Chris Forsythe, On-Farm Network Agronomist, MPSG
Through field-scale replicated and randomized research, MPSG’s On-Farm Network (OFN) works to answer questions that impact the profitability of a farm. Reliable and unbiased results are made available to the participating farmer and the public.
Since the launch of OFN in 2014 there have been over 520 trials completed, and over time the program has evolved.
One deliberate change made in 2019 was moving away from conducting an ever-increasing number of trials to capping trial numbers and collecting more detailed information from each trial. This approach helps to explain why a yield response occurred and to better predict if the same response would happen on other farms.
An example of needing to provide a good answer for the why is seen in our soybean trials. Out of the 26 soybean biological trials OFN has conducted to date, none have resulted in a yield benefit. Further investigation is required to learn why there was no yield benefit, and the only way to find out is by digging deeper.
There are two ways to collect data in a field. One way is to put people in the field, and another way is to use technology such as remote sensing. As staff is limited, using more technology in our operation is required to efficiently increase in-depth data collection.
In 2024, OFN purchased new equipment, such as weather stations and drones (Figure 1). On-Farm Network Research Assistant Mikayla Melnick is dedicated to equipment operation and collecting more in-depth data. 
Drones equipped with high-resolution multi-spectral cameras will be used for in-season monitoring. Normalized Difference Vegetation Index (NDVI) combines measures of light reflectance and may be correlated to plant biomass, chlorophyll content and crop stress. Stressed crop patches are closely evaluated and precisely mapped allowing us to get a good view from above of the effect of treatments in a trial (Figure 2).
With the addition of advanced weather stations, we can get data back in real-time. Having real-time feedback allows for faster responses to sites when extreme weather events occur, such as hail and extreme wind. Sensors that measure soil parameters, such as soil moisture, can be added to the station and the data can provide more clues into a particular response.
OFN is utilizing a near-infrared (NIR) spectroscopy with an instrument called SCiO Cup that measures seed protein, moisture and oil percentage. We will learn if these seed attributes are affected by treatments such as inoculation and nitrogen fertility. Higher seed protein and oil percentage provide more value to a crop.
Smartphone apps, such as Canopeo, can be used to quantify crop canopy closure. We are working to determine how much earlier narrow row spacing provides crop canopy closure than wider row spacings. A closed canopy, compared to one that has not yet fully closed, has agronomic consequences such as weed pressure.
Precision technology using variable rate equipment is going to be incorporated into OFN as a trial option this season. An example is varying nitrogen rates across a field to discover which nitrogen rate is most profitable (Figure 3). This technology is leveraged to design unique and robust trials.
The results of our on-farm research have helped farmers make informed decisions by being able to test various management practices on their farm before committing to every acre. By using more technology, we hope to answer more questions and provide more value back to the farmer.
With the increasing availability of new applications, artificial intelligence, machine learning and new technology, the sky is the limit towards incorporating technology in the daily trial data collection and analysis workload. While there’s still no substitute for in-person field visits, technology will be an important tool moving forward.
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