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Dairy Supply Chain (DSC) is an important component in the agri-food sector which involves a lot of inter connected processes starting from the dairy farmers to the consumers. DSC faces significant challenges due to the highly perishable nature of its products thereby making it especially sensitive to fluctuations in demand and spoilage. This review synthesizes advances in the various research areas of DSC from the chronological period 2010 to 2025 to help identify the Machine Learning (ML) models, real-time IoT integration, federated learning for data privacy and sustainability-oriented performance measures. These contributions further aim towards improvement of operational efficiency, reduce wastage and enable actionable decision making across DSC.

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Exploring Machine Learning Applications for Demand Forecasting and Performance Enhancement in Dairy Supply Chains

  • 会议论文

  • 发表日期：

    2026年

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  • Jahida N. Khan,
  • Venkatesh M. Kulkarni,
  • Girish R. Naik,
  • Poornima G. Naik

摘要

Dairy Supply Chain (DSC) is an important component in the agri-food sector which involves a lot of inter connected processes starting from the dairy farmers to the consumers. DSC faces significant challenges due to the highly perishable nature of its products thereby making it especially sensitive to fluctuations in demand and spoilage. This review synthesizes advances in the various research areas of DSC from the chronological period 2010 to 2025 to help identify the Machine Learning (ML) models, real-time IoT integration, federated learning for data privacy and sustainability-oriented performance measures. These contributions further aim towards improvement of operational efficiency, reduce wastage and enable actionable decision making across DSC.