What are the advantages of R&D/breeding in indoor farming?
Daylight-free R&D and breeding are all about complete control, repeatability, and speed. Here are the main advantages and what they offer in practice.
Advantage 1: Stable research conditions
In a fully controlled environment, outdoor temperature, sunlight exposure, and day length are irrelevant. In fact, you determine the exact conditions you need for your research question and focus solely on the variables you want to test. This improves the reliability of your results and makes it easier to compare different trials over time.
Advantage 2: Highest hygiene standard
When the growing environment and access are strictly controlled, pests and diseases get little opportunity to spread. You can achieve very high hygiene standards (GHP/lab-like) in your research environment, minimizing the need to intervene with crop protection products and keeping your data cleaner. This is particularly valuable for sensitive research or when small differences make a big impact.
Advantage 3: Lower costs due to faster turnaround and fewer losses
Reproducibility is not just a scientific goal; it is economically important, too. Full control leads to far fewer failed trials, faster conclusions, and a higher turnaround. Additionally, you are no longer tied to growing seasons: you can run the same trials year round and shorten growing cycles, since plants are always in an optimal growing climate.
Advantage 4: Better germination results, better plant health, and potentially improved seed storage qualities
In daylight-free propagation, you can steer the germination process more closely to the crop’s needs. This results in more uniform and more robust starting material that is better equipped for the next cultivation phase – be it the greenhouse or the field.
Advantage 5: Controlled simulation of certain extreme conditions
Stress and resilience research often requires extremes: fluctuations in light and temperature, drought stress, or specific RH profiles. Indoor farming research allows you to simulate these extremes in a controlled way, changing one factor at a time and giving you much more confidence in cause and effect. This speeds up the acquisition of insights and improves the quality of your conclusions.