When harvest data is collected, we can finally analyze how different rates affected yield in different productivity zones.

To do that, you need to upload a yield map to the platform. Just drag it to the browser window or click 'Upload data' in the 'Data from equipment' tab of the field report. You can upload yield data directly from your machinery's onboard computer or an already converted shapefile.

When matching the attributes, it's important that you match three of them: yield data, units of measurement, and the time when the yield point is recorded.

  • The 'Yield' parameter represents yield data. We recommend using an attribute that indicates a wet crop, as the grain moisture sensor often shows incorrect readings and can affect the results of the analysis.

  • After that, select the units of measurement you use for yield. We work with the metric, imperial, and hybrid (Canada) measurement systems.

  • The 'Timestamp' parameter represents the time at which the yield point is recorded. It's needed to determine the machinery's direction. It usually corresponds to the 'timestamp' attribute. If there's no such name in the list, select any other attribute that indicates the sequence of points (i.e., 'id').

When the file is uploaded, you can view it in the 'VRA maps & trials' tab. Click the yield map to compare it to productivity zones and analyze the VRA map.

How to interpret trial results

The app will generate a report that shows how much was harvested in each zone when using different rates. With this information in hand, you'll be able to determine the best rates for each zone.

In the experiment results with two control strips, we usually observe 3 scenarios:

  1. An increase in yield. The yield increases in the high-productivity zone when increasing the seeding rate or in the low-productivity zone when reducing the seeding rate.

  2. The yield for all three rates is the same, which means that the rate can be reduced, thus saving money.

  3. The yield in all zones increases when increasing the application rate. It means that the standard rate was underestimated.

Let's take a look at an example

We've decided to plant our field with corn. Based on her previous experience, a farm agronomist determines the average seeding rate is 70,000 seeds/ha. She decides to plant 78,000 seeds/ha in the high-productivity zone and 62,000 seeds/ha in the low-productivity zone.

First of all, let's compare the yield map and productivity zones. We see that the zone boundaries correspond with how yield is distributed in the field.

Now, let's compare the yield and VRA maps. To calculate the average yield without variable-rate application, we look at yield in the control strips with the standard rate. In our case, that's 5.44 t/ha. The average yield when using variable-rate application increased to 5.86 t/ha. That's a great result! Yes, we've used a bit more seeds, but that'll be fully compensated for by the profit made from increased yield.

Now, let's look at the charts towards the bottom part of the report. Right away, we see that: the low-productivity zone had the biggest yield output with a seeding rate of 62,000 seeds/ha. We can conclude that the low rate worked best. Decreasing the seeding rate led to increased yield. Planting 70,000 seeds/ha in this area doesn't make sense. In fact, we even lost yield.

In the high-productivity zone, the situation is quite the opposite. By increasing the seeding rate, we managed to achieve higher yield. In this case, the planting costs were worth it.

Experiment data (rates, control strips, yield map) will always be stored on the platform for each individual season and each separate field. After you select a field from the list, you'll be able to remember what was planted or fertilized season after season (and how) and what the results were. This information can be used for reports. Or to brag to your colleagues!


What's next?

We'd appreciate any feedback you have about the app and trial results. Please tell us whether the platform is user-friendly, which additional features would be useful, what may not have been clear, and anything else you can think of. You can also tell us how much you were able to save on inputs and earn on increased yield! Please e-mail us at hello@onesoil.ai.

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