Plant population effects on corn yields and ear characteristics to evaluate
thinning in research yield trial plots
by
Kevin J. Betz
A creative component submitted to the graduate faculty
in partial fulfillment of the requirements for the degree of
MASTER OF SCIENCE
Major: Agronomy
Program of Study Committee:
Dr. Roger W. Elmore, Major Professor
Dr. Kenneth J. Moore
Dr. Thomas E. Loynachan
Iowa State University
Ames, Iowa
2010
Copyright © Kevin John Betz 2010. All rights reserved.
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Graduate College
Iowa State University
This is to certify that the master’s creative component of
Kevin J. Betz
has met the creative component requirements of Iowa State University
___________________________________________
Major Professor
___________________________________________
For the Major Program
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Abstract
Advances in genetics and adoption of insect and herbicide-tolerant corn plants have led to a trend
of increasing plant densities across the Corn Belt in recent years. Private seed companies
continue to test hybrids at higher densities. The objective of this study was to evaluate the
effects of varying plant densities on yield to determine if thinning could be reduced. A
secondary objective was to determine if ear characteristics were influenced by increasing plant
density to determine if fixed-ear hybrids were gaining an advantage. A plant density study was
conducted in 2008 to evaluate if plant density affected yield. Four DeKalb commercial corn
hybrids, two classified as fixed-ear and two flexed-ear were, tested at four locations across nine
different plant densities. Densities ranged from 27,412 plants per acre to 38,038 plants per acre.
The main effects of plant density, hybrid, and location had more influence on all factors than did
the hybrid x density interaction. No factor showed a hybrid response to increasing plant
densities. All densities above 30,984 plants per acre plus that of 28,555 plants per acre, yielded
similarly. Fixed ear hybrids had higher number of kernel rows per ear while flex-ear hybrids had
higher kernels per row but these characteristics were not affected by plant density.
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Table of Contents
Abstract………………………………………………………………...3
Introduction…………………………………………………………….6
Literature Review………………………………………………………6
Materials and Methods………………………………………………..17
Results and Discussion………………………………………………..20
Conclusion………………………………………………………….....27
References…………………………………………………………….29
Figures………………………………………………………………...34
Tables…………………………………………………………………48
Appendix……………………………………………………………...51
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Acknowledgements
Acknowledgements
I would like to thank Dr. Roger Elmore for his helpful insight and valuable experience in corn
research for guiding me through this project. Also for his prompt responsiveness to questions
and ability to keep me on track. Thank you to Jesse Drew who was always only a phone call or
e-mail away from answering any questions regarding this program and has been a huge help.
Thank you to Dr. Ron Mowers for his continued help with the analysis. Also thank you to the
rest of the ISU Agronomy staff for making this program possible and for the knowledge that
each has shared during my time in this program.
I would also like to thank the vast number of Monsanto colleagues that were there to offer
insight as well as help me in the planning, planting, thinning, note-taking, harvest and process of
this trial. Without their continued support I could not have achieved this goal of completing this
project. To my managers thank you for the understanding of how to juggle a busy work week
with school work and the flexibility that you allowed me to work on course work and this
project.
Last but not least I would like to thank my beautiful wife for her endless support of me through
this program. From day one until today she has been my number one supporter and I could not
have done this without her to keep me focused and motivated. I would also like to thank the rest
of my family and friends for their continued support as I worked to achieve this goal.
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Plant population effects on corn yields and ear characteristics to evaluate
thinning in research yield trials
Introduction
With estimates of world population to be at 9 billion by 2040, up from the current 6.8 billion, the
importance of supplying food for the world increases. Corn (Zea mays, L.) is a major staple in
the world not only as a food source but also as a fuel source with the recent increase in ethanol
production. The United States alone produces 41 percent of the world’s corn and 38 percent of
the world’s soybeans (Schlenker, 2008). In January 2009, the world supply and demand report
showed an 11.1 million ton increase in global corn demand compared to the 2008 marketing
year, raising the global demand projection to 783.22 million tons (Newsom, 2009). In 2009 the
U.S. planted nearly 86.5 million acres of corn which produced 13.1 billion bushels (National
Agricultural Statistics Services, NASS, 2009). The number of acres of corn grown each year
fluctuates based on factors such as price per bushel of grain and input costs like fertilizer, fuel,
and seed to name a few (Figure 1).
United States produced corn continues in high demand not only in the U.S but globally.
However, as global population increases so does the need for arable land currently in production
for grain to be used as industrial sites, recreation sites or for urbanization. That means
worldwide food production must be met by producing more on the same or less number of acres.
This leads to the fact that grain yield potential must increase at a pace that will keep up with the
global population increase as we continue to have the same or even lesser number of corn acres.
A corn yield increase of 1.5 percent annually is needed to meet this growing demand while from
1982-1994 the annual growth rate of corn yield was only 1.2 percent worldwide (Duvick and
Cassman, 1999). In the U.S corn yields over the past 30 years have increased at a rate of 1.7
bushels per acre per year (Figure 2). This is an annual rate gain of 1.3 percent, still shy of the 1.5
percent needed to meet growing demand.
This increase in yield from 25 bushels per acre average to 151 bushels per acre average in the
United States can be attributed to a number of factors. Introduction of hybrid corn in the 1930’s
and the improvement in genetics has been a great benefit. Advancement in corn genetics is well
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documented and shows how the introduction and improvements in corn hybrids have come about
(Griliches, 1957; Duvick and Cassman, 1999; Duvick, 2005). Crop management practices such
as improved insect and weed control through the use of pesticides, the use of synthetic nitrogen
fertilizer (Duvick, 2005) and the advancements in farm equipment have also been major factors.
The ability for modern corn hybrids to withstand greater environmental stress under higher plant
densities (Tollenaar, 1991) is proof of how genetic advancement has played a role in protecting
yield potential. The continued release of new technologies being presented by the private sector
has led to great promises for increased corn yields. The introduction of Bt (Bacillius
thuringensis) corn hybrids in 1996, the subsequent release of hybrids resistant to glyphosate in
1997 and in 2003 the release of corn rootworm resistant hybrids has provided farmers with
additional control measures. The release of these technologies has caught on very fast across
the US and especially in the Corn Belt (Table 1).
In 2009, 85 percent of the corn planted in the United States contained some type of trait (Table
1). That is an astonishing 70 percent increase since 2000. One reason for the widespread
adoption is that the traited hybrids have increased yields compared to their non-traited, near
isolines especially when subjected to insect pressure. Singer et al. (2003) observed hybrid
differences between two Bt hybrids and their non-traited near isolines at three of four locations
in 2000 and one of three locations in 2001. Yield increases ranged from 5-8 percent depending
on the level of severity for corn borer based on stalk tunneling ratings. Graeber et al. (1999)
compared Bt hybrids to non-Bt hybrids and observed a 4 to 6.6 percent increase in yields as well
as reduced stalk lodging. Lauer and Wedberg (1999) researched initial Bt hybrids introduced in
the northern corn belt and concluded that isoline hybrids yielded 10 percent less than standard or
Bt hybrids under infested or natural conditions. Cox et al. (2009) conducted a study in New
York to compare double and triple stack hybrids to their base genetics. Double-stack hybrids
contain Bt to control European Corn Borer (ECB) and glyphosate resistant traits while the triplestack hybrids contain Bt to control both ECB and corn rootworm while also containing
glyphosate resistance. When averaged over two years and all locations both the triple and
double-stacked hybrids yielded 2.7 percent more than their base genetics in a corn-corn rotation.
They observed low levels of rootworm pressure at all sites. This suggests that most of the yield
increase could be attributed to the control of ECB in these years; one location in 2008 had
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significant corn borer and lodging in the base genetics with the Bt hybrids having less lodging.
Data from Monsanto in 2008 show that Yieldgard VT Triple hybrids out-yielded Roundup
Ready Corn 2 traits at all densities and increased yield potential with higher densities and is
consistent with data from 2007 from a similar study done across fewer locations (Figure 3,
Monsanto, 2008). In 2008 there were 72 locations across 10 states with a varying degree of ECB
and corn rootworm pressure.
The ability for modern hybrids with improved insect and herbicide resistance technology to
better handle stresses could aid in the increase of grain yield. The trend line for the last 10 years
shows an increase of 2.7 bushels per acre per year (Elmore, 2007) and includes the inception of
the above mentioned traits. However caution must be used when using short-term trend lines
because the Corn Belt has had very favorable weather in the last 10 years. Tanura et al.notes that
for the three major corn producing states of Iowa, Illinois and Indiana over the last 10 years the
average June-July precipitation has been at or above average and the July-August temperatures
have been at or below normal (Tannura, 2008). A few exceptions have occurred but the weather
patterns of the last 10 years cannot be ignored when discussing the increase in corn yields
relative to the adoption of new technologies in corn hybrids.
With modern corn hybrids optimum planting density has continued to increase over the years. It
must be noted that planted density or seeding rates will be higher than the actual final plant
density. Germination rate of the seed, pest problems, and soil conditions at planting will
contribute to a percentage of mortality and reduce the final plant density. Data from USDANASS show that final corn crop densities have steadily increased since 1991 across the Corn
Belt and are at or near 30,000 plants per acre average across states with Minnesota being the only
one above 30,000 plants per acre (Figure 4, USDA-NASS, 2009). However, in a 2007 survey
conducted by Pioneer Hi-Bred, over 50 percent of the respondents in North America were
planting over 30,000 seeds per acre or higher. Iowa and Minnesota were leading the way with
over 80 percent over the 30,000 seeds per acre (Figure 5, Paszkiewicz and Butzen, 2007). In just
a 10 year time frame the number of corn acres with seeding rates higher than 30,000 increased by
over 25 percent. Although different results, the two surveys show that the trend of increasing
plant densities is continuing.
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In 2009 plant density recommendations continue to be over 30,000 plants per acre. Jeff Coulter,
University of Minnesota agronomist, recommends a target planting rate of 33,000 seeds per acre
in Minnesota, Bob Nielsen, Purdue University agronomist, recommends no less than 30,000
seeds per acre for a final stand should be planted in Indiana (Stalcup, 2009). The question then
becomes what is the optimum planting density that will achieve the highest yield? The term
optimum must not be confused with the term economic when discussing planting densities.
Optimum plant density is the rate at which the highest yield can be achieved, whereas the
economic optimum would be considered the rate at which the highest revenue per acre is
received. With genetic improvements of modern hybrids comes the increased cost of a unit of
seed. This increase in cost could contribute to densities being reduced but profit margins
remaining the same. Optimum plant density depends on factors such as hybrid, yield goal, soil
fertility, moisture stress levels, seed price, and geographic region (Iowa State University
Extension, PM1885, 2001). In Iowa, data from 2006, averaged over 10 locations show that the
optimum plant density was around 36,000 seeds per acre (Figure 6, Elmore, 2008). Coulter
notes that the optimum plant density in Minnesota is 36,000 plants per acre but economic
optimum ranges between 32,000-34,000 seeds per acre (Coulter, 2009). Monsanto in an ongoing
row width and plant density study has showed the optimum planting density to range between
33,000-38,000 plants per acre. (Figure 7, Monsanto, 2010).
