[Objective] Agricultural operators are the initial origin and key contributors to smart agriculture data, and the protection of their data rights and interests urgently needs to be addressed. China's smart agriculture is currently developing rapidly, and the digitalization level of agricultural production continues to rise. However, agricultural operators' data rights and interests have not received sufficient attention. What rights and interests they should enjoy and how these can be realized have become pressing practical issues. The aim of this research is to reveal the nature and connotation of agricultural operators' data rights and interests, analyze the dilemmas in rights protection, and propose institutional responses, and form a virtuous cycle of "data generation-value creation-rights feedback", thereby promoting the healthy and sustainable development of smart agriculture. [Methods] Literature review, normative analysis, case analysis and comparative analysis were adopted. The literature review was conducted to examine existing research progress and to identify the research questions. Through normative analysis and systematic interpretation of the data rights rules in China's existing legal norms and relevant policy documents, the nature of rights and interests of agricultural operators' non-personal agricultural data was defined. Representative institutional norms of foreign agricultural data governance were compared to distill referable experience for the protection of agricultural data rights and interests. Typical cases were used to concretely illustrate the practical dilemmas in protecting agricultural operators' data rights and interests in the development of smart agriculture. [Results and Discussions] The results demonstrated that agricultural operators' data rights and interests constituted a legal interest arising from their contribution as a data source, protected by civil law but not elevated to a right. The subjects of rights and interests included rural contract-management households, family farms, specialized farmer cooperatives, agricultural enterprises, etc. The object was non-personal agricultural data within agricultural data. Based on the theories of fruits of rights and "digital labor", agricultural operators held property-type rights and interests in their non-personal data. It further revealed that in practice, the protection of agricultural operators' data rights and interests faced fourfold dilemmas. First, the lack of a basis for claims: Existing laws do not provide protection for non-personal agricultural data. Second, the imbalanced autonomy of will: Contract terms were unilaterally drafted by data processors, leaving agricultural operators with limited bargaining power and substantive choice. Third, the technological control or constraints: Data processors locked in data through technical means, while the absence of technical standards for agricultural data interoperability made data portability unattainable. Fourth, the difficulties in rights and interests relief: The highly concealed technical nature of data processing made it hard for agricultural operators to trace data flows and to prove damages and causation, coupled with the generally low digital literacy of agricultural operators and their fragmented strength, which made it challenging for them to enforce their rights. [Conclusions] A multi-layered institutional framework encompassing "rights confirmation - contractual checks and balances - data governance - mechanism innovation" should be established to safeguard agricultural operators' data rights and interests. At the legal level, the content of agricultural operators' data property interests should be clearly defined, and non-exclusive data interests including the right to know, to access and control, to portability, and to benefit should be constructed based on the bundle-of-rights theory. At the contractual level, relevant authorities should formulate model texts for standard agricultural data contracts to rectify the substantive inequality between agricultural operators and data controllers. In terms of data governance, technical rules and legal norms should be integrated by unifying data technical standards, refining data classification and grading, and establishing compliance certification systems. In the dimension of mechanism innovation, considering the particularities of agricultural operators' data, the introduction of a collective governance model through data trusts should be explored, relying on specialized operation and collective management to ensure the effective realization of data rights and interests.