Laboratories activities are a keystone of modern plant breeding programs. It brings breeders and testers fast information for their decision making.
Biotechnologies and analytical testing generate big amounts of data in various files formats and from different type of living materials. One of the challenges researchers are facing is to feed sample lists and generate result files in a standardized format. Another challenge is to improve the communication and the workflow between laboratory technicians and breeders, to share efficiently data and link phenotypic and genetic information.
That’s why this is crucial to build IT bridges between laboratory department and breeding department, through laboratory automation in a collaborative system that centralizes and standardizes all the data exchanges.
Let’s see 3 examples of processes where exchanges of information can be enhanced by laboratory automation:
Sample management with laboratory automation tools
Breeders and laboratories are interacting every single day, constantly exchanging samples and data. IT tools within the plant breeding software automatically generate an identifier for each material and generate labels, facilitating information exchanges between the laboratory and the breeder who use the same material. Such codification ensures the traceability of every material.
The laboratory automation process of the plant breeding software allows to manage user’s profiles and their access rights, enabling notably blind analysis: Technicians will not get the access to the origins of samples and so they will make objective analysis and avoid to generate biased results.
Bar-codes also facilitate the identification system and accelerates samples inventory for the shipment, for instance.
Data workflow optimized by laboratory automation
Process identification in the plant breeding software saves time and avoids wrong manipulations. For instance, new workers in the laboratory can just follow the steps which are already registered on the laboratory automation software.
To optimize the data workflow, it is also important to automate data exchanges. It saves time, avoids Excel file transfer and thus reduces the risk of handling mistakes.
Laboratory automation saves time on repetitive tasks, to capture and to store automatically data from a sequencer, from a LIMS and to get sample plates in the right order for analytical tests.
Enhance analysis and communication automation in the laboratory
Store and manage voluminous data in a plant breeding software with suitable IT architecture and storing facilities are crucial to optimize performances. A prerequisite is to centralize all kinds of research activities into one system.
For instance, if you centralize breeding activities, laboratory activities, product development you will allow researchers to combine information from every department and determine some correlations or links between these research data.
Various reports such as Word, PDF or Excel reports enable to industrialize and standardize the communication of the results.
Laboratory automation breeding software
Appropriate breeding software IT tools enable to manage samples, automate laboratory processes and centralize IT system to optimize collaboration among laboratories and breeders.
Doriane’s objective is to improve breeding programs and facilitate the exchange of data between laboratories and breeders: The plant scoring app RnDExp® Mobile enables fast and safe data collection of observations and measurements. The plant breeding software RnDExp® centralizes all the R&D department information and processes, thus avoids all type of mistakes during the transfer of information.
Doriane, your R&D IT partner
About DorianeThe expertise of Doriane brings the three players of R&D the resources to organize, share and valorize their research projects:
RESEARCH DEPARTMENTS: Fast implementation of business processes ; Liberation of researchers creativity
IT DEPARTMENTS: Real-time centralization of multilocation data ; Security and integrity of data
MANAGEMENT: Maximization of research investments ; Research departments monitoring ; Intellectual assets valorization and sustainability