Sentera, an industry leading ag analytics platform powered by machine learning, has launched seven new crop health and performance analytics as part of its FieldInsights product, which helps agronomic leaders make critical in-season and post-harvest decisions with accurate and reliable data sets.
For research and seed production leaders in agriscience, the labor shortage has expounded the challenge of capturing accurate and precise measurements that can be trusted and delivered in a timely fashion. Recent data shows that there’s been a significant decrease in the number of hired farmworkers in recent years – and for agriscience, this poses challenges and risks for bringing new products to market.
“Our technology gives research and product development leaders the measurements they need to evaluate crop health and performance from first sign of emergence through harvest,” said Andrew Muehlfeld, director of solutions engineering, Sentera. “We know that timeliness matters just as much as accuracy, and given the technology that powers FieldInsights, we can deliver our analytics when our customers need them most.”
FieldInsights is Sentera’s data and analytics solution. After capturing high-resolution aerial imagery with a compatible ag drone system, Sentera’s machine learning platform translates the imagery into detailed data sets and measurements. Users can then analyze the data by using Sentera’s software platform, FieldAgent, or choose to consume the data via an integration or data export.
In addition to Stand Count (including Male/Female Stand Count), Crop Health, and Tassel Count (including Male/Female Tassel Count) analytics available today, new FieldInsights analytics include:
- Canopy Cover: identifying green vegetation to characterize growth stage and development.
- Crop Area: digitally tracking field borders for seed production to minimize the risk of genetic drift
- Elevation & Hydrology: modeling how water will flow within the field to inform water management strategies.
- Flowering: measuring timing of plant flowering and development to characterize phenotype and track pollination.
- Height and Lodging: detecting areas of damaged crop canopy to help track plant growth stage.
- Residue Cover: quantifying the amount of residue cover to help improve soil management efforts.
- Weed Detection: identifying the location, extent, and type of weed pressure.
FieldInsights analytics provide essential insight into key crops, including corn, soybean, cotton, canola/OSR, and small grain.