Measuring Soybean Maturity With Automated Workflows

As soybean researchers and plant breeders create higher-yielding varieties, maturity dynamics are critical in categorizing which geographic regions the new hybrids are best suited. 

During the trial phase, researchers are looking to properly categorize the maturity rating, so growers can optimize their yield while mitigating environmental risks, such as the first frost occurring before the plant has reached maturity. 

Measuring soybean maturity is typically a manual process in which agronomists walk the fields at the peak of the growing season to record which plots have turned brown, which are still green, and which are somewhere in between. 

A typical soybean trial might encompass 15 acres, with 500 plots per acre. Walking each of the 7,500 plots twice a week requires the efforts of multiple agronomists — and takes a significant amount of time. Gathering information with a UAV equipped with a remote sensing device, by contrast, would take approximately 20-30 minutes. 

Relying on manual methods to gather information isn’t just tedious. Relying on human judgment to categorize a plot means each person uses a slightly different methodology to categorize soybean development — resulting in subjective measurements. 

By contrast, collecting measurements with UAVs equipped with remote sensing devices remove the need to walk fields to record information on soybean maturity and plant characteristics. Analytics engines process the information and remove the human subjectivity that can lead to errors. 

In the short-term, automated workflows provide objective, statistically accurate soybean maturity ratings, freeing up agronomists’ time for research and analysis. Longer-term, an automated approach gives researchers greater confidence in trial results, leading to faster research and development pipelines, along with decreased time-to-market. 

Comparing Soybean Maturity Dynamics

Screenshot of SlantRange aerial phenotyping platform showing soybean maturityScreenshot of SlantRange aerial phenotyping platform showing soybean maturity

The two examples you see above show two neighboring soybean plots from the same trial in our Aerial Phenotyping platform. Data was collected using an RGB (color) camera roughly every four days during the peak growing season. 

As you can see in the images above, SlantRange’s Aerial Phenotyping platform gives researchers a suite of valuable information about soybean maturity, including: 

  • Days to maturity
  • Date of maturity
  • Time history of maturity progression throughout the growing season

In both views from the platform, the image on the left side shows an aerial view of the trial, with color overlays that provide a geographical representation of the selected metric. Once a plot is selected, you’ll see the maturity date and how many days have elapsed since planting. 

The plot is shown in greater detail on the selected date on the right side of the screen, to provide a comprehensive and more granular view of the research trial.

A histogram in the bottom left corner shows the distribution over the entire trial. Right next to the histogram, a line graph plots the trajectory of soybean maturity across the entire season. In these examples, the plots overlaid in darker green took fewer days to reach maturity, while the plots overlaid in yellow took longer. 

While the two plots grew side-by-side in the field, the soybeans grew at different trajectories to reach maturity 10 days apart. When comparing the two images of the field, both taken on Sept. 26, you’ll notice the first one is entirely brown. In the second plot, you can clearly see yellow leaves, as that plot hadn’t yet matured.

As with all SlantRange data products, it’s easy to export your metrics in a variety of different formats. API integrations are also available to seamlessly import statistics into your own database. 


Measure More Than Maturity Date

While maturity date is the most specialized data product SlantRange offers for soybean researchers, we provide a full suite of measurements for a comprehensive view of your trials.

Other key metrics for soybean researchers include:

  • Emergence fraction, which quantifies the fraction of emergence along a selected row. This measurement is commonly used to estimate the population for crops with very high planting densities, like soybeans. 
  • Chlorophyll index, which quantifies the leaf chlorophyll content to give researchers an understanding of soybean health.
  • Vegetation stress and NDVI, which measure pigment concentration to provide deeper insight into issues such as nutrient deficiencies, pest infestations, dehydration concerns, and other factors that negatively impact plant health. 

SlantRange data products are available for both RGB cameras and multispectral sensors. The chart below shows the data products we currently offer for soybeans.

Data Product

RGB Cameras

Multispectral Sensors

Emergence Fraction

Vegetation Fraction

Chlorophyll Index


Yield Potential


Vegetation Stress



Plant Height

Weed Pressure


Spectral Indices (e.g. NDVI)


Greenness Index

Absolute Reflectance


Plot Images

RGB (Color) Orthomosaics

Plant Lodging (Developmental)


SlantRange data products are powered by patented technologies essential to forecasting, precision input prescriptions, efficiency, and scalability — creating measurements that more accurately, comprehensively, and efficiently measure and predict crop development. 

The Leading Choice of Agricultural Researchers

SlantRange works with many of the world’s leading agricultural input suppliers and producers to provide a more accurate and comprehensive understanding of trial performance for confident, accelerated product advancement decisions. We’ve analyzed 2.7 million plots across 385 trial locations in 57 countries — and counting. 

To learn more about our solutions for research & breeding, including our data products, check out our product guide. If you’d like to discuss how we might be able to help your organization, don’t hesitate to get in touch