To realize efficient cooperation among tea plantations, manufacturers, logistics, and sellers, the tea production and supply chain (PSC) benefits participating enterprises by coordinating tea planting, product processing, transportation, and product sales links. However, the current tea PSC lacks resourcesaving automatic control and suffers from the effect of counterfeit tea products and inefficient supervision.To address these problems, in this work, blockchain and Internet of Things (IoT) technologies are applied to turn the tea PSC around with efficient automation and decentralized supervision. Specifically, we propose DeTea, a blockchain-IoT-empowered decentralized framework, for chain-wide tea counterfeiting supervision and automatic environment management. On the one hand, for the benefit of tea customers, an incentive scheme is designed based on blockchain technology to attract tea PSC participants and decentralized detectors to report dishonest participants, which can motivate the good behaviors of the participating enterprises for a healthier tea market. On the other hand, for the benefit of practitioners of tea products, we realize the automation of environment monitoring and equipment control via IoT technology. Moreover, we design an improved adaptive weighted data fusion algorithm for accurate IoT data and efficient resource allocation, and present an optimal irrigation strategy for automatic plantation environment adjustment. To evaluate the proposed solution, a prototype is implemented by designing a blockchain infrastructure with ten main smart contracts and constructing an IoT-based system sandbox for automatic environment monitoring and resource allocation. Experimental results demonstrate the high throughput of DeTea and the efficiency of resource-saving automation. This work introduces blockchain and IoT technologies to tea PSC for full-process traceability and automatic environment control, which is expected to extend to other agricultural products to ensure the safety, reliability, and efficiency of agricultural traceability systems.