Stanger and Lauer (2006) found that when comparing Bt to non-Bt corn hybrids increasing
population significantly increased grain yield. The experiment at 10 locations across three years
showed that Bt hybrids outyielded non-Bt hybrids by 5.9 to 8 percent as plant densities increased
from 25,000 to 50,000 plants per acre; however the increase in yield was offset by higher costs
thus the economic return was optimized at 33,900 plants per acre. This yield increase in Bt
hybrids is consistent with data from Lauer and Wedberg (1999) and Graeber et al. (1999).
Nafziger (1994) studied two hybrids at two locations which involved two extremely dry years
and found the optimum plant density to be 30,300 plants per acre. Porter et al. (1997) reported
that in Minnesota optimum plant density was much higher than the USDA reported average
harvest density of 26,400 plants per acre for Minnesota. Although their data were inconsistent
over the three year study the maximum yields ranged for densities of 35,000 to 41,000 plants per
acre for those three years. That varies from what Coulter (2009) noted in Minnesota but his
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density recommendations were based on the economic optimum and varies with current
economic conditions. He noted that the economic optimum ranged between 32,000 to 34,000
plants per acre, however, just looking at yield potential the Coulter (2009) data set shows that
100 percent yield potential was reached at 36,000 plants per acre. Widdicombe and Thelen
(2002) showed that plant density had a significant effect on grain yield with a plant density of
36,400 plants per acre yielding the highest; thus was also the highest density tested. The data
from these studies would lead one to believe that by increasing plant densities into the 32,00036,000 plants per acre range there could be an increase in potential yield.
Despite the increase in corn plant density rates over the years, recommendations still vary among
individual hybrids and among private seed corn companies. One aspect to hybrid differences in
plant density is their variation in ear growth habit. Many seed companies characterize hybrids as
being fixed (determinate) or flexed (indeterminate) ear type. Seed companies vary in the amount
of information available in their literature regarding ear types. For instance Pioneer rates each of
their hybrids on a 1-9 scale with the higher rating being the ability for a hybrid to flex its ear size
but does not note if that is in length or girth (Pioneer, 2009). Beck’s Hybrids notes in their
product line-up that ear types range from determinate to flex for length or girth; they also note
medium flex hybrids (Beck’s Hybrids, 2009). Garst classifies ear flex in their hybrids by being
highly flexible, flexible, moderately flexible, semi-determinate and determinate (Garst, 2009).
Monsanto, however under their Dekalb brand does not clearly specify ear type but gives certain
recommendations in their online seed resource guide as to what plant densities hybrids should be
planted. For instance DKC60-51 responds to higher planting densities. If the theory of fixed-ear
type hybrids yielding better at higher densities is true one could assume that DKC60-51 might be
a fixed-ear hybrid based on their statement. Another hybrid DKC62-54 performs well over a
wide range of planting densities. One could assume that DKC62-54 is a more flexed-ear hybrid
based on the theory that ear size flexes and ears are bigger at lower densities thus the yield
potential over a wider range of densities can be obtained. Since DKC65-44 is recommended to
be planted at “medium high to high plant populations for maximum yields,” it is more of a fixedear hybrid (DeKalb, 2009). These are just a few examples of how seed companies vary in the
way they market hybrids based on assumed differences in ear growth habit.
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Fixed-ear type hybrids according to some seed companies are limited in their capacity to
compensate for variations in plant density, where as flexed-ear type hybrids are able to
compensate for variations in plant density (Thomison and Jordan, 1995). This might be
important across the Corn Belt as plant density recommendations vary based on geographic
regions if ear flex is indeed real. The Western Corn Belt for instance is typically drier under
non-irrigated systems and has a much lower recommended planting density than do areas of the
Central or Eastern Corn Belt that receive adequate moisture throughout the growing season.
Studies conducted in Western Nebraska and Kansas show varying results in plant densities that
give maximum yield. Norwood (2001a) showed highest yields being reached at just over 24,000
plants per acre when using later maturing hybrids and planting in late May; however, Blumenthal
et al (2003) showed that yields increased as densities increased from 7,000 plants per acre to
over 11,000 plants per acre with the optimum being 11,012 plants per acre. Nafziger (1994)
noted that even under extremely dry conditions plant densities of 25,000 plants per acre in
Illinois yielded the best under extremely dry conditions with two hybrids whose potential to vary
to plant density was different. If a hybrid can flex and increase ear size at low densities this
could lead to increased yield in parts of the Western Corn Belt where plant densities are lower.
However, this ability to “flex” could also be ideal for areas in which conditions do not warrant
increased densities because ear size would be larger increasing kernels per acre to make up for
the reduction in number of ears per acre. Subsequently in regions with adequate moisture the
ability for fixed-ear hybrids to maximize yields is greater at higher plant densities. This
hypothesis does not exclude flexed-ear hybrids from being grown in areas with adequate
moisture as long as they can yield as well as fixed-ear hybrids under higher densities. With the
improved genetics of modern hybrids the chance to produce satisfactory yields under stressful
conditions is much greater than with hybrids from the past (Duvick, 2005). Increasing plant
density to above 30,000 plants per acre can be considered one of those stresses and the studies
mentioned before show that yield potential is greater at the mid 30,000 plants per acre density
(Coulter, 2009; Elmore and Abendroth, 2008; Widdicombe and Thelen, 2002).
Very little research has been conducted comparing hybrid-ear type and their responses to varying
densities. Thomison and Jordan (1995) looked at yield effects of different ear types at densities
ranging from 16,000- 32,000 plants per acre and found that hybrid differences in ear growth had
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a small effect on yield response to density. Their study showed that the hybrid response to
increasing plant density was less important in determining grain yield than were location, hybrid
and density. Hybrid response to increasing population in their study usually was related to the
difference in the degree of response to densities above 24,000 plants per acre. They concluded
that differences in hybrid response were highly associated with different environmental
conditions over the two-year study and other factors such as soil moisture availability and hybrid
stalk quality should play a greater role in choosing plant density than ear type. In a Wisconsin
study, Hudelson and Carter (1991) evaluated 154 hybrids ranging from early maturing to late and
concluded that there was little correlation between increasing density and seed companies ear
type ratings. Cox (1997) reported that ear type did not contribute much to hybrid variability for
optimum plant density. The optimum density for two flexed-ear hybrids and one fixed-ear
hybrid in the study exceeded 36,000 plants per acre. Widdicombe and Thelen (2002) although
not directly studying ear type showed a significant hybrid response to increasing density for
grain yield among hybrids tested at densities ranging from 22,672 plants per acre to 36,437
plants per acre. They found it was due to differences other than relative maturity, ear type, plant
height and leaf orientation. Nafziger (1994) chose two hybrids whose potential to respond to
differing densities was noted. He found that hybrid response to increasing plant density was not
significant at densities ranging from 10,000 to 35,000 plants per acre. This variability in hybrid
response to density due to ear type indicates that ear type should not be considered a factor when
choosing the optimum planting density.
Corn yield components include plants per acre, ears per plant, kernels per ear and kernel weight.
Kernels per acre is often determined by multiplying plants per acre x ears per plant x kernels per
ear. Determination of kernels per ear is a function of kernels per row (KPR) or ear length and
kernel rows per ear (RPE). Earlier I discussed the importance of how the number of plants per
acre affects yield. When discussing the idea of fixed and flexed-ear corn hybrids the number of
kernels per ear becomes a major factor in determining if a hybrid truly “flexes it ear.” Most of
today’s hybrids have one dominant ear; however prolific hybrids can produce more than one ear
per plant. Ear shoots are developed at multiple nodes on the plant beginning very early in the
plant’s development (Nielsen, 2007). The number of kernels and the weight of those kernels can
change significantly if stress occurs at certain ear development points during the growing season.
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Strachman (2004) reports four major development stages in which kernel number and weight can
be affected: (1) when the plant is setting the maximum number of kernel rows per ear, (2) when
the ear is setting the maximum number of ovules along the length of the ear, usually just before
pollination, (3) during pollination when the maximum number of ovules are pollinated to form
developing embryos and, (4) later during grain fill at growth stage R3-R5 (Ritchie et al. 1992)
when the maximum kernel size is set.
Kernel rows per ear (RPE) are usually determined between V5-V8 growth stages (Strachman,
2004). A rule of thumb is that whatever node the top ear shoot is developed on, the seventh node
below is the growth stage in which RPE is determined (Strachman, 2004). For instance, if a
parent line’s primary ear node is V13 then the RPE will be determined around V6 growth stage
(Strachman, 2004). Kernel rows per ear will always be even because of the splitting of the
ovules to produce two rows. Despite kernel rows being primarily affected by genetics certain
stresses before the V8 growth stage can have a negative impact on the number of kernel rows
(Elmore, 2006). Subedi and Ma (2005) found that nitrogen deficiency before V8 caused a
substantial decrease in not only kernels per row but also RPE and number of kernels per ear.
This shows how important it is to reduce stress during the early part of the growing season. If
flexed-ear hybrids are susceptible to stress at higher densities then we would expect RPE to be
reduced and that the fixed-ear hybrids would be able to maintain their expected kernel row
numbers at higher densities. The fact that RPE is determined early in the growing season as well
as being less affected by environment and more by genetics the ability for flexed-ear hybrids to
respond by decreasing RPE is reduced. Plant density could potentially affect RPE for flexed-ear
hybrids by reducing the number of RPE as densities increase, whereas fixed-ear hybrids would in
theory continue to produce the maximum number of RPE.
The next yield component that affects kernels per ear is the number of kernels per row (KPR).
Like RPE, this factor is determined by genetics but can vary much more due to environmental
stresses than RPE. The number of potential ovules per ear can be upwards of 1,000 and as they
receive pollen develop into a maturing kernel (Elmore and Abendroth, 2006). Maximum KPR is
determined just prior to pollination when ovule formation is complete (Strachman, 2004). The
period of time that brackets pollination is the most critical growth stage in determining the total
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number of kernels per ear (Andrade et al, 1999). Environmental stresses that lead up to V12 can
negatively affect the KPR by reducing the number of ovules formed, while stresses during and
after silking can reduce the total kernels per ear. This is due to the fact that during this period
select ovules depending on the amount and length of the stress are sacrificed to allow the plant to
adequately supply the other ovules. Continued stress during pollination can further result in a
loss of ovules being fertilized thus reducing the number of kernels. Porter et. al. (1997) reported
that ear length was influenced by density, hybrid, environment and row width. Three hybrids all
had reduced ear lengths as densities increased from 25,000 plants per acre to 40,000 plants per
acre. This would mean in theory that a flexed-ear hybrid would typically adjust for those
environmental conditions from early in the ear development stage V5-V6 to just before silking or
around V12. It would be expected that if environmental conditions are favorable during this
period the flexed-ear hybrid could produce more ovules to compensate for the favorable
conditions thus leading to longer ears and potentially more kernels which means more yield. If
stress or good conditions occur during or after pollination the flexed-ear hybrid would not be
able to compensate for this as the number of ovules was already set. Fixed-ear hybrids would
not be able to respond to more favorable growth conditions during the period leading up to
silking, thus not being able to add more kernels. However, theoretical ability for fixed-ear
hybrids to respond to high plant densities could be considered a stress and shows that these
hybrids can still set enough kernels to maximize yields at the optimum density under favorable
conditions. This would also lead to the theory of a fixed-ear hybrid being able to maintain ear
length at higher densities better than a flexed-ear hybrid.
