OFR21: Intro to On-Farm Research with Nathan Mueller

Nathan Mueller Author

10/26/2021 Added

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In this video Nathan Mueller discusses the basics of conducting your own on farm research project and how it can add value to your operation.

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[00:00:00.196](uplifting music)
[00:00:09.960]I'm a cropping systems extension educator,
[00:00:12.290]just like many of your local hosting educators.
[00:00:15.340]And for those of you online,
[00:00:17.290]we're spread across the state,
[00:00:19.010]and I'm located in Jefferson and Gage County.
[00:00:21.520]So I'm gonna go through
[00:00:23.170]how to read the On-Farm Research results table.
[00:00:27.720]And so that way we kind of are all on the same page
[00:00:29.760]moving forward for the day.
[00:00:32.230]So basic understanding.
[00:00:33.580]So this is just an example out of the book from page 19,
[00:00:37.500]but just wanted to walk through
[00:00:38.990]what some of these numbers mean.
[00:00:40.180]And I think probably the main point
[00:00:41.710]I wanna drive home on this, what is a P-value?
[00:00:45.560]any of you that watch Parks and Rec,
[00:00:48.160]you'll recognize this character,
[00:00:49.670]but a P-value stands for probability value.
[00:00:53.500]And essentially, it's a test that we gotta conduct
[00:00:56.840]that's called an analysis of variance,
[00:00:59.020]and the test is called an F-test,
[00:01:00.670]and then we get this P-value.
[00:01:02.730]What we're testing are all the means
[00:01:05.510]or all the yield results
[00:01:06.760]of these four different seeding rates,
[00:01:08.710]are they equal or are they not?
[00:01:11.830]So if you look at stand count,
[00:01:13.460]yep, those don't look the same.
[00:01:15.930]We go over to yield and we see 87, 88, 87, 86.
[00:01:20.880]Are those equal or not?
[00:01:22.130]So we conduct that test.
[00:01:23.660]And if the P-value is less than 0.1 or 10%,
[00:01:28.350]then we say they're equal,
[00:01:31.240]or they're not, they're equal.
[00:01:33.230]If the P-value is less than 0.1 or 10%, they're not equal.
[00:01:39.350]So if we look at the P-value for yield, it's 0.38.
[00:01:43.890]It's larger than 0.1,
[00:01:46.070]so those means are equal or there's no treatment difference.
[00:01:50.320]If we go over to stand count,
[00:01:51.880]since we had a seeding rate steady,
[00:01:53.560]we would hope that there's a difference.
[00:01:56.180]And the P-value there is less than 0.0001.
[00:02:00.510]So significantly less than 0.1, our cutoff level, or 10%.
[00:02:05.420]Now, that 10% cutoff level for determining
[00:02:08.220]if something's significant or not
[00:02:09.690]goes back to what Joe talked about,
[00:02:11.250]that random error or noise that we can have in the data.
[00:02:15.320]And we wanna make sure that we're drawing
[00:02:17.030]the correct conclusions, that the yield difference
[00:02:19.390]or the treatment difference we're seeing
[00:02:21.010]is due to the treatment,
[00:02:21.960]not that random error or noise in the background.
[00:02:24.620]So the 10% level is arbitrary.
[00:02:27.970]And we'll talk about another slide,
[00:02:30.130]an example of where somebody used a different cutoff level.
[00:02:33.240]So next slide.
[00:02:36.520]So just to reiterate that, in your book,
[00:02:39.860]and we'll give you access too, to the online one as well.
[00:02:43.310]Laura will be sharing that, but on page eight,
[00:02:45.810]there's a summary of kind of what we're covering.
[00:02:47.580]So if you ever need a refresher, read through page eight,
[00:02:51.390]but just a reminder,
[00:02:52.720]we're using a 0.1 or a 10% cutoff level.
[00:02:56.070]So again, if the value's 0.11,
[00:03:00.040]approaching significance here,
[00:03:02.962]the third bullet point,
[00:03:04.700]technically, you're gonna see all the letters,
[00:03:07.050]no difference.
[00:03:07.883]It's gonna be the letter A for all the treatment different.
[00:03:10.040]So we're approaching significance,
[00:03:11.870]but it's not quite there.
[00:03:13.820]At 0.25, we're gonna say, there's no treatment difference.
[00:03:17.060]You're gonna see the letters are all the same.
