Agri-Business Decision Support through Price Forecasting: A Case Study of Tomato Market Dynamics in Kolar, Karnataka, India
Niranjan Reddy P *
PGDM (ABM), National Institute of Agricultrural Extension Management (MANAGE), Rajendranagar, Hyderabad - 500030, India.
V Pavan
Institute of Agribusiness Management, University of Agricultural Sciences, Bangalore-560065, India.
Boya Vaishnavi
Bharatiya Engineering Science & Technology Innovation University (BESTIU), Gownivaripalli, Gorantla, Andhra Pradesh - 515231, India.
Vinay H T
Department of Agricultural Statistics, Central Silk Board, Bangalore, Karnataka - 560068, India.
Jahnavi A P
University of Agricultural Sciences Raichur, Karnataka- 584101, India.
Gaddala Prem
Department of Statistics and Mathematics, Prof. Jayashankar Telangana Agricultural University, Hyderabad, Telangana - 500030, India.
*Author to whom correspondence should be addressed.
Abstract
Tomato is one of the most important horticultural crops in Karnataka, playing a key role in the state’s agro-processing and food industries, and making a notable contribution to its economy. Despite substantial production, the tomato market in Karnataka often experiences high price volatility, with drastic fluctuations occurring over short periods. Such instability poses significant challenges to both farmers and consumers. To address this issue, time series forecasting models-namely Exponential Smoothing, ARIMA, SARIMA, and BATS-were applied to predict tomato prices in the Kolar market of Karnataka using monthly wholesale price data from 2010 to 2024. Among these, the BATS model demonstrated superior performance based on model validation criteria such as Root Mean Square Error (RMSE) of 869.70. The BATS model was employed to forecast the monthly tomato prices for the year 2025, thereby enabling farmers, traders, and policymakers to make informed decisions.
Keywords: Forecasting, exponential smoothing, ARIMA, SARIMA, BATS