The final component of yield that can affect yield and vary among flexed-ear and fixed-ear
hybrids is kernel weight. Kernel weight multiplied by kernels per acre will give grain yield per
acre. Estimates show that 85% of the final yield is correlated with the total number of kernels
whereas the final 15% is determined by the kernel weight (Stachman, 2004). Light weight
kernels can dramatically reduce yields. Late-season stress caused by drought, insect pressure,
disease or loss of leaf area caused by strong winds or hail can severely reduce kernel weights.
Ahmadi et.al (1993) reported few effects from density on kernel weights, however Lamm and
Trooein (2001) showed that as plant densities increased kernel weights decreased. Cox (1996)
reported a negative quadratic response for kernel weights as plant density was increased.
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Adjusting any of the above yield components will affect final grain yield per acre. For a fixedear hybrid one way to increase the number of kernels per acre is to increase the number of plants
per acre. For flexed-ear hybrids the increase in kernels per acre remains more variable because of
the possibility of ear flex.
If RPE is less affected by the environment than KPR a hybrid’s ability to “flex” its ear would be
seen in KPR or kernel weight differences more so than RPE. Final yield is highly correlated
with the final kernel number per plant at harvest (Andrade, 1999). The question becomes, is the
increase in plants per acre enough to compensate for the probable reduction in RPE, KPR and
kernel weight? We would expect flexed-ear hybrids to reduce kernels per acre and kernel weight
as we increase densities whereas a fixed-ear hybrid should be able to increase kernels per acre at
higher densities.
As planting density recommendations continue to increase at the commercial level the
importance of properly testing pre-commercial hybrids at higher densities becomes very
important. Subsequently, the increase in plant density could negatively affect the selection of
certain genetic families. In particular, those hybrids that show ear flex characteristics could be
getting selected against based on the hypothesis that flexed and fixed-ear hybrids respond
differently to increasing density. The ability for a flexed-ear hybrid to compete at higher
densities could then eliminate them from being selected. Ultimately it is important for the private
sector to release hybrids that will provide the greatest yield potential for producers under a
variety of conditions despite ear type. For the producer they must ultimately select hybrids and
choose planting densities that will provide the most economic return on their farm.
Private seed companies test thousands of hybrids each year across North America in an effort to
continually find improved hybrids that can eventually fill their commercial pipelines. Elite
hybrids, after thorough testing and evaluation, are released as commercial products available to
farmers across the country. The management of test plots is critical to making the proper
evaluation of genetics. One aspect of managing trials is the effort it takes to thin each location.
Thinning includes the removal of plants and plant competition within each plot to get to an
adequate density range for that specific test at each location. Plots are planted to a desired
15
density, however, certain scenarios such as reduced germination require individual tests to be
counted and possibly thinned to a more uniform density. Comparisons among hybrids can then
be made knowing that plant densities of each hybrid are within a specific range. The time and
money it takes to cover these thousands of hybrids and thin appropriately is enormous. Hashemi,
et. al. (2005) found that plants remaining after thinning at V5 showed similar yields as unthinned plants at equal densities, indicating early-season competition had little effect on final
grain yield. The greatest yield differences shown were when plant competition occurred between
V5 and anthesis and between anthesis and grain filling. Yield losses of 8-21% and 6-22% were
observed, respectively, with the higher yield losses at higher densities. The densities in which
they tested ranged from 12,140-48,561 plants per acre (Hashemi, et. al, 2005). Pendelton and
Dungan (1955) found that removal of plants from hills at plant heights of 7, 20, 41 and 70 inches
decreased yield of the remaining plants. As the number of plants removed and plant height
increased yield decreased. Nafziger (2006) showed that as thinning was delayed the ability for
remaining plants to compensate decreased based on the overall number of plants removed
(Figure 8, Nafziger, 2006).
In my time with Monsanto there has been some debate among colleagues of the importance of
thinning in yield trials. While a majority of yield trials are thinned between growth stages V4V7 the time and labor associated with this task is tremendous. As seen from Hashemi et al.
(2005) and Nafziger (2006) delaying thinning beyond V5-V6 has the greatest impact on grain
yield. Timing is not the only factor that must be considered in discussing yield losses within
these plots. Effects of within-row plant spacing and plant emergence have been shown to have
effects on yield, although results are mixed. In numerous studies conducted to quantify yield
losses due to plant space variability (PSV) results have varied from showing yield losses due to
high PSV to other studies not showing a relationship. Nielsen (2004) and Doerge et al. (2002)
showed that with each inch of increase in the standard deviation of plant spacing yields declined
from 2.5 bushels per acre to 3.4 bushels per acre respectively. Conversely Liu et. al. (2004) and
Lauer and Rankin (2004) showed no effect on yield due to PSV. The advancement in research
equipment has helped reduce the amount of PSV seen in recent years with the adoption of
precision planters used for small plot yield trials.
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Study Objectives
The objectives of this study were to determine a range of plant density variability that could be
tolerated without affecting yield comparisons among hybrids. A secondary objective was to look
at the effects of plant density on both fixed-ear and flexed-ear hybrids. In addition we wanted to
determine if thinning could be reduced.
Materials and Methods
Location Information
Field research was conducted in 2008 at four locations. Plots were grown near Thomasboro, IL,
Farmer City, IL, Bloomington, IL and Oxford, IN (Figure 9). Soil at the Thomasboro site is a
very deep, poorly drained soil formed in loess or other silty material with slopes ranging from 02%. Bloomington and Farmer City site soils are very deep, somewhat poorly drained soil
formed in loess on uplands with slopes ranging from 0-5%. Soil at Oxford was a very deep,
somewhat poorly drained soil formed in silty or loamy sediment with slopes ranging from 0-3%.
Soils at each site and general site information are listed in Table 2.
Experimental Design and Plot Layout
The experimental design was a split plot design, with whole plots in a randomized complete
block design with two replications. Densities were main plots and hybrids were sub-plots. The
density whole plots were completely randomized within replicates at each location, and within
each plant density, hybrids were randomized. The treatments consisted of four commercial
hybrids and nine plant densities at each site. Figure 10 is a map of the Farmer City, IL location.
The numbers inside the boxes are the DeKalb hybrid number and the colors represent the nine
different planting densities. Appendix A has a complete list of randomizations for all four
locations with the final densities and hybrids grown.
Plots were planted in four 30-inch rows at a seeding rate of 42,000 seeds per acre and thinned to
the appropriate density between growth stages V4-V6. Plants were randomly cut out using a
dandelion puller. Doubles were removed but plants bordering a skip were avoided when
possible. All four rows were thinned to the final stand. Data were collected from the middle two
rows. Soil preparation was either a conventional till or reduced tillage system depending on the
17
location; previous crop was soybeans (Glycine max L) at all locations. Thomasboro and Oxford
were under conventional tillage which included fall chisel plowing, and soil finishing in the
spring. Bloomington and Farmer City were under reduced tillage which included one pass in the
spring with a soil finisher. The trial consisted of six ranges and 24 columns with subplots being
10 ft wide and 20 ft long. Each study was planted with a minimum of one range of border in the
front and the back to easily identify and reduce edge effects and damage.
Density ranges were determined by previous company density studies which determined that the
highest should be 38,000 plants per acre. I then decreased densities from 38,000 plants per acre
by increments of four percent to a minimum density of 27,412 plants per acre. Due to the row
length and number of seeds planted the calculations used to determine plant densities we actually
ended up being 38,038 plants per acre after thinning. The four percent decrease was determined
so that smaller ranges of densities could be evaluated. Again because of the calculation for
number of plants the four percent was not exact. This is a typical range of densities that are
being planted in these trials.
Hybrids were chosen based on recommendations from plant breeders to represent differences in
ear growth habit and that were common relative maturities (RM) for the locations tested. The
four hybrids ranged from 113-115RM with two considered fixed- ear and two flex-ear (Table 3).
All four hybrids chosen were from the Dekalb brand and gave the best representation of products
in the line-up that met both the RM and ear type requirements. All hybrids contained the
YieldGard VT triple trait (VT3) lineup which consists of yieldgard cornborer, corn rootworm
protection and glyphosate resistant traits.
Locations varied in the amount of fertilizer applied, tillage system, and herbicide used (Table 2).
The cooperators at these sites used practices that they use in their own operations. The planting,
thinning, data collection and harvesting was done by Monsanto. All seed was treated with a
standard seed treatment containing both fungicide and insecticide. In addition, during planting a
soil applied insecticide was applied at all locations in the form of a granular at 5 pounds per acre:
Force 3G [(2,3,5,6-tetrafluoro-4-methylphenyl) methyl-(1ά,3ά)-(Z)-(+)-3-(2-chloro-3,3,3trifluoro-1-propenyl)-2,2-dimethylcyclopropanecarboxylate,(Syngenta, Wilmington, DE).
Thomasboro, Farmer City, and Oxford plots were planted with an 8-row research planter from
18
Seed Research Equipment Solutions (SRES, South Hutchinson, Kansas). Bloomington was
planted with an 8-row Almaco Seed Pro research planter (Almaco, Nevada, Iowa).
Climate
Rainfall from Champaign-Urbana is shown in Table 4; this is the closest weather station to the
three locations in Illinois and table 5 shows data from West Lafayette, Indiana which is
approximately 20 miles from the Oxford location. Due to the scope of the project each field was
not managed the same and location could play a major role in the outcome.
Harvest
Before machine harvest total number of ears were counted and divided by the number of plants
per plot to obtain average number of ears per plant. We hand harvested six ears per plot
randomly from the center two rows to measure ear characteristics avoiding ears from the first
five or last five plants of each row. Kernel rows and kernels per row were collected from these
six ears. Hand harvested ears were shelled and weighed; the weight was added back into the
total weight collected by the combine during harvest to determine overall yield. Grain from the
sampled ears were counted and weighed to determine 100 kernel seed weight. This was done by
using an Old Mill Model 900 (San Antonio, TX) seed counter to count 100 seeds. The one
hundred seeds were then weighed using an Ohaus (Pine Brook, New Jersey) gram scale. Due to
an error, 100 kernel weights were not obtained for the Thomasboro, IL location.
Stalk and root lodging notes were taken before machine harvest on each plot. Plants were
considered stalk lodged if the stalk was broken off below the ear. Root lodging was counted if
any plant was leaning at a 45 degree or more angle from the soil surface. Plant heights were
taken at Thomasboro, Farmer City, and Bloomington plots. Plant height was measured from the
soil surface to the flag leaf on 5 random plants in the plot and an average taken. Machine harvest
was then conducted using a New Holland CR940 or TR99 split plot combine equipped with an
Almaco (Nevada, IA) weigh system. The center two rows of the plots were harvested and total
weight in pounds, moisture and test weight were all collected. Yield was then adjusted to 15.5%
moisture.