[00:03:19.480]We're assuming at that point,
[00:03:21.280]that that difference there is likely just random error
[00:03:24.580]or noise that Joe talked about in his presentation,
[00:03:28.110]that can come from the combine artifacts
[00:03:30.890]or the combine or field variability.
[00:03:33.370]Next slide.
[00:03:36.490]So that was the first step was,
[00:03:39.280]are the means or are the treatments equal?
[00:03:42.210]And then we needed to know the next step,
[00:03:44.100]where are they different?
[00:03:45.280]What treatment is different than the other?
[00:03:48.400]So that's the next test.
[00:03:50.200]And that's called a mean separation test.
[00:03:52.480]And we use Tukey's, which does protect against error rate
[00:03:56.960]when we make lots of comparisons.
[00:03:58.650]So if we have six different treatments,
[00:04:00.470]or four in this case,
[00:04:02.150]the chances us making an incorrect conclusion
[00:04:04.690]go up with each individual pairwise comparison.
[00:04:07.950]So we are controlling for that,
[00:04:10.890]so that way, again,
[00:04:11.760]we don't attribute a treatment difference right away,
[00:04:14.240]just that may not be true.
[00:04:16.830]So if you look at the letters
[00:04:17.990]that you're gonna see in all the tables,
[00:04:19.390]it's just like Sesame Street.
[00:04:21.480]If the letters are the same, the treatments are the same.
[00:04:24.110]There's no difference.
[00:04:25.950]If the letters are different,
[00:04:27.090]then we're seeing a difference according to the statistics.
[00:04:29.620]So Laura's highlighting there, letter D, C, B, A.
[00:04:33.180]So actually, we are able to separate out
[00:04:35.410]with the statistical counts that we got that,
[00:04:39.270]yep, we hit those.
[00:04:40.400]There's changes in the seeding rate across the field.
[00:04:43.320]If we go over to yield,
[00:04:44.980]you can see with this mean separation test,
[00:04:47.270]we got all letters A.
[00:04:48.420]So that one or two bushel numeric yield difference
[00:04:51.330]you're seeing there,
[00:04:52.300]we're not confident that that two bushels
[00:04:54.330]is actually due to the seeding rate.
[00:04:56.850]And then we move over to marginal net return.
[00:04:59.240]And we'll talk about how we calculate this,
[00:05:01.490]but we have A, A, AB and B.
[00:05:04.220]So what's this AB?
[00:05:06.310]It's like A and it's like B.
[00:05:09.320]We weren't quite able to separate out
[00:05:11.380]the 140,000 seeding rate from the 110 or the 170.
[00:05:15.880]We're not confident that that change in seeding rate
[00:05:20.490]is gonna drive a marginal net return difference.
[00:05:23.720]But we are confident that the 80,000 seeding rate profit us
[00:05:27.940]or had a higher and marginal net return
[00:05:29.910]than the 170,000 seeding rate
[00:05:32.230]because the difference in the letter A and B.
[00:05:34.700]If any of you have followed FIRST Trials,
[00:05:36.280]it's a third-party entity in Eastern Nebraska
[00:05:38.970]that does variety testing.
[00:05:40.090]This is from their plot this year in Beatrice.
[00:05:42.530]The plot average is 209.
[00:05:44.820]Sometimes you'll see a value called LSD
[00:05:47.050]and that's least significant difference.
[00:05:49.160]It's how many bushels there needs to be a difference
[00:05:51.980]between two hybrids, or in this case,
[00:05:53.770]two different seeding rates
[00:05:55.530]for it to say that it's due to the hybrid,
[00:05:57.240]it's due to the seeding rate.
[00:05:58.820]So they report both, a 0.1 net 10% cutoff level.
[00:06:03.200]And then they also report a 25% or a 0.25 cutoff level.
[00:06:07.730]And of course, you only need a 3.8 bushel difference
[00:06:12.010]at that lower confidence level.
[00:06:14.760]However, you also have a 25% chance of being wrong
[00:06:18.240]in drawing a conclusion that that four bushels
[00:06:20.550]was due to the hybrid in their plot,
[00:06:22.700]where at the 7.3 bushels,
[00:06:24.340]you only have a 10% chance, essentially, of being wrong,
[00:06:27.960]that there actually wasn't a,
[00:06:30.210]that you're saying there was a hybrid difference.
[00:06:32.100]So again, it's about being confident in the results,
