Data Sets and Recommendations Peanut Notes No. 79 2023
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We (university faculty and staff and NC State Extension agents) often conduct research on products from companies. In some cases, we may look at a product or group of products for one season at one location. In other instances we have a more detailed study with multiple locations and years. This week a farmer provided images of a sales sheet for trials we conducted in 2017. There was a clear advantage to products by the company. I recall doing the trials with that company, but they likely provided the product with an experimental number. At the time I did not know exactly what the product was. That’s perfectly fine. We received a grant from the company, conducted the trial appropriately, and provided the results to them. I’m pretty sure I provided a statistical analysis with the raw data.
The graphs the farmer saw were from one trial and from one year and did not have any statistics on them. Without knowing the variation in response, it is difficult to know how repeatable or consistent the results are beyond that one trial. My suggestion is that when you see a set of data, ask how many years the trial was conducted and if the trial was at one location or more than one location. These are important questions. It’s also important to ask how much variation did you see?
THIS IS THE CASE NOT JUST FROM INFORMATION BY COMPANIES. YOU SHOULD ASK ME AND OTHERS IN A SIMILAR ROLE THE VERY SAME QUESTIONS ABOUT OUR INFORMATION.
I do think there are products out there that under some conditions can increase yield by a modest amount. But that is likely less than 5% and closer to 1 to 2%. They are very incremental. Major differences in yield response are often associated with digging a week or so too early or not controlling a key pest like weeds, pathogens causing leaf spot, thrips, not applying general fertilizer or gypsum, or having an inoculant failure in new ground. These differences can approach 10% (or more) in some cases. Most other inputs are more modest in the benefits, and the benefits are observed less frequently.