19
Statistics
JMP software (SAS Institute Inc, 2007) was used to run an analysis of variance with the standard
least squares model. Differences were considered significant at the P < = 0.05 level. Least
significant means were separated using the Student’s t-test.
Results and Discussion
The 2008 growing season was an above average year for precipitation and a below average year
for temperature in Central Illinois (Table 4), including all four locations in which this experiment
was grown. The Illinois State Climatologist station in Bloomington had an error occur and
climate data was not available. Champaign-Urbana was also the closest station to the Farmer
City location. This is typically a good combination in order to produce high yielding crops and
2008 did exactly that with an average U.S corn yield of 153.9 bushels per acre (NASS, 2009)
compared to past yields with the exception of 2004 which had a record U.S yield of 160.3
bushels per acre (Figure 2). Precipitation in the Champaign, IL area was 11.57 inches above
normal (Table 4) and the fourth wettest year on record. Average temperature was 1.2 degrees
Fahrenheit cooler and the twelfth coolest year on record (Illinois State Climatologist Office,
2009). This was the case for most of the Midwest with above average precipitation and below
average temperatures for the entire growing season (Figure 13 and 14, National Climatic Data
Center, 2010). This combination of below average temperature in July and August (Figure 11,
Illinois State Climatologist Office, 2009) and above average precipitation in June and July
(Figure 12, Illinois State Climatologist Office, 2009) can play a major role in producing higher
yields (Tannura et al, 2008). All averages are based on climatological data from 1971-2000. The
above average rain introduced many environmental conditions which provided challenges in
collecting quality data. Crop yields for the study averaged over 215 bushels/acre averaged over
all densities, hybrids and locations.
20
Yield Results
The major point of interest was determining if there was going to be a hybrid response to
increasing plant density. The hybrids responded the same to plant density across locations. The
main effects of hybrid, density and location were more important in determining yield than the
interactions. Plant density when analyzed across both hybrids and locations had a significant
effect on grain yield in this study (Figure 15). All plant densities above 30,984 plants per acre
plus that of 28,555 plants per acre yielded the same ranging from 216-220 bushels per acre. The
other two densities yielded different and averaged 207-208 bushels per acre. The effect of plant
density on grain yield shown in this study is consistent with what Widdicombe and Thelen
(2002), Thomison and Jordan (1995) and Nafziger (1994) reported. An interesting note is that
the two year study of Thomison and Jordan (1995) showed that increasing densities improved
yield by 28 percent in 1990 when greater precipitation and cooler temperatures occurred,
compared to 1991 when increasing population only increased yield 7 percent when limited
precipitation and warmer temperatures occurred during the reproductive stages. Nafziger (1994)
showed in dry years very little yield response in contrast to a year with adequate rainfall where
yield response was much greater with increasing densities. The yield response of this study was
not as much as those studies but the tighter range of densities possibly leads to that. It does
however show that favorable weather conditions seem to lead to a higher yield response to
increasing density. This could be due to the fact that the plant is under less stress during the
growing season.
This effect of plant density is similar to other research data from Monsanto gathered in 2008 and
2009 on a larger scale where maximum yield potential was seen between 33,000-38,000 plants
per acre (Monsanto, 2010). If seed company and public university data consistently show
optimum planting densities above 32,000 plants per acre are ideal for greater yields (Elmore,
2008; Coulter, 2009; Stalcup, 2009) we would expect higher grain yield at higher plant densities.
That is not the case exactly, but we do show that densities over 30,000 plants per acre yield
similar under these conditions. These data suggest that densities could be increased up to
38,000 plants per acre with no yield penalty, however, once densities are dropped to below
28,500 plants per acre a yield penalty is possible. An interesting feature of these data is that
21
densities from 27,412-30,984 plants per acre increase yield sharply while densities from 30,98438,000 plants per acre have relatively stable yields.
Grain yield of hybrids differed when tested over densities and locations (Figure 16). The two
highest yielding hybrids in the study were DKC64-79 and DKC 63-42 which were both flex-ear
hybrids (Figure 16). Only DKC64-79 is significantly different than the two fixed-ear hybrids.
Despite hybrids showing a significant response in yield, these differences are not consistent and
no hybrid response is noted. Hybrid differences in yield must be attributed to factors other than
plant density and location. Even though the two flex-ear hybrids were higher yielding, the lack of
hybrid response to increasing density tells us that different genetics for ear type are not
influenced by plant density. Based on these results the lack of hybrid x density interaction
answers our question of whether or not increasing plant density will favor fixed-ear hybrids in
test plots. Thomison and Jordan (1995) showed a significant hybrid x density interaction in 1990
but not in 1991 when conditions were hotter and drier. The four hybrids they tested were a
single ear fixed, single ear flex, semiprolific and prolific. The semiprolific, flex and fixed ear
hybrids showed similar responses to increasing density across locations and years. They
concluded that hybrid x density interactions had less importance in final grain yield than did the
main effects of location, density, and hybrid and that yield response to increasing density was
strongly related to varying environmental conditions. Flexed-ear hybrids yielded as well as
fixed-ear hybrids at varying densities; individual effects of hybrid, density and location were
more important than plant density in determining yield for this study.
Grain Moisture
Grain moisture content at harvest was influenced by hybrid, density and location. No hybrid
response to increasing plant density was noted. Moisture content varied inconsistently with plant
density (Figure 17). Moisture content between all densities ranged from 25.5 percent to 26.4
percent. This is consistent with what Cox (1997) showed. Porter et. al. (1997) showed a mixed
response to grain moisture content to increasing density in a three year study. The four hybrids
tested in this study ranged from 113-115 relative maturity (RM) with the 113 RM hybrid having
the highest moisture content (Figure 18). Hybrid differences were more significant with a 2.4
percent difference between the wettest and driest hybrid (Figure 18). Despite the small range in
22
grain moisture hybrids differed. This varies from what Widdicombe and Thelen (2002) observed
as they showed a hybrid x density interaction due to relative maturity of the hybrids tested. DKC
64-24 had the lowest grain moisture content and DKC 63-42 had the highest moisture when
averaged across all densities and locations. Ear growth habit seemed to have no effect on
moisture content. The hybrid x location interaction was significant for grain moisture content.
Location differences can be primarily attributed to the difference in harvest dates (Table 2). Due
to the scope of trial locations it was not feasible to get each site harvested in the same time
frame. The Bloomington, IL site had the lowest average moisture; Farmer City, IL had the
highest moisture averaged across all replications, hybrids, and densities.
Test Weight
Test weight was affected by plant density, hybrid and location but no hybrid response to
increasing plant density was seen. The highest test weight was observed for DKC65-44 and the
lowest test weight was observed for DKC63-42 (Figure 19.) All hybrids and plant densities had
test weight above 57 pounds per bushel for the study. When compared across plant densities and
hybrids, Oxford, IN had the highest test weight with an average of 61.0 pounds per bushel. The
favorable growing conditions during grain fill led to increased test weights. Porter et. al. (1997)
showed a trend that as plant density increased test weight decreased. This was not seen with
these data as there was no hybrid response to increasing plant density. There was a hybrid x
location and a location x population interactions for test weight. As with yield and moisture,
location differences were less important to our objective and will not be discussed any further.
Favorable climatic conditions through the growing season and primarily during grain fill had a
greater effect on test weight than plant density. This is evident because of the high overall test
weights for the study relative to the industry standard of 56 pounds per bushel. With cooler than
normal temperatures in July and August and abundant rainfall (Figure 11 & 12) plants had very
little stress during grain filling, this is consistent with Porter et al. (1997) and Widdicombe and
Thelen (2002).
Number of Kernel Rows per Ear
Hybrid and location affected the number of kernel rows per ear (RPE) but their interactions were
not significant (P>0.05). This goes with what we expected in terms of the hybrids varying in
23
sensitivity to early-season competition, while RPE was being determined. This answers the
question of whether or not flex-ear hybrids would have lower RPE at higher densities. Kernel
rows per ear of the hybrids responded the same to increasing plant densities and thus increasing
plant density did not affect RPE in either flex or fixed-ear hybrids. Kernel rows per ear remained
very similar as plant density increased. Hybrids differed in RPE as we would have expected
because this factor is influenced more by genetics. The two fixed-ear hybrids had the highest
RPE while the two flex-eared hybrids had lower average RPE across all densities and locations
(Figure 20). However the difference between the lowest hybrid DKC64-79 a flex-ear and the
highest DKC65-44 a fixed-ear was only 1.9 kernel rows. This partially contradicts what Bavec
and Bavec (2002) found. In their study plant density significantly affected the number of kernel
rows, but hybrids responded the same at all densities. This shows that even though RPE is
primarily influenced by genetics, plant density can have an effect on it as well although not seen
in this study. One interesting note is that DKC64-79 had the lowest number of kernel rows but
had the highest average yield. This would indicate that yield is influenced by another factor
besides RPE, such as the number of kernels per row or the kernel weight. Both fixed-ear hybrids
had the highest average number of kernel rows but the lowest yields for the study. Location also
had a significant effect on RPE for the study but is less important to our objectives. Differences
in growing environment as well as differences in nutrient availability may have contributed to
these differences among locations. Despite the flex-ear hybrids having the lowest RPE for the
study they did so at all plant densities, showing that hybrid differences were more significant
than densities. Early-season conditions in 2008 were ideal with plenty of moisture available for
plant growth. The stress of increasing density was not enough to affect RPE under favorable
environmental conditions. It leaves us the question of how would RPE be affected under less
ideal conditions as density is increased?
Kernels Per Row
Knowing that RPE is determined early in the growing season around V5-V8 (Strachman, 2004)
leaving little time for that component to “flex” we would then expect the true ability of a hybrid
to flex ear size would be seen in the ear length or number of kernels per row (KPR) or kernel
weight. Kernel rows per ear are still important because under early-season stress hybrids can
reduce RPE and ultimately affect yield in those situations. It was shown above that RPE were
24
more affected by hybrid than plant density, thus the ability for a hybrid to flex in terms of RPE
was limited in this study. As discussed earlier maximum KPR is determined just prior to
pollination, however environmental stresses leading up to this and during pollination can
adversely affect KPR by reducing ovule formation (Strachman, 2004). The main effects of
hybrid, density, and location all affected the number of kernels per row. Hybrid x location, and
location x density interactions were also significant. However, the hybrid x density interaction
was not significant for this trait. The general trend averaged over all locations and hybrids
showed that the number of kernels per row decreased as density increased (Figure 21).
Kernels per row can be broken down as follows: the two lowest densities had the highest KPR,
the next four densities were then all similar followed by 35,020 and 36,480 plants per acre
having similar KPR and finally 38,000 plants per acre had the lowest KPR. These data show that
as density increases KPR is reduced. However the reduction in KPR was not enough to reduce
grain yield and the lower yielding densities had the higher KPR. The flexed-ear hybrids had an
average of 33.5 KPR compared to the fixed-ear hybrids which averaged 31.2 and 30.2 when
averaged across all densities and locations (Figure 22). The “flex” ability was seen in this study
by the hybrids being able to increase ear size by having longer ears. The hybrids ability under
favorable environmental conditions to maximize ovule formation prior to pollination was seen in
this study. These data would indicate that yield is much more affected by KPR than the RPE
since the two flexed-ear hybrids showed the lowest KPR but the highest RPE and were ranked
number one and two in yield for this study. The fact that both flexed-ear hybrids had higher
KPR and that as plant densities increased KPR decreased is interesting. Changes in KPR were
consistent across all hybrids at all plant densities.
