December 2003


Joe Lauer, Kent Kohn, and Pat Flannery


PDF Format
Excel Format and Cover

The University of Wisconsin Extension-Madison and College of Agricultural and Life Sciences conduct a hybrid corn evaluation program, in cooperation with the Wisconsin Crop Improvement Association. The purpose of this program is to provide unbiased performance comparisons of hybrid seed corn available in Wisconsin. These trials evaluate corn hybrids for both grain and silage production performance.


In 2003, grain and silage performance trials were planted at thirteen locations in four production zones. Both seed companies and university researchers submitted hybrids. Companies with hybrids included in the 2003 trials are listed in Table 1. In the back of the report, hybrids previously tested over the past four years are listed. At most locations trials were divided into early and late maturity trials, based on the hybrid Relative Maturities provided by the companies. The specific Relative Maturities separating early and late trials are listed below.

Map: Wisconsin Relative Maturity Belts and test sites.

Southern Zone
Arlington, Janesville, Lancaster
Early Maturity Trial: 105-day or earlier
Late Maturity Trial: later than 105-day
Table 4
Table 5
South Central Zone
Fond du Lac, Galesville, Hancock (irrigated)
Early Maturity Trial: 100-day or earlier
Late Maturity Trial: later than 100-day
Table 6
Table 7
North Central Zone
Chippewa Falls, Marshfield, Seymour, Valders
Early Maturity Trial: 90-day or earlier
Late Maturity Trial: later than 90-day
Table 8
Table 9
Northern Zone
Spooner (three sites), White Lake
Table 10
Southern Zone
Arlington and Lancaster
Early Maturity Trial: 105-day or earlier
Late Maturity Trial: later than 105-day
Table 11
Table 12
South Central Zone
Fond du Lac and Galesville
Early Maturity Trial: 100-day or earlier
Late Maturity Trial: later than 100-day
Table 13
Table 14
North Central Zone
Chippewa Falls, Marshfield, Valders
Early Maturity Trial: 90-day or earlier
Late Maturity Trial: later than 90-day
Table 15
Table 16
Northern Zone
Spooner (two sites), Rhinelander
  Table 17


Seasonal precipitation and temperature at the trial sites are shown in Table 2. The southwestern quadrant of Wisconsin was affected by a drought where little rain fell from mid-July through August. Grain and silage yields were quite variable. Both grain and silage yields were above normal in northeastern Wisconsin. Spring planting conditions were good until May 4 after which conditions were cooler and dryer than average. Plant emergence and stands were above average and the condition of the crop looked good through the end of July. Corn development was somewhat behind average due to cool early growing conditions, but development caught up and was average by mid-July due to hot, dry conditions. Dry, hot weather during pollination lowered yields in southwestern Wisconsin, especially for late-planted corn and longer-season relative maturity hybrids. Growing degree unit accumulation was slightly behind average throughout the entire growing season. Corn silage harvest began earlier than normal on sites affected by the drought. A killing frost did not occur until early-October. Plant standability was poor in drought affected trials. During the fall harvest season, yields were generally good to excellent, and moisture was low decreasing drying costs.


The seedbed at each location was prepared by either conventional or conservation tillage methods. Fertilizer was applied as indicated by soil tests. Herbicides were applied for weed control and supplemented with cultivation when necessary. Corn rootworm insecticide was applied when the previous crop was corn. Information for each location is summarized in Table 3.


A corn planter with cone units was used at all locations. Two-row plots were planted at all locations. Twenty-five foot long plots were over planted and hand thinned to achieve as near a uniform stand as possible. Each hybrid was grown in at least three separate plots (replicates) at each location to account for field variability.


Grain: Plots were harvested with a self-propelled corn combine. Lodged plants and/or broken stalks were counted, plot grain weights and moisture contents were measured and yields were calculated and adjusted to 15.5% moisture.

Silage: Whole-plant (silage) plots were harvested using a tractor driven, three-point mounted one-row chopper. One row was analyzed for whole plant yield and quality. Kernel milk percent, plot weight, and moisture content were measured, and yields were adjusted to tons dry matter / acre. A sub-sample was collected and analyzed using near infra-red spectroscopy.


