Growers can often feel bombarded by agronomists, researchers, economists, retailers, marketers and even other farmers talking about the latest research, information and practices that can help their farms become more profitable. New products and practices are introduced in the marketplace every year, and it’s tough to know what will work best for you.
One way to get the questions answered is to conduct some level of on-farm research on your farm. “Every farmer should have at least one research or demonstration trial going on every year, says Michigan State University Extension educator Pual Gross. But how to go about doing that? A 2017 technical bulletin posted by Sustainable Agriculture Research & Education (SARE) provides the following helpful tips.
For more information, visit www.sare.org.
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Identify your research questions and objective.
Identifying your research question involves moving from the general to the specific—from ideas or hunches to a clear objective—and selecting just one yes-or-no question to answer. In developing your question, consider your own capabilities and if the information needed to answer the question is actually measurable. The question will usually ask whether a new approach is an improvement over the current one or if it will help you meet some goal or objective.
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Develop a research hypothesis.
Your research hypothesis stems directly from the research question or objective. A hypothesis is simply a clear statement of what you expect the outcome of your experiment to be, based on the limited evidence you have at hand. A well-written hypothesis statement can be confirmed (or denied) with actual data.
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Decide what you will measure and what data you will collect.
What will you measure and record in order to answer your question and test the validity of your hypothesis? This is the time to decide what techniques you will use to get your data, looking at factors such as cost, practicality and feasibility. In many crop research projects you will be collecting yield data, but depending on your project, you might also be collecting data on soil nutrient levels, crop development, plant health, plant height, costs or anything else. Determing whether the information you want to collect will be useful in answering your research question.
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Develop an experimental design.
It is tempting to rush through the previous steps and start planning what the experiment will look like in the field. But the task of designing your experiment should flow from the previous steps. Experimental design includes arranging treatments in the field so that error and bias are reduced, and data can be accurately analyzed using statistics. If an experiment has a poor design, you cannot have confidence in the data.
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Choose the location and map out your field plots.
Be specific about plot size and layout, how the crop will be planted, which treatments are to be applied in each plot, and any other important aspects of managing the plots. Select a field that has the right characteristics for what you are testing. Look at the field history and make sure there are no major problems that might prevent you from establishing the plots, or that could negate your results. Research plots should be accessible and easy to maintain. Each treatment plot should be large enough to collect the data you need. To moderate the effect of external variation, choose an area that is as uniform as possible in terms of soil characteristics, management history or slope.
Keep in mind that land adjacent to the research plots can also have an impact on your research due to runoff, pesticide drift or by harboring pests that migrate into the research plots. To control these effects, establish a border or buffer zone around the entire research project. Ideally, a buffer should be a minimum of one tractor pass on all sides, or larger if conditions permit.
Finally, create a detailed plot map for your chosen location based on your research design.
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Implement the project.
Begin by establishing the research plots based on the map you created. Measure and mark your plots with clearly visible stakes or flags. In order to prevent mishaps with the project, make sure you discuss plot design, location, time frame and implementation with your entire farm crew, and share the detailed plot map with everyone involved. Throughout the experiment, be careful to manage all plots exactly the same, except for the treatments (the practices you are testing or comparing.)
Most importantly, plan ahead and communicate. Before you start any field work, create a management plan and calendar for the project. Be specific about how the plots and the crop will be managed, how and when treatments are to be applied, and what data will be collected and how. Then make sure you review this plan with everyone who will be involved in the project.
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Make observations and keep records throughout the season.
Separate from your actual data collection, make observations and take notes throughout the season on influential factors such as rainfall, temperature, other weather events, seedling emergence, crop growth, soil condition, pest problems, field operations or anything else that seems relevant. Keeping a designated notebook, file or spreadsheet with this information will help you interpret your data and put your research results in context.
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Collect research data.
Be highly organized and specify your data collection techniques ahead of time. Prepare your data record sheets beforehand and have all your copies ready to fill out. If you are collecting samples, have all your bags or containers labeled accurately and organized by treatment and plot to facilitate the process. Keep all treatments and plots separate; do not lump data together thinking you will be able to just take an average. Doing so will invalidate your data.
If measuring yield, try to harvest from the center of the plots for your research data and, again, keep each treatment and plot separate. You will eventually harvest the whole area, but do not include buffer rows in your data. If you are measuring other effects (e.g., soil characteristics, weed cover, disease or insect damage), use random sampling procedures.
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Analyze the data.
The statistical techniques that you will use to analyze your data depend on the research design you have used. You can learn to do your own data analysis, either by hand or with a statistical software program. In most situations, you will also want to consult with your technical advisor or extension personnel for guidance with your data analysis.
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Interpret the data and draw conclusions.
Now that you have analyzed the data from your on-farm research, what do the results tell you? What can you infer from the data, and how can you apply that information to your farm? The statistical analysis you use will indicate whether or not there is a “significant” difference in the treatments, practices or varieties you are comparing. If there is a difference, and you feel confident about the results, you may decide to begin making changes in your farming practices.
https://www.youtube.com/watch?v=sicWaiv4lec&list=PLdssrgg38jJ2Qaf3heqE_ne6ecce-j7ud