100 Kernel Weight
Kernel weight on average decreased as plant densities increased (Figure 23). Data were only
collected on three of the four locations for this trait. The data are somewhat variable, however,
consistent with Hashemi et al. (2005) and Tetio-Kagho and Gardner (1988). Similar to the other
yield components already discussed, the main effects of hybrid, density, and location all affected
kernel weight. Again there was no hybrid x density interaction for this trait. The highest kernel
weight was seen at 28,555 plants per acre and the second highest at 30,984 plants per acre, while
25
the plant densities from 32,275-38,000 had the lowest kernel weights. The range from lowest
kernel weight at 36,480 plants per acre to 28,555 plants per acre was 31.1-34.9 grams per 100
kernels. Norwood (2001b) showed a similar trend in that kernel weight either decreased slightly
or did not change in a three-year study comparing five different hybrids and two planting dates in
Southwest Kansas. Norwood (2001b) also noted that five percent of the total variation in yield
was attributed to kernel weight where as 58-64 percent of the yield variation was due to kernels
per ear. Three of the four hybrids had similar kernel weights with only DKC 63-42 being
different. It ranged 1.2-1.8 grams per 100 kernels less than the other hybrids (Data not shown).
This hybrid was also the wettest in terms of moisture at harvest meaning that it was later
maturing than the other hybrids tested. It would seem that hybrid ear type has no effect on
kernel weights and the difference in hybrids could be contributed to a factor other than density
and ear type. The ability of these specific hybrids to perform under high plant densities
compensates for the fact that the number of kernels per row and the kernel weights were
decreased as shown by the yield data previously (Figure 15).
Agronomic Factors
One of the biggest fears with increasing plant density is the increased risk associated with
lodging. The perception is that as plant density increases so does lodging. This still might be the
case but newer hybrids seem to have a much better tolerance for lodging than older hybrids and
standability at higher plant densities is much better (Tollenaar, 1989). Overall very little stalk
lodging occurred at any of the locations. Of the lodging that was seen the overall trend for stalk
lodging was that as densities increased lodging was more prevalent. However, it must be noted
that the amount of stalk lodging for the trial was very minimal and yields seemed unaffected by
the lodging. The highest amount of stalk lodging present for the study was 3 percent of one plot
in Oxford, IN and that plot yielded 235 bushels per acre. The average percent of stalk lodging for
densities was from zero percent to 0.5 percent. The overall mean for all treatments at all
locations for stalk lodging was 0.2 percent.
The highest level of root lodging, 16 percent, occurred on a few plots in Oxford, IN (Figure 24).
The lowest yield on those plots with 16 percent root lodging was never lower than 225 bushels
per acre. The main effects of hybrid, density, and location again were significant for root
26
lodging. The flexed-ear hybrids ranked 1 and 2 in percent root lodging, while the plant densities
ranging from 35,020-38,000 plants per acre were significantly different (Figure 24). The overall
mean for all treatments at all locations for root lodging was 1.2 percent. The range in percent
root lodging from the lowest to highest was 0.2 to 2.7 percent. Although minimal the data would
indicate that as densities are increased so is root lodging. It is also interesting that the flexed-ear
hybrids had the largest ears in terms of KPR and also the highest root lodging. However,
because of such minimal lodging it is hard to draw any conclusions for both neither stalk nor root
lodging.
Plant heights were collected at three of the four locations in the trial. There was no hybrid x
density interaction for plant height but there were hybrid and location differences which we
expected (Data not shown). Density had no effect on plant height in this trial.
Conclusion
Results from this study showed no hybrid x density interactions for yield, grain moisture, test
weight, kernel row numbers, and kernels per ear, kernel weight, stalk lodging, root lodging or
plant height. The main effects of hybrid, density and location were more important in
determining significant differences. Very high yields were achieved with 215 bushels per acre
averaged over four hybrids, nine densities and four locations. Overall the trend was that as yield
increased density increased, and densities ranging from 30,984-38,000 plants per acre including
28,555 plants per acre showed no difference in yield, meaning that a large range of densities
yielded similar. The lowest yielding density was the lowest density tested. The flexed-ear
hybrids were the two highest yielding for the study. The number of kernel rows per ear was less
affected by density than was the number of kernels per row and kernel weight. As plant density
increased the number of kernels per row and kernel weights decreased. This decrease was not
enough to reduce yields and the hybrids were able to compensate enough at higher densities to
produce more kernels per acre thus yield higher. Root and stalk lodging were minimal for the
study but the general trend for root lodging showed a higher percentage of plants lodged at the
higher densities and flexed-ear hybrids had higher root lodging.
27
It is difficult to conclude that a decrease in thinning could be warranted based onone year of data
at four locations. Especially since the environmental conditions for the growing season were
very favorable and virtually no heat or moisture stress was seen. However, based on this limited
set of data it might be worthwhile to investigate further the effects of a reduction in thinning and
subsequently the impact it has on the quality of data being collected. Plant densities from 30,98438,000 plants per acre showed no difference for yield. If the range of plant densities can be
increased without causing a negative impact on the comparison of yields between plots then the
amount of thinning could be reduced or the guidelines that are in place now could be made more
flexible. This could be a huge cost-savings without sacrificing the quality of data being collected.
When designing this study we anticipated as plant density varied so would yield but for the most
part that was not the case. Only two plant densities, 27,412 and 29,744 plants per acre yielded
less than the other seven densities. This study also shows that the lower plant densities limited
the hybrids ability to yield better and these densities should be on the low end of what should be
used to evaluate research yield trial plots.
The results also showed that for the second objective of comparing fixed-ear and flexed-ear
hybrids that the flexed-ear hybrids had higher yields than the fixed-ear when averaged over all
plant densities. We expected the fixed-ear hybrids would yield more at the higher plant densities
but this was not the case. This answers the question of whether or not the fixed-ear hybrids are
being given an advantage in test plots by increasing the plant density and based on this they are
not. Plant density did affect the yield components of kernels per row and 100 kernel weights by
reducing both as densities increased. It was not enough to reduce yield. The number of kernel
rows per ear was less affected by plant density and most likely is due to the plant’s ability to
determine that factor early in its development. Increasing plant density in research plots does not
seem to favor either a fixed-ear or flexed-ear hybrid and thus should not be a major concern.
Again further studies must be completed to validate this but this initial study would indicate that
would be true.
28
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31
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32
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33
Figures
Figure 1. Total Corn Acres Planted in the Unites States, 1926-2009 (National Agricultural
Statistics Services, NASS, 2009).
Figure 2. United States corn yields from 1900-2008 (National Agricultural Statistics Service,
NASS, 2009).
180
Yield (Bu/Acre)
160
140
120
100
80
60
40
20
0
1900
1915
1930
1945
1960
Year
34
1975
1990
2005
Figure 3. Impact of trait and population on yield potential. Monsanto data, 2008.
Figure 4. Corn crop densities for states in the Corn Belt (National Agricultural Statistics Service,
NASS, 2009).
35000
Plants per acre
30000
25000
20000
15000
10000
5000
0
IL
IN
IA
MN
NE
State
1991
1995
2000
35
2005
2009
OH
WI
Figure 5. Percent of corn acres with seeding rates of 30,000 seeds/acre or higher. Pioneer HiBred Brand Concentration, Economics and Analysis (Paszkiewicz and Butzen, 2007)
Figure 6. Corn yield as a percent of maximum at varying seeding rates. Data is averaged across
10 locations in 2006. (Iowa State University Extension, 2008)
36
Figure 7. Effect of plant density by year averaged across locations, row widths and germplasm
(figure from Monsanto, 2010).
Figure 8. Response of corn plants to removal of competition by thinning at different growth
stages. Initial plant population of 40,000 per acre was decreased to 35,000 (by 12.5%), 30,000
(25%), 25,000 (37.5%), and 20,000 (50%) at stages indicated. Data are from a study conducted
at Urbana, Illinois, 1995-96 (Nafziger, 2006).
37
Figure 9. 2008 Trial Locations marked with pushpin
Figure 10. Split-plot design with whole plot-plant densities in a randomized complete block
design with two replications at the Farmer City, IL location. Subplots were hybrids with the
DeKalb brand number represented in each colored square.
Plant Density per acre
27404
28631
29858
31085
33312
33539
35175
36402
B
B
B
38038
9
B
Rep 2
8
63-42
65-44
64-79
64-24
63-42
64-79
64-24
65-44
64-79
65-44
63-42
64-24
Rep2
7
64-24
64-79
65-44
63-42
63-42
64-24
65-44
64-79
64-24
64-79
65-44
63-42
Rep2
6
64-79
65-44
64-24
63-42
63-42
64-79
65-44
64-24
64-24
63-42
65-44
64-79
Rep1
5
64-24
65-44
63-42
64-79
65-44
64-24
64-79
63-42
64-24
64-79
63-42
65-44
Rep1
4
64-24
64-79
63-42
65-44
64-24
64-79
65-44
63-42
64-24
63-42
64-79
65-44
Rep1
3
64-24
63-42
64-44
64-79
63-42
65-44
64-79
6424
64-79
64-24
65-44
63-42
2
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
1
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
Col
1
2
3
4
5
6
7
8
9
10 11 12 13
14
15
16
17 18 19
20
21
22
23 24
Range
B
B
B
B
B
B
B
B
B
B
B
38
B
B
B
B
B
B
B
B
B
B
B
B
B
B
Figure 11. 2008 monthly temperature departures from 1971-2000 average for ChampaignUrbana (Illinois State Climatologist Office, 2009).
Figure 12. 2008 monthly precipitation departures from 1971-2000 average for ChampaignUrbana. (Illinois State Climatologist Office, 2009).
39
Figure 13. Precipitation for United States based on long term averages.
Figure 14. Temperature for the United States based on long term averages
40
Figure 15. Plant Density effects on yield averaged across 4 locations and 4 hybrids.
Grain Yield (bu/acre)
250
216AB
207C+
220A
217A
208BC
217A
218A
217A
218A
200
150
100
50
0
38
00
0
36
48
0
35
02
9
33
61
5
32
27
4
30
98
4
29
74
5
55
28
27
41
2
0
Plant Density (plants/acre)
† Means followed by same letter are not different
Figure 16. Hybrid response averaged by plant density, location and replications
Grain Yield bu/acre
250
217AB+ 221A
212B
212B
200
DKC63-42-Med Flex
150
DKC64-79-Flex
DKC64-24-Fixed
100
DKC65-44-Fixed
50
0
C
DK
63
-4
M
2-
ed
ex
Fl
C
DK
64
7
ex
Fl
9
C
DK
64
2
xe
Fi
4
d
C
DK
65
4
xe
Fi
4
d
Hybrid-Ear Type
† Means followed by same letter are not different
41
Figure 17. Plant population effect on grain moisture averaged over 4 locations and 9 densities.
