The grain supply chain not only broadens the financing channels for small and medium-sized enterprises in the supply chain and strengthens the cohesion of the supply chain but also opens up new business models and sources of profit for commercial banks. This article aims to study the use of advanced information technologies such as mobile Internet, Internet of Things (IoT) transmission, BT, and other advanced information technologies to design intelligent grain depot integrated systems based on the IoT technology, in accordance with the principles of practicality and advancement, to realize the informatization of the daily management of the grain depot and provide construction experience for the informatization construction of the food industry. This article proposes a detailed summary of several models of agricultural supply chain finance from the perspective of supply chain management and analyzes the applicable conditions and basic processes of these models. It also analyzes the structure of the agricultural supply chain through typical cases, introduces the operation of supply chain finance, and evaluates and analyzes its effectiveness and problems. The experimental results in this paper show that, compared with other storage methods, this solution has obvious advantages in data query efficiency and data storage cost. Without a central server, the entire distributed system will have a certain degree of efficiency, reliability, and cost-effectiveness. When the amount of grain data reaches 100,000, 1 million, and 10 million, the system data integrity check time is 0.0263 seconds, 0.3251 seconds, and 1.5032 seconds, respectively. The program seems very useful.

中文翻译：

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基于物联网和区块链的食品供应链金融新模式

粮食供应链不仅拓宽了供应链中中小企业的融资渠道，增强了供应链的凝聚力，也为商业银行开辟了新的商业模式和利润来源。本文旨在研究利用移动互联网、物联网（IoT）传输、BT等先进信息技术，设计基于物联网技术的智能粮库综合系统，遵循以下原则：实用性和先进性，实现粮库日常管理信息化，为食品行业信息化建设提供建设经验。本文从供应链管理的角度对农业供应链金融的几种模式进行了详细总结，并分析了这些模式的适用条件和基本流程。还通过典型案例分析了农业供应链的结构，介绍了供应链金融的运作，并对其有效性和存在的问题进行了评价和分析。本文的实验结果表明，与其他存储方式相比，该方案在数据查询效率和数据存储成本上具有明显优势。如果没有中央服务器，整个分布式系统就会有一定的效率、可靠性和成本效益。当谷物数据量达到10万、100万、1000万时，系统数据完整性检查时间为0.0263秒，0.0263秒。分别为 3251 秒和 1.5032 秒。该程序似乎非常有用。