The machine learning technology behind all future crops.
At Computomics, we understand the challenges encountered by plant breeders. New crop varieties have to be produced faster, cost-efficiently, and under rapidly changing climate conditions. In response to these challenges, our cutting-edge machine learning-based technology, ⨉SeedScore®, is here to empower you like never before. It's an invaluable addition to your plant breeder's toolbox.
Our tailored technical support and consulting services are designed to cater to your unique plant breeding program's needs, putting you on the path to a new commercial product. Let us support you in making more (and better) data-driven decisions on the path to creating your future signature genetics.
Enabling you to fully exploit the potential of our machine learning-based technology is our highest priority. To achieve this, we guide you on our joint journey, which encompasses four major steps:
The prediction and application phases (steps 3 and 4) are carried out as routine practices and are repeated multiple times throughout the year, contingent upon your breeding program.
Our machine learning-based technology ⨉SeedScore® is well-suited for a wide range of crops - field and vegetables crops for variety development as well as for hybrid production. We invite you to explore its applicability within your breeding cycle and discover the ways in which it can support your selection processes.
At a strategic level, variety development breeding cycles typically encompass three fundamental phases - the creation of genetic variation, the forming of varieties, and the testing - to identify the top performers resulting in a new commercial variety.
With our machine-learning-based technology ⨉SeedScore®, we can provide invaluable support in the early stages. Here, we excel at identifying e.g. the crosses that show the greatest potential to outperform existing commercial varieties. Based on phenotypic and genotypic data from your current breeding program, we predict the performance of the genetics available to you in new crosses. This foresight allows you to focus your efforts on the crosses and varieties with the highest probability of success.
As you approach the end of the variety forming phase, just prior to embarking on the testing phase, our expertise comes into play again. By using genetic information about your potential new varieties, we can predict their performance under field conditions. This predictive capability allows you to rationalize your field resources and focus on a selected subset of potential new varieties, greatly improving your chances of success in the final testing phase.
At a strategic level, hybrid breeding cycles typically encompass three fundamental phases - the creation of genetic variation, the creation of parental lines, and the creation and testing of hybrids - identifying the top performers resulting in a new commercial hybrid.
In all instances, a comprehensive understanding of the genetics of the hybrid parents and the phenotypic attributes of the hybrid is imperative.
With our machine learning-based technology ⨉SeedScore®, we can provide invaluable support in the early stages. Here, we excel at identifying the crosses that show the greatest potential to become parental lines. Based on phenotypic and genotypic data from your current breeding program, we predict the performance of the genetics available to you in new crosses. This foresight allows you to focus your efforts on the crosses and parents with the highest probability of success.
As you approach the end of the parental line forming phase, just prior to embarking on the testing phase, our expertise comes into play again. By using genetic information about your potential hybrid parents, we can predict their performance in all hybrid combinations under field conditions. This predictive capability allows you to rationalize your field resources and focus on a selected subset of potential new hybrids, greatly improving your chances of success in the final testing phase.
Experience actionable insights! Our demo dashboard showcases the depth of conclusions you can draw from our predictions with ⨉SeedScore®.
This interactive dashboard features yield-to-moisture plots illustrating predicted values for corn hybrids, among other insights. The color-coded elements within the plots provide distinctions among hybrid groups, reflecting their genetic lineage, used tester, environments in which performance predictions were generated, and other details. These visualizations are fully customizable to align seamlessly with your dataset and are also adaptable for other use cases such as variety development.
In addition to traditional plant breeding methods, new breeding techniques such as CRISPR offer novel possibilities to optimize and enhance plant characteristics. Editing enables targeted, adaptable, and rapid modifications of plant genomes.
While these groundbreaking technologies hold the promise of designing future-ready plants, there remain challenges. One such challenge is the precise identification and detection of the key editing targets essential for enhancing desirable traits. This task can prove time-consuming and labor-intensive, particularly when dealing with complex traits like yield or disease resistance.
Leveraging cutting-edge machine learning for CRISPR genome editing technologies, we facilitate the acceleration of new plant variety development, reducing the timeline by 3-4 times compared to traditional breeding.
Accelerate your plant breeding with our solution AccelATrait™ and benefit from the combined experience of experts in bioinformatics, plant breeding and genome editing.
Benefits of Computomics AccelATrait™ solution:
Predict virtual hybrids from a male and female double-haploid population and predict hybrid phenotypes that exceed their parents and testers
Multi-trait optimization in malting barley for specific climates
Advancing rice breeding by predicting actual phenotypic values in specific environments