Grain Moisture %
34
32
30
28
26
26.3AB+ 26.3ABC25.9BCD 26.5A 25.9BCD 25.6D
25.7D
25.8CD
25.5D
24
22
0
38
00
0
36
48
0
35
02
9
33
61
5
32
27
4
30
98
4
29
74
5
55
28
27
41
2
20
Density (plants/acre)
† Means followed by same letter are not different
30
29
28
27
26
25
24
23
22
21
20
27.1A+
26.6B
xe
d
DK
C6
544
-F
i
xe
d
24.7D
DK
C6
424
-F
i
DK
C6
479
-F
ed
DK
C6
342
-M
le
x
25.5C
Fl
ex
Grain Moisture %
Figure 18. Hybrid effect on grain moisture averaged over 4 locations and 9 densities.
Hybrid-Ear Type
† Means followed by same letter are not different
42
Figure 19. Grain test weight of hybrids averaged across 9 plant densities and 4 locations.
60
Test weight (lbs/bushel)
59
58.8A
58.4B
58
57.9C
57.5D+
57
56
55
54
53
52
51
d
d
-F
ixe
-F
ixe
-4
4
-2
4
Hybrid-Ear Type
† Means followed by same letter are not different
43
65
KC
D
D
KC
64
64
KC
D
D
KC
63
-4
2
-M
-7
9
ed
-F
le
x
Fl
ex
50
d
-F
ix
e
d
D
KC
64
-
65
-
24
79
64
D
KC
17.5A
-F
ix
e
Fl
ex
ed
-M
42
D
KC
63
-
17.5A
15.6C
44
16.5B+
D
KC
20
18
16
14
12
10
8
6
4
2
0
-F
le
x
Kernel Rows per Ear
Figure 20. Number of kernel rows per ear by hybrid averaged across 9 plant densities and 4
locations.
Hybrid-Ear Type
† Means followed by same letter are not different
35
34
33
32
31
30
29
28
27
33.7A+ 34.0A
32.8B 32.8B
32.1B 32.2BC
31.3CD
30.7D
29.6E
27
41
2
28
55
5
29
74
4
30
98
4
32
27
5
33
61
9
35
02
0
36
48
0
38
00
0
Kernels/Row
Figure 21. Number of kernels per row averaged across 4 hybrids and 4 locations.
Plant Density (plants/acre)
† Means followed by same letter are not different
44
Figure 22. Plant population effect on kernels per row among 4 hybrids averaged across 9
populations and 4 locations.
33.5A+
33.6A
31.3B
-F
ixe
d
KC
D
D
KC
D
D
KC
65
-4
4
-F
ixe
d
64
64
KC
-4
2
63
30.2C
-2
4
-7
9
-M
ed
Fl
-F
le
x
ex
Kernels/Row
40
35
30
25
20
15
10
5
0
Hybrid-Ear Type
† Means followed by same letter are not different
Figure 23. Plant density effect on kernel weight
Kernel Weight (grams/100K)
36
34.8A
35
34
34.7A
33.7B+
33.3B
32.6CD
33
32.3C
32.2C
32
31.7CD
31.2D
31
30
29
27412 28555 29744
30984 32275 33619
35020 36480 38000
Plant Density (plants/acre)
† Means followed by same letter are not different
45
Figure 24. Plant density effect on root lodging.
Root lodging %
5.0
4.0
2.8A
3.0
2.4AB
1.8ABC
2.0
1.0
1.1BCD 1.0CD 1.1BCD
0.7CD+
0.4D
0.3D
28555
29744
0.0
27412
30984
32275
33619
Plant Density (plants/acre)
† Means followed by same letter are not different
46
35020
36480
38000
Tables
Table 1. United States Department of Agriculture-Economic Research Service, USDA-ERS,
2009.
Table 1. Genetically engineered (GE) corn varieties by State and United States, 2000-2009 Herbicide-tolerant only
.
Insect-resistant (Bt) only
.
State
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Percent of all corn planted
.
Percent of all corn planted
Illinois
13
12
18
23
26
25
24
19
13
10
3
3
3
4
5
6
12
15
15
15
Indiana
7
6
7
8
11
11
13
12
7
7
4
6
6
7
8
11
15
17
16
17
Iowa
23
25
31
33
36
35
32
22
16
14
5
6
7
8
10
14
14
19
15
15
Kansas
25
26
25
25
25
23
23
25
25
24
7
11
15
17
24
30
33
36
30
29
Michigan
8
8
12
18
15
15
16
19
15
13
4
7
8
14
14
20
18
22
24
20
Minnesota
28
25
29
31
35
33
28
26
19
23
7
7
11
15
17
22
29
32
29
24
Missouri
20
23
27
32
32
37
38
30
27
23
6
8
6
9
13
12
14
19
21
17
Nebraska
24
24
34
36
41
39
37
31
27
26
8
8
9
11
13
18
24
23
24
23
North Dakota2/
21
29
29
24
22
39
34
37
34
30
Ohio
6
7
6
6
8
9
8
9
12
15
3
4
3
3
4
7
13
12
17
17
South Dakota
35
30
33
34
28
30
20
16
7
6
11
14
23
24
30
31
32
34
30
25
Texas2/
21
27
22
20
21
42
37
37
31
30
Wisconsin
13
11
15
21
22
22
22
19
14
13
4
6
9
9
14
18
18
23
26
27
Other States 1/
10
11
14
17
19
19
20
20
20
20
6
8
12
17
21
19
25
33
32
30
U.S.
18
18
22
25
27
26
25
21
17
17
6
7
9
11
14
17
21
24
23
22
Stacked gene varieties
.
All GE varieties
.
State
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Percent of all corn planted
.
Percent of all corn planted
Illinois
1
1
1
1
2
5
19
40
52
59
17
16
22
28
33
36
55
74
80
84
Indiana
*
*
*
1
2
4
12
30
55
55
11
12
13
16
21
26
40
59
78
79
Iowa
2
1
3
4
8
11
18
37
53
57
30
32
41
45
54
60
64
78
84
86
Kansas
1
1
2
5
5
10
12
21
35
38
33
38
43
47
54
63
68
82
90
91
Michigan
*
2
2
3
4
5
10
19
33
42
12
17
22
35
33
40
44
60
72
75
Minnesota
2
4
4
7
11
11
16
28
40
41
37
36
44
53
63
66
73
86
88
88
Missouri
2
1
2
1
4
6
7
13
22
37
28
32
34
42
49
55
59
62
70
77
Nebraska
2
2
4
5
6
12
15
25
35
42
34
34
46
52
60
69
76
79
86
91
North Dakota2/
15
20
22
31
41
75
83
88
89
93
Ohio
*
*
*
*
1
2
5
20
37
35
9
11
9
9
13
18
26
41
66
67
South Dakota
2
3
10
17
21
22
34
43
58
65
48
47
66
75
79
83
86
93
95
96
Texas2/
9
13
20
27
33
72
77
79
78
84
Wisconsin
1
1
2
2
2
6
10
22
35
37
18
18
26
32
38
46
50
64
75
77
Other States 1/
1
1
2
2
6
6
U.S.
1
1
2
4
6
9
* Less than 1 percent.
1/ Includes all other States in the corn estimating program
2/Estimates published individually beginning in 2005. 10
15
14
28
22
40
47
28
46
17
25
20
26
27
34
36
40
46
47
44
52
55
61
67
73
74
80
78
85
Table 2. Soil type and general site information for four locations in 2008.
Location
Soil Common Name
(Taxonomic name),
Planting
Date
Harvest
Date
Fertilizer rates
lbs/acre
N
P
K
Farmer City, IL
Ipava silt loam (fine, smectitic,
mesic Aquic Argiudolls)
5 May
12 October
236
92
120
Bicep II, atrazine, callisto,
cultivation
Bloomington,
IL
Ipava silt loam (fine, smectitic,
mesic Aquic Argiudolls)
5 May
17 October
170
40
120
Lumax, atrazine, callisto,
cultivation
Thomasboro,
IL
Drummer silty clay (finesilty,mixed,superactive,mesic,
Typic Endoaquolls)
4 May
3 October
290
NA*
NA*
Harness Xtra, atrazine,
callisto, option, cultivation
Oxford, IN
Darroch silt loam (fine-loamy,
mixed, superactive mesic
Aquic Argiudolls)
6 May
8 October
147.5
52
120
Degree Xtra, laudis, aatrex,
cultivation
Weed Control, Chemicals
*No phosphorus or potassium fertilizer was applied this crop year
Table 3. Hybrids, relative maturities, trait and ear type used in study (Stangland, 2008).
Hybrid
DKC 63-42
DKC 64-24
DKC 64-79
DKC 65-44
RM
113
114
114
115
Trait
VT3
VT3
VT3
VT3
Ear Type
Med-Flex
Fixed
Flexed
Fixed
48
Table 4. Climate summary for Champaign-Urbana. (Illinois State Water Survey, 2008).
Month
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2008 Depart
Avg
Max
35
33.3
47.3
61.9
68.8
83.4
83.9
82.4
77.5
66.5
48
34.4
60.2
-1.1
Temperature (°F)
Avg
Avg
Min
Mean High
16.5
25.8
67
17.8
25.6
55
30
38.7
67
40.5
51.2
81
48
58.4
86
63
73.2
89
63.7
73.8
89
61.7
72.1
90
57.3
67.4
92
43
54.8
85
31
39.5
73
17.7
26.1
62
40.9
50.6
92
-1.2
-1.2
Low
-4
-3
13
28
37
55
56
55
47
29
14
-2
-4
Precipitation
Total Snow
(in)
(in)
2.31
1.3
5.96 15.2
2.84
2.0
3.01
0.0
6.07
0.0
6.4
0.0
7.89
0.0
0.78
0.0
8.15
0.0
2.96
0.0
1.31
2.4
4.89
4.2
52.57 25.1
11.52 -1.1
Degree Days
Heat
1209
1137
808
413
215
0
0
0
29
327
760
1201
6099
274
Cool
0
0
0
7
22
251
279
227
109
18
0
0
913
-73
Wind (mph)
Corn
203
326
698
736
687
529
3179
-26
Dir
232
276
328
218
264
241
242
5
8
261
252
233
213
Speed
7.9
6.9
6.6
6.7
5.1
4.4
3.1
2.6
2.3
3.2
5
7.7
5.1
-1.3
Peak
Gust
46.4
33.7
31.6
37.6
31.2
46.2
32.9
26.8
24.2
31
23.8
35.6
46.4
Degree Days: heating and cooling base 65°F. Corn Growing Degree Days base 50°F with a max temp cutoff at
86°F.
Depart=Departures from the 1971-2000 30-year average
Table 5. Climate summary for West Lafayette, IN, 2008 (Indiana State Climate Office, 2010).
