By: Claire LaCanne, University of Minnesota Extension Educator – Crops, Angie Peltier, University of Minnesota Extension Educator – Crops, and Jennifer Brhel, University of Nebraska Extension Educator
The March 12th session of University of Minnesota Extension’s Strategic Farming: Let’s Talk Crops program focused on data-driven decision making. This webinar featured Angie Peltier, University of Minnesota Extension Educator – Crops, and Jennifer Brhel, University of Nebraska Extension Educator joined by moderator Liz Stahl, University of Minnesota Extension Educator - Crops as they discussed “Data Driven Decisions: Determining what really affects the bottom line.”
Try to keep as many factors consistent as possible. Compare treatments in an area with the same or similar soil types and the same management history to minimize as much field variability as possible. The goal is to keep all else uniform so that one can determine whether there are differences in yield (or other desired measurements) due to the treatments that are being applied.
Some formats for plot design include a paired comparison, where a planter can be split to create two treatments and then replicates can be randomized as the planter moves through the field. Examples of comparisons that can be made this way include comparing seed treatments or trying different seeding rates.
Another design is a block design, which could be used to test benefits of cover crops in a field, for example. This design is especially helpful when examining management practices when equipment that doesn't match up well - planters, sprayers, and fertilizer equipment that are not all the same width. For those with equipment that has variable rate capabilities, prescriptions can assist in randomization and replication of treatments.
The March 12th session of University of Minnesota Extension’s Strategic Farming: Let’s Talk Crops program focused on data-driven decision making. This webinar featured Angie Peltier, University of Minnesota Extension Educator – Crops, and Jennifer Brhel, University of Nebraska Extension Educator joined by moderator Liz Stahl, University of Minnesota Extension Educator - Crops as they discussed “Data Driven Decisions: Determining what really affects the bottom line.”
On-farm research
Keep things consistent
There are several things to think about when conducting on-farm trials. It is important to plan properly - which is not always simple, but is doable when you keep these considerations in mind.Try to keep as many factors consistent as possible. Compare treatments in an area with the same or similar soil types and the same management history to minimize as much field variability as possible. The goal is to keep all else uniform so that one can determine whether there are differences in yield (or other desired measurements) due to the treatments that are being applied.
Use replication and randomization
Simply splitting a field, or even comparing one field to another, cannot provide reliable answers to agronomic questions. Treatments need to be replicated to provide more data points and confidence in results. This also helps ensure that we are not just capturing natural variability in a field. Conducting a study over multiple years can also be helpful; however, because on-farm trials are conducted in real-world conditions, results may not be perfectly replicable from year to year. Randomization is important to account for variability (drainage, past field history) that can impact results, revealing ‘differences’ that are actually due to the variability rather than the treatments applied. |
| Field map showing a simple side-by-side comparison. Image credit: Jennifer Brhel |
Some formats for plot design include a paired comparison, where a planter can be split to create two treatments and then replicates can be randomized as the planter moves through the field. Examples of comparisons that can be made this way include comparing seed treatments or trying different seeding rates.
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| Field map showing an example of replication. Image credit: Jennifer Brhel |
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| Field map showing an example of replication with randomization. Image credit: Jennifer Brhel. |
Another design is a block design, which could be used to test benefits of cover crops in a field, for example. This design is especially helpful when examining management practices when equipment that doesn't match up well - planters, sprayers, and fertilizer equipment that are not all the same width. For those with equipment that has variable rate capabilities, prescriptions can assist in randomization and replication of treatments.
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| An example of a block treatment that contains replications within blocks. Blue blocks represent clover; yellow blocks represent the check. The red boxes represent one harvest pass from each treatment allowing for 3 replications. Image credit: Jennifer Brhel. |
A solid design is needed so that data can be analyzed properly and conclusions can be made about whether there are true differences between treatments or not.
On top of running on-farm trials and examining your own farm’s balance sheet, one way to estimate return on investment (ROI) is to use a tool from the Crop Protection Network, called the Corn Fungicide ROI Calculator. This calculator can help you estimate the ROI of using fungicides on corn, and the dataset is robust. The calculator is based on four years of data, spanning from 2019 through 2022 with 19 states and Ontario contributing to the dataset. That's 151 site-years of data and close to 1,200 cases where they were comparing fungicide treatments to an untreated control.
Conduct the study, collect data, and observe!
After the plots are established, the next steps include conducting the study and collecting data. This does not just mean relying on a well-calibrated yield monitor; taking pictures is important so that one can explain why the results that one is observing make sense (or don’t). It is part of the process of documenting what's going on and visualizing what is happening. Eventually, it is important to crunch the numbers and analyze the results. Interpreting results will require setting a confidence interval to decide how certain you want to be that results are due to the treatments applied and didn’t happen from random chance.Return on investment
Assessing return on investment
Farmers are running a business. As such, every trip across the field with some sort of crop protection product or chemical needs to at least pay for itself through protecting yield potential when compared to an untreated control.On top of running on-farm trials and examining your own farm’s balance sheet, one way to estimate return on investment (ROI) is to use a tool from the Crop Protection Network, called the Corn Fungicide ROI Calculator. This calculator can help you estimate the ROI of using fungicides on corn, and the dataset is robust. The calculator is based on four years of data, spanning from 2019 through 2022 with 19 states and Ontario contributing to the dataset. That's 151 site-years of data and close to 1,200 cases where they were comparing fungicide treatments to an untreated control.
