Maize white spot, caused by the bacterium Pantoea ananatis, is one of the most detrimental diseases of maize in Brazil and has contributed to significant yield reduction. In this study, P. ananatis isolates were recovered from maize white spot lesions, healthy leaves, corn crop residues and Digitaria horizontalis. All the bacterial isolates were identified and characterized by morphological traits analysis, acid production from sorbitol and glycerol, ice nucleation activity, metabolic fingerprint similarities and molecular analysis by Polymerase Chain Reaction with species-specific primers for P. ananatis (ANAF/ANAR). Results showed that isolates recovered from maize white spot lesions were similar to those isolates collected from other sources. It suggests that corn crop residues, D. horizontalis and healthy leaf surface of the corn plant itself, could be a source of survival for P. ananatis.

The immutability of data stored in a blockchain is a crucial pillar of trust in this technology, which has led to its increasing adoption in various use cases. However, there are situations where the inability to change or delete data may be illegal. European Union’s General Data Protection Regulation (GDPR)—applying to any company processing personal data from European citizens—explicitly entitles individuals to the right to rectification and the right to be forgotten. In this paper, we describe the design of a system to deploy and process survey data in a GDPR-compliant manner. It combines an Hyperledger Fabric blockchain to ensure that data cannot be tampered with and InterPlanetary File Systems (IPFS) for storage. With the proposed arrangement, we reap several security benefits enabled by blockchain’s immutability without running afoul of the regulations. Furthermore, the proof-of-concept is generic and can easily be adapted to various domains.