## 3 The Critical Importance of Product Identity in Agricultural Supply Chains
### Challenges and Barriers to Adoption  
Despite its promise, implementing blockchain in agricultural supply chains comes with significant challenges. The literature and industry reports point to several barriers that must be addressed:  
* Technical scalability and performance: Public blockchains such as Bitcoin or Ethereum are not designed to handle the high volume of transactions that a busy supply chain could generate (every farm harvest, truck shipment, warehouse check-in, among others). Throughput and latency can become issues if every supply chain event were recorded on-chain. Even in private or permissioned blockchains, transaction processing capacity is a concern [8]. Storing large datasets (sensor readings, certificates, images) directly on the blockchain is impractical due to the \"data explosion\" it would cause [8]. Solutions like off-chain storage (e.g., using IPFS or cloud databases for heavy data and storing only hashes on-chain) are being explored to alleviate this [8]. Nonetheless, designing a system that scales to millions of products while keeping performance acceptable is non-trivial. Technical improvements (such as more efficient consensus algorithms, sharding or layer-2 networks) are still evolving to meet these needs. * Integration and interoperability: Agricultural businesses have existing ERP systems, databases, and IoT platforms for supply chain management. Introducing blockchain should ideally complement these, not entirely replace them. A major barrier is connecting legacy systems to blockchain networks in a seamless way. Data standards become important, as different parties might use different formats for product IDs, batch numbers, or timestamps. Without common standards (for example, GS1 standards for product identification), feeding data into a blockchain and retrieving them for various enterprise systems can be challenging. Interoperability is also a concern between different blockchain platforms: if one supplier uses one blockchain system and another uses a different one, linking those for a unified view is complex. Companies worry about vendor lock-in and whether a chosen blockchain solution will be compatible with others in the future. Efforts are underway to develop interoperability protocols  
Figure 6: Comparison of proposed framework with real-world cases. and unified data standards for blockchain traceability, but this remains a barrier to frictionless adoption. * Data privacy and confidentiality: While transparency is a benefit, supply chain participants often have legitimate concerns about protecting sensitive business information. A farmer or trader might be reluctant to put pricing, exact locations, or client details on a ledger that others (even permissioned parties) can see. Public blockchains are fully transparent, which is usually unacceptable for proprietary supply chain data. Permissioned (consortium) blockchains limit visibility to approved members, but even then, companies may want to keep certain data (such as formulas or supplier identities) confidential. Privacy-enhancing techniques are thus crucial, including encryption of data, hashing sensitive attributes (only storing a digest on-chain), or using permissioned channels where only relevant parties see certain transactions. Research has proposed hybrid solutions, such as combining a public blockchain for overall auditability with off-chain or private side-chains for sensitive details [59]. Another approach is using zero-knowledge proofs to validate events (e.g., a compliance check passed) without revealing the underlying data. Ensuring that blockchain implementation complies with data protection laws (like GDPR in Europe) is an added challenge, requiring careful design so that personal data are not inadvertently exposed on an immutable ledger. * Economic costs and incentives: Adopting blockchain can be expensive, at least initially. There are costs for developing or subscribing to the platform, integrating IT systems, and possibly investing in new hardware (such as scanners or IoT sensors for data input).