[00:06:34.910]and that's what we're using statistics for
[00:06:37.220]is to be confidence in the conclusions that we're drawing.
[00:06:40.620]So next slide.
[00:06:43.710]So all of the yield data that you're seeing,
[00:06:46.420]and then that goes into the marginal net return,
[00:06:48.610]we have corrected for moisture across crops.
[00:06:50.870]So for base-level moisture that we're correcting for,
[00:06:53.660]for soybeans here is 13%.
[00:06:55.440]So if for a treatment, the percent was 12.5%
[00:06:59.480]in one treatment or one plot and the next one was 13.5,
[00:07:03.940]we're adjusting the total weight in the bushels
[00:07:06.320]to standardize everything at a common moisture percent
[00:07:09.180]across all of these studies.
[00:07:12.000]So next slide.
[00:07:14.750]So the marginal net return calculation that we use
[00:07:18.170]that you'll see in all the tables
[00:07:19.530]is gross income minus the treatment cost.
[00:07:23.570]And so let's run through, for the 80,000 seeding rate,
[00:07:27.510]what the marginal net return was.
[00:07:30.360]So it would be our yield difference
[00:07:32.120]or our yield measured for that treatment, which was 87.268.
[00:07:36.230]We do, in the tables,
[00:07:39.940]average that out to a full bushel difference.
[00:07:42.910]So if you're calculating this at home by calculator,
[00:07:46.830]you might see a little bit of a difference
[00:07:48.490]by a dollar or two, but we use that full number that we get.
[00:07:52.670]So we take 87 bushel times $9.50,
[00:07:56.520]which is a standard commodity price
[00:07:58.190]that we're using this year in 2020,
[00:08:00.320]minus our treatment cost,
[00:08:01.720]which was 80,000, divided by our 140,000,
[00:08:05.900]which is our unit for soybeans,
[00:08:07.250]times the unit price, which was $62.30 a unit.
[00:08:11.820]So we just do the math on that.
[00:08:13.270]It's $829 minus $35
[00:08:16.910]and we get our $793 marginal net return
[00:08:20.470]that you see in the table.
[00:08:22.030]So essentially, you can verify these as you go through,
[00:08:24.710]if you happen to see a little bit of a blip
[00:08:26.670]or a number that isn't doesn't quite make sense,
[00:08:28.140]sure, let us know.
[00:08:29.960]Sometimes we don't catch all of the errors
[00:08:32.600]when we're running math.
[00:08:33.500]So next slide, we'll talk about
[00:08:35.540]how the numbers we're using for this.
[00:08:38.280]So for the marginal net return calculations,
[00:08:41.010]again, on page nine in the book,
[00:08:43.580]this information is shared there too,
[00:08:45.420]but the average commodity prices we use
[00:08:47.340]for the 2020 studies was 3.51 bushels per acre,
[00:08:51.987]$9.50 per bushel for soybeans,
[00:08:55.457]$6.01 roughly per bushel for cereal rye,
[00:08:58.700]and pinto beans, $24 per hundred weight.
[00:09:03.440]Now, the costs that we use on the studies
[00:09:07.050]come from several different sources.
[00:09:08.470]It could be the producer-reported cost of that treatment,
[00:09:12.190]what they bought those soybeans for.
[00:09:14.550]And when it comes to application,
[00:09:16.610]if we don't have the applicator's cost,
[00:09:18.970]we will use the UNL custom rates to substitute for that.
[00:09:22.960]We will use the 2020 commodity prices
[00:09:25.710]for the marketing year, not necessarily what the farmers
[00:09:29.080]actually sold their crop for, just to standardize that.
[00:09:32.710]And then of course, you can use your own data.
[00:09:34.710]So if you're looking at the results of one of these studies
[00:09:37.210]and you wanna input some of your own costs or your own,
[00:09:40.320]what you got for your commodity
[00:09:41.800]or use your application cost instead of the custom rates,
[00:09:44.890]you can sure do that and kind of rerun some of the math
[00:09:47.780]on your own for each of these studies.
[00:09:50.540]So with that, that kind of wraps up
[00:09:52.390]about understanding the results table
[00:09:55.150]in the On-Farm Research book.
[00:09:56.610]Thanks for your time.
[00:09:58.272](uplifting music)

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OFR21: Intro to On-Farm Research with Nathan Mueller

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