Three questions to ask yourself to get more from your research
As you plan your agronomic trial, it’s crucial to consider three key questions:
1. How will these results be used?
Demo trial, Marketing content, Regulatory trial, Patent/IP data, product optimization, discovery research, mechanism, product performance, white papers, publications, label information? Each has unique trial design and methodology requirements.
When planning your research, it's essential to consider what you want to achieve. This will help you choose the right trial design, methodology, budget, timeline, and other important factors. For example, it's not advisable to rely on a demo trial to obtain regulatory data as it may not provide the necessary information. Additionally, you don't always need a regulatory trial-sized budget to create effective marketing content that is both valuable and accurate.
2. When do you need the information generated from the trial?
Do you plan to use this data for a product launch in three years or for product brochures next season? If you have enough time, consider treating the trial as a multi-year investment that can be built upon next year. What kind of information do you need in the first year that can impact how the second year of trials will be conducted? If you have a tight schedule, how can you gather all the necessary information in one go? Do you need to repeat the trial to observe compounded effects or annual variability? Trials are often focused on the current year without considering the opportunity to gather foundational data for the following years.
3. What are the technological and analytical capabilities available to you?
Gone are the days when genomic or molecular analysis was limited to academia. Sequencing has become affordable and can offer extensive insights into the impact of a product on plants or their environment. However, the challenge lies in distilling the large amount of data generated from sequencing into practical and relevant information. This information can then be utilized to make informed decisions on product development and application, and optimization.