(129430) WEST LAFAYETTE 6 NW_IN
Precipitation
Month
(in)
Avg Max Temp (F)
Jan-08
Feb-08
Mar-08
Apr-08
May-08
Jun-08
Jul-08
Aug-08
Sep-08
Oct-08
Nov-08
Dec-08
Avg Min
Temp
2.49
35
5.64
33
2.23
46
2.76
62
5.95
68
4.89
83
3.82
83
2.4
82
4.24
80
1.79
66
1.09
50
5.94
36
43.24
60.3
2008 Depart
1.75
-1.5
Corn Growing Degree Days base 50°F with a max temp cutoff at 86°F.
Depart=Departures from the 1971-2000 30-year average
49
GDU
15
14
27
40
46
62
62
57
53
39
31
16
38.5
-2.7
15
0
2
144
227
670
705
604
492
147
70
0
3076
-443
Appendix A.
Color chart for final plant densities
Plant Density per acre
27404
28631
29858
31085
33312
33539
35175
36402
38038
Hybrids, relative maturities and ear type
Hybrid
DKC63-42
DKC64-24
DKC64-79
DKC65-44
Relative maturity
113
114
114
115
Thomasboro, IL
8 B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
Rep 2
7
64-79
63-42
65-44
64-24
63-42
64-79
64-24
65-44
63-42
65-44
64-79
64-24
Rep 2
6
64-79
64-24
63-42
65-44
63-42
64-79
64-24
65-44
65-44
64-24
63-42
64-79
Rep 2
5
63-42
64-24
65-44
64-79
64-24
64-79
65-44
63-42
63-42
65-44
64-79
64-24
Rep 1
4
64-24
65-44
64-79
63-42
64-24
64-79
63-42
65-44
64-24
63-42
65-44
64-79
Rep 1
3
63-42
64-79
64-24
65-44
64-79
65-44
64-24
63-42
65-44
64-24
63-42
64-79
Rep 1
2
63-42
65-44
64-79
64-24
63-42
64-24
65-44
64-79
64-24
63-42
65-44
Range
1 B
Col
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
64-79
B
B
109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132
Farmer City, IL
9
B
Rep 2
8
63-42
65-44
64-79
64-24
63-42
64-79
64-24
65-44
64-79
65-44
63-42
64-24
Rep2
7
64-24
64-79
65-44
63-42
63-42
64-24
65-44
64-79
64-24
64-79
65-44
63-42
Rep2
6
64-79
65-44
64-24
63-42
63-42
64-79
65-44
64-24
64-24
63-42
65-44
64-79
Rep1
5
64-24
65-44
63-42
64-79
65-44
64-24
64-79
63-42
64-24
64-79
63-42
65-44
Rep1
4
64-24
64-79
63-42
65-44
64-24
64-79
65-44
63-42
64-24
63-42
64-79
65-44
Rep1
3
64-24
63-42
64-44
64-79
63-42
65-44
64-79
6424
64-79
64-24
65-44
63-42
2
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
1
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
Col
1
2
3
4
5
6
7
8
9
10 11 12 13
14
15
16
17 18 19
20
21
22
23 24
Range
B
B
B
B
B
B
B
B
B
B
B
50
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
Bloomington, IL
B
B
B
B
B
B
B
B
B
B
B
B
B
Rep 2
28
64-79
63-42
65-44
64-24
63-42
64-24
Rep 2
27
64-79
63-42
64-24
64-79
64-24
Rep 2
26
63-42
64-24
65-44
64-79
65-44
Rep 1
25
63-42
64-24
64-79
65-44
Rep 1
24
64-79
65-44
63-42
Rep 1
23
63-42
65-44
64-24
Range
22 B
Col
3
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
64-79
65-44
64-24
64-79
65-44
63-42
65-44
63-42
64-79
64-24
64-79
65-44
63-42
64-79
64-24
63-42
64-24
65-44
63-42
64-79
64-79
63-42
65-44
64-24
65-44
64-24
63-42
64-79
64-24
65-44
63-42
64-24
64-79
63-42
64-24
65-44
64-79
64-79
64-79
64-24
63-42
65-44
64-79
65-44
64-24
B
B
4
5
6
7
8
9
B
B
B
B
B
B
B
B
10 11
B
12
B
13
B
14
B
15
B
B
B
B
B
B
B
B
63-42
B
B
16
17
18
19
20
21
22 23 24 25 26
B
B
B
B
B
B
B
Oxford, IN
8 B
B
B
B
B
B
B
Rep 2
7
63-42
64-79
65-44
64-24
65-44
64-79
63-42
64-24
63-42
Rep 2
6
63-42
64-24
65-44
64-79
65-44
64-79
63-42
64-24
Rep 2
5
65-44
64-79
63-42
64-24
65-44
63-42
64-79
64-24
Rep 1
4
64-24
63-42
65-44
64-79
65-44
64-79
64-24
Rep 1
3
64-24
64-79
63-42
65-44
64-79
63-42
64-24
Rep 1
2
64-24
65-44
64-79
63-42
64-24
65-44
B
Range
Col
B
B
B
B
B
64-79
65-44
64-24
65-44
64-24
63-42
64-79
64-24
63-42
64-79
65-44
63-42
63-42
64-79
65-44
64-24
65-44
64-79
65-44
64-24
63-42
63-42
64-79
64-79
64-24
63-42
65-44
B
B
B
B
B
B
1 B
B
B
B
B
B
B
B
25
26
27 28 29 30 31
32
33
34
35 36 37 38 39 40 41 42 43 44 45 46 47 48
51
B
B
B
B
B
B
B
B
Appendix B.
Analysis of Variance for Yield
Summary of Fit
RSquare
RSquare Adj
Root Mean Square Error
Mean of Response
Observations (or Sum Wgts)
0.804316
0.611349
11.9828
215.4955
144
Analysis of Variance
Source
DF
Sum of
Squares
Model
71 42493.231
Error
72 10338.294
C. Total
143 52831.525
Effect Tests
Source
Hybrid
Populations
Location
Hybrid*Location
Hybrid*Populations
Location*Populations
Mean Square
598.496
4.1682
143.587 Prob > F
<.0001
Nparm
DF
3
8
3
9
24
24
3
8
3
9
24
24
Sum of
Squares
1858.382
2707.708
27589.953
2558.663
3630.108
4148.417
LSMeans Differences Student's t- Hybrid
α=0.050
t=1.99346
Level
DKC64-79
DKC63-42
DKC64-24
DKC65-44
Least Sq Mean
A
A
B
B
B
F Ratio
220.54583
217.21389
212.46806
211.75417
Means followed by same letter are not different.
52
F Ratio
Prob > F
4.3142
2.3572
64.0491
1.9800
1.0534
1.2038
0.0074*
0.0260*
<.0001*
0.0541
0.4162
0.2685
LSMeans Differences Student's t-Density
α=0.050
t=1.99346
Level
32275
36480
38000
33619
35020
30984
28555
29744
27412
Least Sq Mean
A
A
A
A
A
A
A
B
B
219.91875
218.42188
218.23750
217.43125
217.20625
216.65313
216.35625
208.20625
207.02813
C
C
Means followed by same letter are not different.
LSMeans Differences Student's t –Location
α=0.050
t=1.99346
Level
Oxford, IN
Farmer City, IL
Thomasboro, IL
Bloomington, IL
B
Least Sq
Mean
232.17917
218.91667
B
217.15278
A
C
193.73333
Means followed by same letter are not different.
53
Analysis of Variance for Moisture
Summary of Fit
RSquare
RSquare Adj
Root Mean Square Error
Mean of Response
Observations (or Sum
Wgts)
0.977218
0.954752
0.678796
25.94549
144
Analysis of Variance
Source
DF
Sum of
Squares
Model
71 1423.0196
Error
72
33.1750
C. Total
143 1456.1946
Effect Tests
Source
Mean Square
20.0425 43.4985
0.4608 Prob > F
<.0001
Nparm
DF
3
8
3
9
24
24
3
8
3
9
24
24
Hybrid
Populations
Location
Hybrid*Location
Hybrid*Populations
Location*Populations
F Ratio
Sum of
Squares
121.6752
14.0357
1150.8081
103.7174
14.6856
18.0977
F Ratio
Prob > F
88.0243
3.8077
832.5373
25.0110
1.3280
1.6366
<.0001*
0.0009*
<.0001*
<.0001*
0.1785
0.0569
LSMeans Differences Student's t Hybrid
α=0.050
t=1.99346
Level
DKC63-42
DKC65-44
DKC64-79
Least Sq Mean
A
27.051389
B
26.561111
C
25.469444
DKC64-24
D
Means followed by same letter are not different.
54
24.700000
LSMeans Differences Student's t Density
α=0.050
t=1.99346
Level
Least Sq Mean
30984
A
26.481250
27412
A B
26.315625
28555
A B C
26.256250
32275
B C D
25.921875
29744
B C D
25.856250
38000
C D
25.815625
35020
D
25.693750
33619
D
25.643750
36480
D
25.525000
Means followed by same letter are not different.
LSMeans Differences Student's t Location
α=0.050
t=1.99346
Level
Farmer City, IL
Oxford, IN
Thomasboro, IL
Bloomington, IL
Least Sq
Mean
28.040278
A
B
27.651389
26.998611
C
D
21.091667
Means followed by same letter are not different.
55
Analysis of Variance for Test Weight
Summary of Fit
RSquare
RSquare Adj
Root Mean Square Error
Mean of Response
Observations (or Sum
Wgts)
0.949123
0.896771
0.634574
58.14823
141
Analysis of Variance
Source
DF
Sum of
Squares
Model
71 518.33686
Error
69
27.78519
C. Total
140 546.12206
Effect Tests
Source
Mean Square
7.30052 18.1297
0.40268 Prob > F
<.0001
Nparm
DF
3
8
3
9
24
24
3
8
3
9
24
24
Hybrid
Populations
Location
Hybrid*Location
Hybrid*Populations
Location*Populations
F Ratio
Sum of
Squares
31.29684
19.17882
359.89418
9.62069
11.76045
56.08253
F Ratio
Prob > F
25.9069
5.9534
297.9129
2.6546
1.2169
5.8030
<.0001*
<.0001*
<.0001*
0.0105*
0.2593
<.0001*
LSMeans Differences Student's t Hybrid
α=0.050
t=1.99495
Level
DKC65-44
DKC64-79
DKC64-24
DKC63-42
Least Sq Mean
A
58.795833
B
58.445457
C
58.050458
D
57.523640
Means followed by same letter are not different.
56
LSMeans Differences Student's t-Density
α=0.050
t=1.99495
Level
Least Sq Mean
33619
A
36480
A
28555
58.962500
B
B
58.559375
C
58.476031
38000
C
D
58.096875
30984
C
D
58.075000
32275
C
D
58.055470
29744
C
D
58.028125
35020
D
57.878125
27412
D
57.703125
Means followed by same letter are not different.
LSMeans Differences Student's t-Location
α=0.050
t=1.99495
Level
Least Sq
Mean
60.976500
58.011111
Oxford, IN
A
Thomasboro, IL
B
Farmer City, IL
Bloomington, IL
C
57.323611
D
56.504167
Means followed by same letter are not different.
