Price Forecasting of Gram and Black Gram across Major States of India: A Comparative Analysis of Deep Learning Models


22

Authors

  • Dr. Chiranjit Mazumder ICAR-IARI, New Delhi
  • Shubho Paul ICAR-IARI, New Delhi
  • Subrata Barman ICAR-IARI, New Delhi
  • Sukhendu Nandi ICAR-IARI, New Delhi
  • Dr. Pramod Kumar ICAR-IARI, New Delhi

https://doi.org/10.56093/ijas.v96i10.175346

Keywords:

Pulses price forecasting, machine learning, deep learning, gram, blackgram

Abstract

Precise price forecasting of pulse crops is essential in effective market interventions, price stabilisation and informed policy decisions. This paper compares the performance of some deep learning models in predicting wholesale prices of two key pulses, gram and black gram, across the major producing states. Four deep learning models, such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU), were employed and compared in terms of RMSE and MAPE to assess their performance. The RNN performed better than other models in most datasets. The projections indicate that the prices of the two crops will show a downward trend in 2026, with the exception of gram in Madhya Pradesh. The results highlight that deep learning models have the potential to improve the accuracy of crop price predictions and of evidence-based policy-making.

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Author Biographies

  • Dr. Chiranjit Mazumder, ICAR-IARI, New Delhi

    Scientist at Department of Agricultural Economics, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India.

  • Shubho Paul, ICAR-IARI, New Delhi

    Ph.D. Scholar at Department of Agricultural Economics, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India

  • Subrata Barman, ICAR-IARI, New Delhi

    Phd Scholar at Department of Agricultural Economics, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India

  • Sukhendu Nandi, ICAR-IARI, New Delhi

    PhD scholar at Department of Agricultural Economics, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India

  • Dr. Pramod Kumar, ICAR-IARI, New Delhi

    Professor and Principal Scientist, Department of Agricultural Economics, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India.

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Published

2026-10-05

How to Cite

Mazumder, C., Paul, S., Barman, S., Nandi, S., & Kumar, P. (2026). Price Forecasting of Gram and Black Gram across Major States of India: A Comparative Analysis of Deep Learning Models. The Indian Journal of Agricultural Sciences, 96(10). https://doi.org/10.56093/ijas.v96i10.175346
Citation