Use Case: Quantify Crop Response to Treatments and Inputs

In a recent webinar, SlantRange CEO Michael Ritter shared how Aerial Phenotyping technology gives crop researchers the insight needed to quantify and predict input performance. 

The short, 3-minute video below highlights how researchers can quantify product efficacy to demonstrate overall grower returns and target inputs for specific localized environments. A lightly edited transcript follows below. 

 

For input suppliers, it's critically important to be able to quantify the efficacy of their product to demonstrate overall grower returns and be able to target inputs for specific localized environments. 

The challenge here, and I'm talking largely about crop protection, suppliers, crop nutrition suppliers, biologicals, the challenge for those companies is often demonstrating that their input performed better than another input given the myriad of variables always at work in any field. 

So the challenge here is really to try to isolate and quantify the performance of an input subject to whatever treatment may be applied. 

What the solution involved here is really looking at the time-based response of plant development in response to those inputs. 

Learn More: Analyze Stand and Vigor With Aerial Phenotyping

Response to Inputs

 

In the next slide, what we see is a similar layout. This happens to be a crop protection trial on corn. This is a bit later in the vegetative stages in corn. 

It's a managed stress environment where stress is introduced, and then a treatment is applied to see how the plants respond to that stress. The heat map at center is what we consider plant stress, a four-band NDVI. It's a bit more sensitive to plant stress than NDVI. Green is relatively healthy, red is more stressed plants. At the bottom left, again, you have a histogram of all the plots across the trial. At right, you have a high-resolution image of the location. 

What's different in this example is the line plot you see at the center at bottom, which is a time series of two different variables. I think this is vegetation fraction or canopy closure, along with vegetation stress. What we're showing is how an individual plot is responding to treatment over time. 

So what's really different here is the ability for the input supplier to quantify that, and provide evidence of the efficacy of their input, as the crop is responding in real-time. This is all enabled by sunlight calibrated narrowband spectral imaging techniques. 

Learn more about how SlantRange Aerial Phenotyping provides the insights for researchers to quantify and predict crop performance in this recent article.

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