes. Analyzing the trend, seasonal, and cyclical aspects of turmeric prices can aid in forecasting peak and low periods, thereby minimizing cultivation risks. Data spanning 14 years (2010-2023) was gathered from key markets to examine price behaviour, including the Erode Regulated Market in Tamil Nadu, Nizamabad in Telangana, and Sangli in Maharashtra. Researchers applied a regression model to analyze price trends, while seasonal indices were used to identify seasonality. The Bry-Boschan algorithm, implemented through MATLAB software, was used to determine price cycles. The study revealed an upward price trend across all major Indian turmeric markets over the years and identified cyclical behaviour, with cycles lasting 2-4 yrs. Notably, the duration of price slumps exceeded that of booms. By anticipating these cycles, farmers make informed decisions regarding sowing and selling, potentially reducing risks associated with turmeric cultivation. Implementing a Minimum Support Price could help offset rising labour costs and falling prices, encouraging farmers to continue turmeric cultivation. Additionally, adopting a pricing system based on curcumin content for Tamil Nadu turmeric could yield better prices.

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