We are continually meeting different people in different cultures around the world as they share their challenges and struggles to explain how their breeding data, collected with effort and purpose, is not available when they need it. It may not be presented correctly or is still in someone’s notebook after that person left the company. In other situations, too many naming mistakes have happened with time causing data for generations to be lost. Some data maintenance challenges are unique but most sound painfully familiar.
It’s easy to make a mess out of quality breeding data. Breeding has a complex structure built out of multiple layers and entities all connected to one another in various relationships. It is genuinely difficult to find a methodical, coherent way to maintain breeding data and keep quality documentation for many years. This is especially difficult when several researchers are involved. Sophisticated and well-designed solutions are required to provide information management guidelines or answer unexpected, out-of-the box questions. Data to support clear and useful methodology, team collaboration, standardization and harmonization are necessary. No notebook, Excel file, Access table or an old SQL database can provide that.
Looking horizontally at the breeding companies of the world from smallest to largest emphasizes the technological gap between where we are now and where we want to be. There are already many innovative IT solutions being offered but few are adopted and implemented. Our industry is quickly developing new solutions with GMO methods, CRISPR, new legislation, breeding intelligence algorithms, social networks of genes and more. Soon (if not already) more data is being collected by devices than by man. Images collected by drowns will soon allow extracting phenotypic observations and save hundreds in man work hours. Sensors, robots, seed counting and phenotyping machines record, filter, analyze and who knows what else with data. Systems provide recommendations to breeders for parent crossing combinations and to crop producers for irrigation, chemical treatments, storing conditions and propagation all aiming to create supreme next generation products. The reality is that most companies have messy, unorganized breeding databases (or just data) that is somehow ‘stuck’ and will not evolve.
It is clear that anyone involved with plant research must start preparing for future reality and implement quality a software program to backup and support their data collection and breeding operations and make sure their system can enable technological growth.
