St. Paul, Minn. – Sentera, the industry-leading provider of ag analytics, introduced its Lookback Program initiative to the agriscience industry, providing a toolset to ag researchers and product developers to process agronomic data from past seasons to unlock insights to inform the seasons ahead.
The seasonality and site-specific data of agriculture creates challenges for agronomic leaders, both from a data collection and analysis perspective. Finding the resources to collect, process, and analyze data can often be constrained given current research or project needs.
“Data sits at the core of research and product development in agriscience, and we often don’t realize the immense value that historical data holds,” said Brian Bohman, Ph.D., director of product strategy, Sentera. “Whether it’s informing future research initiatives or improving current programs, data from past seasons or initiatives can help validate outcomes over time and inform future research and development decisions.”
Through the Lookback Program, Sentera has the capability to process any agronomic data set via its data science ecosystem. Its core geospatial platform consumes spatio-temporal agronomic and image data to power image-based deep learning and agronomic machine learning capabilities to deliver plant-level measurements and insights.
As a result, Sentera delivers key imagery-based analytics and insights – like Stand Count, Crop Health, Flower Cover, Canopy Cover, and Tassel Count – while also providing agronomic modeling solutions for predictive insights into maturity date, yield and quality, and nutrient status.
The data agnostic nature of the Lookback Program opens the door to evaluating historical data for infinite use cases in agronomy. Key areas of focus include:
- Seed breeding, to measure emergence, uniformity, vigor, and plot quality;
- Crop nutrition, to measure nutrient uptake, efficiency, and yield response; and
- Crop protection, to measure product efficacy, crop damage, and treatment response.
“The value of the Lookback Program is twofold: it provides insight into historical data and identifies requirements for a future data collection program,” continued Bohman. “Looking back opens doors in the future by identifying what worked, uncovering what was missed, and informing future decisions about research design.”
For more information about the Lookback Program and Sentera, visit https://www.sentera.com.