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  4. »eUpdate 584 August 12th, 2016»Precision ag tools and on-farm population research

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Department of Agronomy

Kansas State University

1712 Claflin Rd.

2004 Throckmorton PSC

Manhatan, KS 66506

785-532-6101

agronomy@ksu.edu

Extension Agronomy

Precision ag tools and on-farm population research

(Note: The following article is a slightly edited transcript of a short K-State Research and Extension YouTube video produced by Dan Donnert, KSRE videographer. The link to this video is: https://youtu.be/9veufLbuR80  – Steve Watson, Agronomy eUpdate Editor)

Figure 1. Ignacio Ciampitti (left) and Justin Knopf at a recent K-State dryland corn tour in Saline County. From video by Dan Donnert, K-State Research and Extension.

 

Ignacio Ciampitti, K-State Crop Production and Cropping Systems Specialist: How do you see precision agriculture and our population on-farm research project helping you in the future?

Justin Knopf, Saline County producer: It’s been a wonderful opportunity to partner with you and K-State in this research, looking at precision agriculture research to better fine-tune our populations on our fields. For us farmers, precision ag is overwhelming in many regards. We have all this data, and the age-old question, what do we use this data to do? We’ve been looking at the different yield environments that have become pretty apparent in this field, and were able to set up a population study to go across those multiple yield environments. Now we have population curves and responses in both lower-yielding and higher-yielding environments. The next step is then to fine-tune our populations by environment.

Ciampitti: When we start putting all this information together, using data from precision ag technology such as drones, variable seeding rates, and variable fertilizer rates, we need to evaluate this from the farmer’s perspective. If I’m a farmer, should I invest in this technology? Will that pay off in my fields? The main point we are emphasizing with this on-farm research is to find out if we can find ways to manage in-field variability more cost effectively. In your case, we have satellite imagery of this field from mid-season last year, yield monitor data from last year, and now satellite imagery from early-season this year. We take all this information and correlate it with the different populations we’re testing using the strip trials. We have some preliminary results now, and my question for you would be, from this point on how do you think we can translate this information so it can apply to all yield environments?

Figure 2. Some of the precision ag data on Knopf’s field from last season and this, and how it is correlating with population studies being done on that field.

 

Knopf: I’ve learned some of the steps to take in analyzing the data so that I can now understand what to do. I think I can now apply those same steps to some of our other fields on our own and begin to translate the results we get. I plan to go through this same kind of process in learning what to make of the data we get on other fields across our landscape and across our farm. Hopefully other farmers in our community can do the same and the whole community benefits from the research.