Yield monitors, drones – even smartphones – can collect vast amounts of agricultural data for use in research labs. Getting that raw data from the source to a laboratory database, however, isn’t always an easy process, especially when that data is accompanied by physical samples.
Simplicis analyzes the system architecture and workflows of agriscience labs to identify opportunities for improvement. With sample management solutions, software integration, and ongoing support, Simplicis can help establish a scalable agricultural lab that’s prepared to handle the growing demand for research and development.
Preserving Data Integrity
Precision agriculture requires actionable, usable, “clean” data, that can be communicated effectively to end users. The variety of sources for agricultural data, along with collection methodology and documentation, often results in cumbersome data sets that must be standardized, normalized, and de-duplicated. Simplicis can help set up processes that ensure data is sound.
Our proprietary laboratory information management system, Ledger, enables labs to track the movement of samples and data, from collection through discovery. Ledger LIMS can restrict access to samples, create audit trails, and ensure optimum storage protocols.
The number of devices gathering agricultural data is expected to reach 75 million by 2020, up from 30 million in 2015.*
Laboratories often scale quickly, adding components that may not be truly integrated. Eventually, these custom solutions can fail, leading to unplanned downtime. Simplicis can develop the APIs that allow every component to exchange information efficiently, eliminating weak points in the workflow.
Simplicis understands that agriscience labs may be subject to routine Environmental Protection Agency and Food & Drug Administration audits. With Ledger, you can easily document your processes and demonstrate compliance with Title 21 of the Code of Federal Regulations, expediting the audit process.
Contact us to learn how Simplicis can improve your efficiency, data integrity, and processes, so you can be prepared to scale at any time.
SOURCE: Chi H, Welch S, Vasserman E, Kalaimannan E. 2017. A framework of cybersecurity approaches in precision agriculture. In Proceedings of the ICMLG2017 5th International Conference on Management Leadership and Governance, pp. 90–95. Reading, UK: Acad. Conf. Publ. Int.