Cold Chain Logistics Optimization: Integrating IoT and Data Analytics to Reduce Post-Harvest Loss in the United States Perishable Food Supply Chain: A Case Study of Dole Food Company

Food spoilage in the United States is not simply a logistical inconvenience. It is one of the most underappreciated sources of economic and environmental waste in the country's food system. Fruits, vegetables, dairy products, and meat are routinely lost during storage and transport not because operators lack the will to prevent it, but because conventional cold chain management has historically lacked the tools to detect and respond to deteriorating conditions before damage becomes irreversible. This paper examines how the convergence of Internet of Things (IoT) sensing networks and data analytics platforms is reshaping what cold chain operators can know, predict, and act on. Drawing on the architecture of U.S. cold chain systems and operational evidence from Dole Food Company, the paper argues that the transition from reactive temperature management to anticipatory, data-driven oversight is both technically achievable and commercially justified. All references cited in this study are drawn from peer-reviewed and institutional sources published no later than 2024.