Wide-Area Corn Hybrid Assessment Tool

An important concept that you’ll need to understand...

...in order to appreciate the potential helps that this website can provide – as well as its limitations, is that of “competitiveness”. Unlike most hybrid performance summary reports that generate “head-to-head” (one-on-one) comparisons, our tool asks each hybrid to compete against the whole class, and not just one of the other class members (specific hybrid).

The performance metric tracked in this tool is yield expressed as a “percent of location average” (% of LA). Location average then is used to represent an estimation of the “yield level” provided by each plot’s unique combination of soil type, weather/climate, and management (planting rate & date, fertility, tillage, irrigation, weed control, etc.).

The advantages of this approach are several:
  1. This tool records a “hit” for each plot location that the hybrid of concern is entered in, and not just the plots where it happens to be entered with a specific other comparison hybrid. In effect, this approach generates more hits; “more hits” equates to “more data”; and the more data -- the better.

  2. Hybrids have different “adaptabilities” as you move them from year to year, soil type to soil type, east to west, north to south, and to different yield levels, moisture regimes, fertility levels, tillage practices, and planting rates. As you change locations for any two hybrids, relative to the performance of all the other hybrids you could have planted (i.e. “yield level”) -- one of these specific two could be becoming more competitive, while the other one could be becoming less. That is why you can easily find head-to-head reports where Hybrid A beats Hybrid B, Hybrid B beats Hybrid C, and Hybrid C beats Hybrid A (akin to an Escher illusion). Each head-to-head comparison is generated from a different set of plot locations; and each set of plot locations represents a different level of competitiveness (i.e. ability to compete; ability to perform above average) for each of the two hybrids in question. From loc to loc they could be changing (relative to the “rest of the pack”, relative to the changing yield level) in the same direction but to different degrees, or they may even be changing in opposite directions. Although it seems counter-intuitive, comparing to a specific other hybrid represents more of a “moving target” than does comparing to location averages (i.e. its merits (any given hybrid’s) are made less clear and obvious instead of more).

  3. Perhaps the greatest benefit of taking this approach is that it allows the patterns of the natures of hybrids (i.e. how they behave) to reveal themselves as you parse the data. Additional yet-to-be-introduced tools (have been developed but still need to be incorporated (coded) into this website) will enable you to more easily discover some of those patterns: e.g. the ability to compete as you move a hybrid east or west (“eastern hybrids” often need better disease tolerance in order to compete; “western hybrids” usually need better heat and drought tolerance), or north to south (most hybrids perform best where they are full-season (on the northern side of their “area of adaptation”; but that is not always true, especially if they flower (silk) late for their maturity). Other useful patterns that can be teased from this kind of data: the effect of elevation on a hybrid; response to planting rates, response to yield levels (low-stress vs. “tough” environments), and the interactions between these two.

However, there are also disadvantages (limitations) to this approach:
  1. The primary disadvantage of this approach is that it uses an unbalanced dataset (i.e. all hybrids cannot be found at every location). As most data published by seed companies comes from plots that are predominantly hybrids of their own brand, they for the most part are not much more than just competing against themselves (i.e. how “competitive” their products are vs. true competitors is not very readily made obvious). The implications for this tool, then, are:

  2. Hybrids from companies with relatively “strong” line-ups show to perform not quite as strongly as they really are; whereas hybrids from companies with relatively “weak” line-ups actually show to perform (i.e. compete) just a little bit better than what they really do…

  3. Even though this may be true, the inaccuracies of this approach are probably much smaller (insignificant?) than one would think.

  4. The other main limitation of this approach has to do with a hybrid’s maturity relative to the rest of the plot entries. As a rule, later-maturing hybrids have a higher yield potential than do earlier ones. (The last time I checked it was about 5-eigths of a percentage point (0.625 %) per 1 day in maturity on average (i.e. with all other things being equal, a hybrid that is 8 days later should out-yield the earlier one by about 5%)) Hybrids that are consistently on the early side of the average of all plot entries are disadvantaged in this type of an assessment system. This, in reality, affects very few hybrids as they usually are scattered around enough (i.e. sometimes they are “early” and sometimes they are “late” relative to the other plot entries) that this effect washes out (i.e. disappears or goes away). The hybrids that “move south” best (i.e. “competes well with later hybrids”) are the ones that are most often over-represented as early hybrids in plots and therefore are the ones most likely to be misrepresented in this way. We offer the option of excluding all locations where a hybrid is more than 5 days earlier than the plot average (for maturity) as an attempt to minimize this concern. However, we can do nothing about the very earliest of all hybrids that are by definition always then the earliest of the plot entries (i.e. a 72-day hybrid is almost always one of the earliest entries in a plot and is therefore disadvantaged). The only thing you can do is keep this in mind and only compare it to other hybrids of the exact same maturity.

Search Criteria Guidelines
In light of these strengths and weaknesses that I’ve just delineated, you may still be a little queasy about using this tool to determine if a hybrid from one company is better than one from another. Fair enough. Please consider the guidelines listed in the “Search Criteria” and “Economic Criteria” sections in order to improve your level of confidence. But even if you aren’t very confident in using this tool to compare hybrids from one company to another, please know that this tool is extremely powerful in helping you to better understand “behaviors” and “adaptabilities” of individual hybrids, and also in comparing hybrids within a single company’s line-up.
 
Search Criteria
  • Geography (map selection tool)
  • Maturity range (###RM to ###RM)
  • Yield Level (### to ### bu/a)
  • Planting Rate (##,### to ##,### seeds/a)
  • Year Filter (Select Years to be removed)
  • Brand (drop-down list)
Search Criteria Guidelines
  1. The more data you have, the better. Any result that shows less than 10 loc’s (locations) for a hybrid of interest is suspect; and certainly those with results from only 4, 5 or 6 loc’s should be highly “questionable”. When you get many results with uncomfortably few locations, consider broadening your selection criteria (including the geography you highlight on the map).

