Jowar Price Forecasting Using Different Time Series Models in Ballari District, Karnataka, India

As a staple food grain and fodder source, its price trends directly impact both farmers’ incomes and regional food security. Given the increasing volatility in agricultural markets due to climatic, policy and global economic influences, accurate price forecasting has become essential for informed decision making by farmers, traders and policymakers. Sorghum (Jowar) plays a critical role as a staple food and fodder crop in semi-arid regions of India, especially in Karnataka. This study focuses on forecasting the wholesale prices of Jowar in the Ballari market using monthly data spanning 2002 to 2024. To capture seasonality and complex patterns in the data, different time series models such as ARIMA, SARIMA, BATS, and TBATS were evaluated. Model accuracy was evaluated by using RMSE and MAPE metrics. Among the models, the BATS model exhibited superior forecasting accuracy with the lowest RMSE (87.1809) and MAPE (5.0855) values when compared to other fitted models. BATS model appears to have adequately captured the patterns in the time series data, as indicated by the p-value. This suggests that the model's residuals are approximately white noise, which is a good indication of model fit. Descriptive statistics and seasonal indices highlighted July and August as peak pricing months, aligning with demand-supply dynamics. The findings underscore the value of advanced forecasting methods in supporting informed decision-making for farmers, traders, and policymakers in the region. Seasonal indices confirmed peak prices during July and August, aligning with observed demand-supply dynamics. These insights offer valuable guidance for farmers, traders, and policymakers to make informed decisions related to production, marketing, and pricing strategies. As agricultural markets grow increasingly volatile, integrating advanced statistical forecasting tools becomes not only beneficial but essential for ensuring food security and economic stability in the region.

Authors

Institutions

Publication Details

Journal
Archives of Current Research International
Published
2025-07-24
DOI
https://doi.org/10.9734/acri/2025/v25i71382
Primary Topic
Agricultural Economics and Practices
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Jowar Price Forecasting Using Different Time Series Models in Ballari District, Karnataka, India

Vasudeva Naik K, Amaresh, Sajitha Vijayan M
Archives of Current Research International
Agricultural Economics and Practices
article

Jowar Price Forecasting Using Different Time Series Models in Ballari District, Karnataka, India

Vasudeva Naik K, Amaresh, Sajitha Vijayan M
article en

Abstract

As a staple food grain and fodder source, its price trends directly impact both farmers’ incomes and regional food security. Given the increasing volatility in agricultural markets due to climatic, policy and global economic influences, accurate price forecasting has become essential for informed decision making by farmers, traders and policymakers. Sorghum (Jowar) plays a critical role as a staple food and fodder crop in semi-arid regions of India, especially in Karnataka. This study focuses on forecasting the wholesale prices of Jowar in the Ballari market using monthly data spanning 2002 to 2024. To capture seasonality and complex patterns in the data, different time series models such as ARIMA, SARIMA, BATS, and TBATS were evaluated. Model accuracy was evaluated by using RMSE and MAPE metrics. Among the models, the BATS model exhibited superior forecasting accuracy with the lowest RMSE (87.1809) and MAPE (5.0855) values when compared to other fitted models. BATS model appears to have adequately captured the patterns in the time series data, as indicated by the p-value. This suggests that the model's residuals are approximately white noise, which is a good indication of model fit. Descriptive statistics and seasonal indices highlighted July and August as peak pricing months, aligning with demand-supply dynamics. The findings underscore the value of advanced forecasting methods in supporting informed decision-making for farmers, traders, and policymakers in the region. Seasonal indices confirmed peak prices during July and August, aligning with observed demand-supply dynamics. These insights offer valuable guidance for farmers, traders, and policymakers to make informed decisions related to production, marketing, and pricing strategies. As agricultural markets grow increasingly volatile, integrating advanced statistical forecasting tools becomes not only beneficial but essential for ensuring food security and economic stability in the region.

Archives of Current Research InternationalVol. 25(7)
University of Agricultural Sciences Raichur (IN)
Openalex Percentile: Top 72%
Agricultural Economics and Practices
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.