The calculator has been populated with data that includes:
Using the calculator, we can look at how economical a fungicide application is likely to be given the current corn prices. Under low disease pressure, at $4/bu corn, the probability of most foliar fungicide applications resulting in a farmer breaking even is 50% or less in most instances. However, if corn prices were $6/bu and disease pressure high, a foliar fungicide has a better than a coin-flip’s chance of breaking even. This is why making a profitable fungicide application entails reserving foliar fungicides for those instances in which one is actually treating a known disease threat.
There are several factors that should be considered when deciding whether to use a fungicide prophylactically. First of all - what disease is being targeted? When dealing with fungicides, it's important to know what disease or diseases you are protecting the crop against because not every fungicide works equally well against every disease and not every disease is caused by a fungus. The Crop Protection Network has a resource called the Fungicide Efficacy tool that shows the effectiveness of various products for different corn foliar diseases. Product efficacy is rated from poor to excellent for controlling a particular disease.
Prophylactic applications are not recommended for several reasons. The economics just do not pencil out when disease pressure is low. There's a couple things you can assess in the field to determine disease pressure, which requires scouting and looking for symptoms. Once diseases are identified, the next step is to determine what level of genetic disease resistance your hybrid has. Genetic resistance to disease in a hybrid is essentially disease management at no additional cost. High levels of disease resistance may mean that disease pressure will not become yield-limiting in years in which environmental conditions only moderately favor disease. It is also important to consider current conditions such as disease presence and the weather forecast to determine whether additional cycles of infection are likely to occur and a fungicide may therefore be warranted.
All of these factors should be considered when making a fungicide application to help prevent promoting fungicide resistance in our pathogen populations. We should only use our limited fungicide tools - which consist of just three groups of fungicides in corn - when they are needed, in order to keep them effective options.
If you need help figuring out what you are seeing in the field, University of Minnesota Extension has a tool called Digital Crop Doc where farmers and ag professionals can take pictures, answer a couple of questions, and University of Minnesota personnel can provide a visual diagnosis and associated management recommendations.
To watch this session and other episodes check out: http://z.umn.edu/StrategicFarmingRecordings
Thanks to the Soybean Research and Promotion Council and the Corn Research and Promotion Council for their generous support of this program.
- treatment costs, (the combined cost of the the chemical itself and the application)
- expected financial benefits of that application based on data collected from field trials
- the probability of breaking even
- price of corn ($/bushel)
- disease severity
- expected yield
- fungicide application price
Using the calculator, we can look at how economical a fungicide application is likely to be given the current corn prices. Under low disease pressure, at $4/bu corn, the probability of most foliar fungicide applications resulting in a farmer breaking even is 50% or less in most instances. However, if corn prices were $6/bu and disease pressure high, a foliar fungicide has a better than a coin-flip’s chance of breaking even. This is why making a profitable fungicide application entails reserving foliar fungicides for those instances in which one is actually treating a known disease threat.
Prophylactic treatments
Prophylactic applications are made either without scouting for a pest or making an application without a particular pest being present. Prophylactic treatments are a risky bet in the current economic landscape. The focus of this part of the session was about assessing ROI of prophylactic treatments, and honed in on fungicides as an example.There are several factors that should be considered when deciding whether to use a fungicide prophylactically. First of all - what disease is being targeted? When dealing with fungicides, it's important to know what disease or diseases you are protecting the crop against because not every fungicide works equally well against every disease and not every disease is caused by a fungus. The Crop Protection Network has a resource called the Fungicide Efficacy tool that shows the effectiveness of various products for different corn foliar diseases. Product efficacy is rated from poor to excellent for controlling a particular disease.
Prophylactic applications are not recommended for several reasons. The economics just do not pencil out when disease pressure is low. There's a couple things you can assess in the field to determine disease pressure, which requires scouting and looking for symptoms. Once diseases are identified, the next step is to determine what level of genetic disease resistance your hybrid has. Genetic resistance to disease in a hybrid is essentially disease management at no additional cost. High levels of disease resistance may mean that disease pressure will not become yield-limiting in years in which environmental conditions only moderately favor disease. It is also important to consider current conditions such as disease presence and the weather forecast to determine whether additional cycles of infection are likely to occur and a fungicide may therefore be warranted.
All of these factors should be considered when making a fungicide application to help prevent promoting fungicide resistance in our pathogen populations. We should only use our limited fungicide tools - which consist of just three groups of fungicides in corn - when they are needed, in order to keep them effective options.
If you need help figuring out what you are seeing in the field, University of Minnesota Extension has a tool called Digital Crop Doc where farmers and ag professionals can take pictures, answer a couple of questions, and University of Minnesota personnel can provide a visual diagnosis and associated management recommendations.
To watch this session and other episodes check out: http://z.umn.edu/StrategicFarmingRecordings
Thanks to the Soybean Research and Promotion Council and the Corn Research and Promotion Council for their generous support of this program.
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