Yield results for individual location trials and for multi-location averages are listed in Tables 4 through 18. Within each trial, hybrids are ranked by moisture, averaged over all 2003 trials conducted in that zone. Yield and moisture data for both 2002 and 2003 are provided if the hybrid was entered previously in the 2002 trials. A two-year average for yield is calculated using location data for replications. A hybrid index at the back of this report lists relative maturity ratings, specialty traits and locations tested for each hybrid.


Seed companies use different methods and standards to classify or rate the maturity of corn hybrids. To provide corn producers a "standard" maturity comparison for the hybrids evaluated, the average grain moisture of all hybrids rated by the Minnesota Relative Maturity rating system are shown in each table. Minnesota Relative Maturity ratings are rounded to 5-day increments.

The Minnesota Relative Maturity rating system categorizes corn hybrids into relative maturity groups by comparing harvest grain moisture of a hybrid to the moisture of standard hybrids for each group (see Minnesota Relative Maturity Rating of Corn Hybrids, Agriculture Extension Service, University of Minnesota, Agronomy No. 27). In these Wisconsin results hybrids with lower moisture than a particular relative maturity average are likely to be earlier than that relative maturity, while those with higher grain moisture are most likely later in relative maturity.

Maturity ratings can be found in Table 1 where company maturity ratings, Minnesota Relative Maturity ratings, and Wisconsin Grain and Silage Relative Maturity (GRM and SRM) rating are listed. The Wisconsin ratings are grain or silage moisture at harvest compared to company maturity ratings. Each hybrid in a trial is rated and averaged over all trials in a zone.


Three factors—yield, moisture, and standability—are of primary importance in evaluating and selecting corn hybrids. A performance index (P.I.), which combines these factors in one number, was calculated for multi-location averages for grain trials. This performance index evaluates yield, moisture, and lodged stalks at a 50 (yield): 35 (moisture): 15 (lodged stalks) ratio.The performance index was computed by converting the yield, dry matter, and upright stalk values of each hybrid to a percentage of the test average. Then the performance index for each hybrid that appears in the tables was calculated as follows:

PI = [(Yield x 0.50) + (Dry matter x 0.35) + (Upright stalks x 0.15)] / 100


Corn silage quality was analyzed using near infra-red spectroscopy equations derived from previous work of Drs. Jim Coors and Joe Lauer (UW-Madison). Plot samples were dried, ground, and analyzed for crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), in vitro cell wall digestibility (NDFD), in vitro digestibility (IVD), and starch. Spectral groups and outliers were checked using wet chemistry analysis.

MILK2000 silage performance indices, milk per ton and milk per acre, are calculated using an adaptation by Eric Schwab and Randy Shaver (UW-Madison Dairy Science Department) of the MILK95 model (Undersander, Howard and Shaver; Journal Production Agriculture 6:231-235). In Milk2000, the energy content of corn silage was estimated using a modification of a published summative energy equation (Weiss and co-workers, 1992; Animal Feed Science Technology 39:95-110). In the modified summative equation, CP, fat, NDF, starch, and sugar plus organic acid fractions were included along with their corresponding total-tract digestibility coefficients for estimating the energy content of corn silage. A regression equation developed from literature data was used to predict total tract starch digestibility from the samples whole-plant dry matter content. The samples lab measure of NDFD was used for the NDF digestibility coefficient. Digestibility coefficients used for the CP, fat, and sugar plus organic acid fractions were constants. Dry matter intake was estimated using the samples NDF and NDFD content assuming a 1350 lb. cow consuming a 30% NDF diet. Using National Research Council (NRC, 2000) energy requirements, the intake of energy from corn silage was converted to expected milk per ton. Because the cows maintenance energy requirements were partitioned against the total diet in MILK2000 rather than against only corn silage as was done in MILK95, there was a base increase in our new estimate of milk per ton which was of equal value across all samples that did not influence ranking. Milk per acre was calculated using milk per ton and dry matter yield per acre estimates.