  2. Keep maturity ranges fairly narrow (within 3 to 6 RM) to limit the number of products that show up in a report (especially when considering all brands). You may also want to try running successive reports with overlapping maturity ranges (e.g. run a report for 94 to 98 day hybrids and one for 96 to 100 while keeping all of the rest of the selection criteria the same).

  3. The majority of the data comes from locations that averaged somewhere between 190 and 230 bu/a. You can keep your yield level ranges fairly tight when looking for data from these middle levels; but if you are trying to compare hybrids from much lower or higher yield levels, you will want to broaden out you yield level ranges to pull in enough data for some hybrids.

  4. Likewise, most of the data comes from locations where planting rates are between 29,000 and 33,000 seeds/acre. Once again, you can keep the planting rate ranges pretty tight when dabbling in these middle ranges; but if you are interested in data from loc’s that were planted significantly higher or lower, you will probably want to broaden you selection criteria range in order to pull in enough data.

  5. It is usually best to pull data from as many years as possible. Do to the relatively rapid churn rate of corn hybrids with most companies’ lineups, pulling from more than 3 or 4 years is usually counter-productive. But you may want to drop some years from consideration from time to time if you don’t think that they represent what we normally should be able to expect (like the drought year of 2012 (not available in this database anyway) or the wet, late-planted year of 2019).
Economic Criteria
  • Seed costs (average farm-gate price per unit ($###))
  • Planting rate (# of seeds/acre (##,###))
  • Grain price ($#.##/bushel)
  • Yield level (### bushels/acre)
 
 
Selection Criteria Guidelines
  1. The “Seed Cost” that you are asked to enter is actually a fairly arbitrary number and does not have to be exact. Just answer the question “what is a bag of seed for the average hybrid worth?” and all will work fine. Being overly generous or frugal on your estimate does not change the sort or the relative economic differences between hybrids.

  2. Enter the average planting rate for your farm in the “Seeds/Ac” input box.

  3. Enter the average grain price that you expect to receive in the “Grain Price” input box.

  4. Enter the expected yield for the farm, field, or zone within a field that you are selecting a hybrid for.

Results
Here is a brief description of and explanation for each of the output columns in your “Corn Hybrid Performance Assessment” reports:
 
  • “Yield (Ave % LA)” is relative yield for any one location (% of Location Average (LA)) averaged over all locations.

  • “n” stands for the number of locations (hits) for a hybrid that met your selection criteria.

  • “n > LA” = the number of times that hybrid performed above the location average.

  • “% > LA” = the percentage of times that a hybrid performed above the location average. This value represents “consistency”, one of the more important components of competitiveness.

  • “Perf X Cons Index” stands for “performance by consistency index”. The performance component is basically yield (the first column described). The consistency component is the “% > LA” column just described. This column is essentially a modification of the Yield (performance) column, and provides a more conservative way of evaluating and sorting hybrids. The need to modify the performance metric (Yield) stems from and is determined by 2 considerations: 1) number of hits (“n”). As we’ve said before, more hits = more data, and more data is better. If the numbers for a hybrid come from fewer than 10 locations, the performance number is “shaved” a bit (the fewer the loc’s, the more this number was cut). And 2) consistency (% > LA). The more inconsistent a hybrid is shown to be, the more the performance number (Yield) was cut (i.e. the lower the percentage of the time that a hybrid finished above the location average, the harder it was cut). As shaving is done whenever either factor comes into play, the “Perf X Cons Index” column is always smaller than the “Yield (Ave % LA)” column – if it is different at all (if a hybrid’s numbers came from > 10 locations and always (100% of the time) finished above LA, then no shaving was done).
  • “Lo Value per Unit” is all the economic calculations done using the “Perf X Cons Index” column for the performance metric.

  • “Hi Value per Unit” is all the economic calculations done using the unaltered “Yield (Ave % LA)” column for the performance metric.

  • “Price per Unit” defaults to the “Avg Farm-Gate Price/Unit” that you enter into the input inbox at the top of the report before asking it to calculate. But it is not reality that all hybrids are priced the same. So it is our recommendation that you “overwrite” the values with actual price quotes that you receive from your suppliers to make the last column more meaningful/valuable/real.

  • “Add’l Value” represents the value difference between what you are asked to pay for a hybrid versus what this tool calculates its estimated value really to be. You have the option to have this difference calculated based on either the “Lo” or “Hi” value columns, or you can use an average of the two
We hope that by now it has become pretty obvious to you how valuable this tool can be. We would assume that it is your objective to not just “get what you pay for”, but in the end to find opportunities where you can “get more than what you pay for” (and certainly not less). You finally have a tool that will enable you to at least get a ball-park answer for the nagging question: “yes, I know that this is a really good hybrid – but is it worth what I’m asked to pay for it?”.
 
We would at this time ask you to remember that this tool, while it indeed may be very useful and valuable, is only that – a simple tool (and an imperfect one at that). It is only one of several tools that you have at your disposal to help you make an informed buying decision. Please, please, please consider your own experiences, those of your neighbors, the advice of your seed suppliers and/or agronomists, and also the performance of hybrids you are considering from plots that were in close proximity to your operation. And when this tool is suggesting a conclusion that is out of sync with what everyone else is advising, please take that as a cautionary red flag – a sign that you still have homework to do before making any commitments.

Video Demo - Tool #1

Creator Steven Dvorak demonstrates the functions and results of Tool #1 - Wide-Area Corn Hybrid Assessment Tool View the video tutorial on how this tool works.
 
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