Latin America (LATAM) is incredibly strong agriculturally, so it’s not surprising that the world is knocking on its door. This can bring opportunity, but it can also bring challenges.
One of the things I’ve noticed during my many meetings with LATAM plant breeders is that 95 percent continue to use Microsoft Excel to track their data. I understand why.
Excel has many advantages. It’s affordable, easy to use, and allows you to organize breeding data across multiple sheets. You can sort data by genotype, traits, or other relevant criteria. It works well enough for recording phenotypic observations and even some genotypic data.
But when it comes to data analysis, Excel’s capabilities are limited. While it can help visualize general trends in genotype performance across environments, it lacks the statistical power to accurately analyze genetic variability or estimate variance components. Many breeders rely on external tools like R for more advanced analyses. This often involves manually exporting and importing data between platforms, which increases the risk of human error, data inconsistencies, and inefficiencies throughout the workflow.
For many breeders and government organizations in LATAM, Excel may be sufficient for basic record-keeping and field data organization. Few companies in the region currently engage in hybrid breeding, but this is beginning to change. Argentina, Brazil, Chile, and Mexico are already producing seed for North American companies that conduct off-season nurseries in South America during the Northern Hemisphere’s winter.
On top of that, Excel isn’t built to handle large datasets efficiently. This becomes a major problem when you’re working with complex data from field trials, sensors, or genotyping projects involving thousands of markers. Managing multiple spreadsheets becomes unmanageable fast, and trying to find the right data across dozens of files can be frustrating. The more complex the breeding program, the more likely it is that key information gets lost — or mistakes are made that affect the quality of the analysis.
There are faster, safer, and more reliable ways to collect, manage, and analyze breeding data. Specialized plant breeding software can significantly accelerate breeding programs while improving efficiency, traceability, and transparency. Most importantly, it helps reduce human error by eliminating repetitive manual processes and keeping all data centralized and consistent.
With Genovix and similar tools, data is stored in a centralized database that’s easily searched and managed. Trial design, statistical analysis, selection decisions, and final reports are all streamlined—and compatible with a wide range of crops, from bananas and maize to coffee and sugarcane. You can manage seeds, clones, and cuttings, while inventories are automatically updated. And that’s just the beginning.