Variations in yield and other characteristics occur because of variations in soil and other growing conditions that lower the precision of the results. Statistical analysis makes it possible to determine, with known probabilities of error, whether a difference is real or whether it might have occurred by chance. Use the appropriate LSD (least significant difference) value at the bottom of the tables to determine true differences.

Least significant differences (LSD’s) at the 10% level of probability are shown. Where the difference between two selected hybrids within a column is equal to or greater than the LSD value at the bottom of the column, you can be sure in nine out of ten chances that there is a real difference between the two hybrid averages. If the difference is less than the LSD value, the difference may still be real, but the experiment has produced no evidence of real differences. Hybrids that were not significantly lower in performance than the highest hybrid in a particular test are indicated with an asterisk.


The results can be used to provide producers with an independent, objective evaluation of performance of unfamiliar hybrids, promoted by seed company sales representatives, compared to competitive hybrids.

Below are suggested steps to follow for selecting top-performing hybrids for next year using these trial results:

  1. Use multi-location average data in shaded areas . Consider single location results with extreme caution.
  2. Begin with trials in the zone(s) nearest you.
  3. Compare hybrids with similar maturities within a trial. You will need to divide most trials into at least two and sometimes three groups with similar average harvest moisture—within about 2% range in moisture.
  4. Make a list of 5 to 10 hybrids with highest 2003 Performance Index within each maturity group within a trial.
  5. Evaluate consistency of performance of the hybrids on your list over years and other zones.
    • Scan 2002 results. Be wary of any hybrids on your list that had a 2002 Performance Index of 100 or lower. Choose two or three of the remaining hybrids that have relatively high Performance Indexes for both 2002 and 2003.
    • Check to see if the hybrids you have chosen were entered in other zones. (For example, some hybrids entered in the Southern Zone Trials, Tables 4 and 5, are also entered in the South Central Zone Trials, Tables 6 and 7).
    • Be wary of any hybrids with a Performance Index of 100 or lower for 2002 or 2003 in any other zones.
  6. Repeat this procedure with about three maturity groups to select top-performing hybrids with a range in maturity, to spread weather risks and harvest time.
  7. Observe relative performance of the hybrids you have chosen based on these trial results in several other reliable, unbiased trials and be wary of any with inconsistent performance.
  8. You might consider including the hybrids you have chosen in your own test plot, primarily to evaluate the way hybrids stand after maturity, dry-down rate, grain quality, or ease of combine-shelling or picking.
  9. Remember that you don’t know what weather conditions (rainfall, temperature) will be like next year. Therefore, the most reliable way to choose hybrids with greatest chance to perform best next year on your farm is to consider performance in 2002 and 2003 over a wide range of locations and climatic conditions.

You are taking a tremendous gamble if you make hybrid selection decisions based on 2003 yield comparisons in only one or two local test plots.


This report is also available on the internet at Hybrid performance for the last 10 years can be summarized using SELECT at the above internet address. This book can be downloaded over the internet in Microsoft Excel and Acrobat PDF formats

About the authors: Joe Lauer is professor of agronomy and also holds an appointment with University of Wisconsin-Extension, Kent Kohn is senior research specialist in agronomy, and Pat Flannery is program manager in agronomy.

This publication is available from your Wisconsin County Extension office or from the Department of Agronomy, 1575 Linden Drive, Madison, WI 53706. Phone (608) 262-1390. This publication can also be obtained on the web at .

University of Wisconsin-Extension, Cooperative Extension, in cooperation with the U.S. Department of Agriculture and Wisconsin counties, publishes this information to further the purpose of the May 8 and June 30, 1914 Acts of Congress; and provides equal opportunities and affirmative action in employment and programming. If you need this material in an alternative format, contact Cooperative Extension Publications at (608) 262-2655 or the UWEX Affirmative Action office. This publication is available free from your Wisconsin county Extension office or from the Department of Agronomy, 1575 Linden Dr., Madison, Wisconsin 53706. Phone (608) 262-1390.

A3653 2003 Wisconsin Hybrid Corn Performance Trials - Grain and Silage.

University of Wisconsin, 1575 Linden Drive - Agronomy, Madison WI  53706    (608) 262-1390
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