57
Analysis of Variance for Kernel Rows per Ear
Summary of Fit
RSquare
RSquare Adj
Root Mean Square Error
Mean of Response
Observations (or Sum
Wgts)
0.891907
0.780682
0.470605
16.7883
141
Analysis of Variance
Source
DF
Sum of
Squares
Model
71 126.09180
Error
69
15.28139
C. Total
140 141.37319
Effect Tests
Source
Mean Square
1.77594
8.0189
0.22147 Prob > F
<.0001
Nparm
DF
3
8
3
9
24
24
3
8
3
9
24
24
Hybrid
Populations
Location
Hybrid*Location
Hybrid*Populations
Location*Populations
F Ratio
Sum of
Squares
82.611580
2.547914
22.924827
2.950675
3.666484
8.022614
F Ratio
Prob > F
124.3386
1.4381
34.5041
1.4804
0.6898
1.5094
<.0001*
0.1966
<.0001*
0.1727
0.8445
0.0945
LSMeans Differences Student's t
α=0.050
t=1.99495
Level
Least Sq Mean
DKC65-44
A
17.508333
DKC64-24
A
17.481473
DKC63-42
DKC64-79
B
16.521172
C
15.638104
Means followed by same letter are not different.
58
LSMeans Differences Student's t
α=0.050
t=1.99495
Level
Least Sq Mean
28555
A
17.013858
27412
A
16.953125
32275
A
16.896875
36480
A B
16.790625
35020
A B
16.750000
33619
A B
16.749700
29744
A B
16.693750
30984
A B
16.675000
38000
B
16.562500
Means followed by same letter are not different.
LSMeans Differences Student's t
α=0.050
t=1.99495
Level
Least Sq Mean
Farmer City, IL
A
Bloomington, IL
A
Oxford, IN
Thomasboro, IL
17.184722
B
17.032415
B
16.800000
16.131944
C
Means followed by same letter are not different.
59
Analysis of Variance for Kernels per Row
Summary of Fit
RSquare
RSquare Adj
Root Mean Square Error
Mean of Response
Observations (or Sum
Wgts)
0.926696
0.851267
1.127224
32.13298
141
Analysis of Variance
Source
DF
Sum of
Squares
Model
71 1108.3554
Error
69
87.6738
C. Total
140 1196.0291
Effect Tests
Source
Hybrid
Populations
Location
Hybrid*Location
Hybrid*Populations
Location*Populations
Mean Square
F Ratio
15.6106 12.2857
1.2706 Prob > F
<.0001
Nparm
DF
3
8
3
9
24
24
3
8
3
9
24
24
Sum of
F Ratio Prob > F
Squares
275.56117 72.2897
<.0001*
231.43152 22.7673
<.0001*
402.68252 105.6382
<.0001*
31.04435
2.7147
0.0091*
44.05366
1.4446
0.1198
54.00482
1.7709
0.0343*
LSMeans Differences Student's t
α=0.050
t=1.99495
Level
Least Sq Mean
DKC64-79
A
33.484972
DKC63-42
A
33.426981
DKC64-24
B
31.257768
DKC65-44
C
30.237500
Means followed by same letter are not different.
60
LSMeans Differences Student's t
α=0.050
t=1.99495
Level
Least Sq Mean
28555
A
33.775562
27412
A
33.709375
29744
B
32.784375
30984
B
32.784375
32275
B
32.143750
33619
B C
31.987560
35020
C D
31.343750
36480
D
30.740625
38000
E
29.646875
Means followed by same letter are not different.
LSMeans Differences Student's t
α=0.050
t=1.99495
Level
Oxford, IN
Farmer City, IL
Thomasboro, IL
Bloomington, IL
Least Sq Mean
A
B
33.800000
32.806944
B
32.711111
C
29.089165
Means followed by same letter are not different.
61
Analysis of Variance for 100 Kernel Weight
Summary of Fit
RSquare
RSquare Adj
Root Mean Square Error
Mean of Response
Observations (or Sum
Wgts)
0.857758
0.671263
1.137436
32.94286
105
Analysis of Variance
Source
DF
Sum of
Squares
Model
59 351.07793
Error
45
58.21922
C. Total
104 409.29714
Effect Tests
Source
Hybrid
Populations
Location
Hybrid*Location
Hybrid*Populations
Location*Populations
Mean Square
F Ratio
5.95047
4.5994
1.29376 Prob > F
<.0001
Nparm
DF
3
8
2
6
24
16
3
8
2
6
24
16
Sum of
Squares
46.62016
155.51070
39.09719
17.62106
35.94977
57.91224
LSMeans Differences Student's t
α=0.050
t=2.0141
Level
Least Sq Mean
DKC64-24
A
33.554263
DKC65-44
A
33.333333
DKC64-79
A
32.965125
DKC63-42
B
31.799402
Means followed by same letter are not different.
62
F Ratio
Prob > F
12.0115
15.0251
15.1099
2.2700
1.1578
2.7977
<.0001*
<.0001*
<.0001*
0.0535
0.3278
0.0034*
LSMeans Differences Student's t
α=0.050
t=2.0141
Level
Least Sq Mean
28555
A
34.871531
30984
A
34.741667
27412
B
33.666667
29744
B
33.333333
32275
C
32.341667
33619
C D
32.195746
35020
C
32.183333
38000
C D
31.725000
36480
D
31.158333
Means followed by same letter are not different.
LSMeans Differences Student's t
α=0.050
t=2.0141
Level
Least Sq
Mean
33.661111
32.975000
Oxford, IN
A
Farmer City, IL
B
Bloomington, IL
C
32.102981
Means followed by same letter are not different.
63
Analysis of Variance for Stalk Lodging Percentage
Summary of Fit
RSquare
RSquare Adj
Root Mean Square Error
Mean of Response
Observations (or Sum
Wgts)
0.740404
0.484414
0.417734
0.237153
144
Analysis of Variance
Source
DF
Sum of
Squares
Model
71 35.834635
Error
72 12.564097
C. Total
143 48.398733
Effect Tests
Source
Hybrid
Populations
Location
Hybrid*Location
Hybrid*Populations
Location*Populations
Mean Square
F Ratio
0.504713
2.8923
0.174501 Prob > F
<.0001
Nparm
DF
3
8
3
9
24
24
3
8
3
9
24
24
Sum of
Squares
0.570885
5.352014
11.050469
0.467934
5.222708
13.170625
LSMeans Differences Student's t
α=0.050
t=1.99346
Level
Least Sq Mean
DKC65-44
A
0.32638889
DKC64-24
A
0.26527778
DKC64-79
A
0.18888889
DKC63-42
A
0.16805556
Means followed by same letter are not different.
64
F Ratio
Prob > F
1.0905
3.8338
21.1087
0.2979
1.2471
3.1448
0.3587
0.0008*
<.0001*
0.9731
0.2339
<.0001*
LSMeans Differences Student's t
α=0.050
t=1.99346
Level
Least Sq
Mean
36480 A
0.53125000
38000 A
0.51875000
35020 A B
0.32812500
32275 A B
0.31562500
33619 A B C 0.26562500
28555
B C 0.08750000
27412
B C 0.04687500
30984
B C 0.04062500
29744
C 0.00000000
Means followed by same letter are not different.
LSMeans Differences Student's t
α=0.050
t=1.99346
Level
B
Least Sq
Mean
0.71388889
0.11805556
Bloomington, IL
B
0.08611111
Thomasboro, IL
B
0.03055556
Oxford, IN
Farmer City, IL
A
Means followed by same letter are not different.
65
Analysis of Variance for Root Lodging Percentage
Summary of Fit
RSquare
RSquare Adj
Root Mean Square Error
Mean of Response
Observations (or Sum
Wgts)
0.824945
0.652322
1.899299
1.270486
144
Analysis of Variance
Source
DF
Sum of
Squares
Model
71 1223.9687
Error
72
259.7284
C. Total
143 1483.6971
Effect Tests
Source
Hybrid
Populations
Location
Hybrid*Location
Hybrid*Populations
Location*Populations
Mean Square
17.2390
4.7789
3.6073 Prob > F
<.0001
Nparm
DF
3
8
3
9
24
24
3
8
3
9
24
24
Sum of
Squares
84.62991
98.08503
524.42866
241.05960
70.91899
204.84649
LSMeans Differences Student's t
α=0.050
t=1.99346
Level
F Ratio
Least Sq Mean
DKC64-79
A
2.0722222
DKC63-42
A
1.9333333
DKC64-24
B
0.8513889
DKC65-44
B
0.2250000
Means followed by same letter are not different.
66
F Ratio
Prob > F
7.8202
3.3988
48.4594
7.4250
0.8192
2.3661
0.0001*
0.0023*
<.0001*
<.0001*
0.7016
0.0027*
LSMeans Differences Student's t
α=0.050
t=1.99346
Level
Least Sq Mean
38000
A
2.7562500
36480
A B
2.4437500
35020
A B C
1.7500000
33619
B C D
1.1093750
30984
B C D
1.1093750
32275
C D
0.9531250
27412
C D
0.6562500
28555
D
0.4000000
29744
D
0.2562500
Means followed by same letter are not different.
LSMeans Differences Student's t
α=0.050
t=1.99346
Level
Oxford, IN
Thomasboro, IL
A
B
Least Sq
Mean
4.5708333
0.2763889
Bloomington, IL
B
0.2347222
Farmer City, IL
B
2.2204e-16
Means followed by same letter are not different.
67
Analysis of Variance for Plant Height
Summary of Fit
RSquare
RSquare Adj
Root Mean Square Error
Mean of Response
Observations (or Sum
Wgts)
0.919056
0.819562
1.608925
94.54167
108
Analysis of Variance
Source
DF
Sum of
Squares
Model
59 1410.8079
Error
48
124.2546
C. Total
107 1535.0625
Effect Tests
Source
Mean Square
23.9120
9.2373
2.5886 Prob > F
<.0001
Nparm
DF
Hybrid
Population
Loc
Hybrid*Loc
Hybrid*Population
3
8
2
6
24
Loc*Population
16
F Ratio
Prob > F
3
8
2
6
24
Sum of
Squares
481.74769
35.33333
720.12500
19.74537
96.31481
62.0336
1.7062
139.0934
1.2713
1.5503
<.0001*
0.1213
<.0001*
0.2883
0.0974
16
57.54167
1.3893
0.1874
LSMeans Differences Student's t
α=0.050
t=2.01063
Level
DKC64-79
DKC63-42
Least Sq Mean
A
97.314815
B
F Ratio
95.851852
DKC65-44
C
92.722222
DKC64-24
C
92.277778
Means followed by same letter are not different.
68
LSMeans Differences Student's t
α=0.050
t=2.01063
Level
Least Sq Mean
35020
A
95.041667
32275
A
94.958333
28555
A
94.916667
38000
A
94.875000
33619
A
94.833333
27412
A
94.500000
36480
A
94.500000
30984
A B
94.125000
29744
B
93.125000
Means followed by same letter are not different.
LSMeans Differences Student's t
α=0.050
t=2.01063
Level
Thomasboro, IL A
Farmer City, IL
Bloomington, IL
Least Sq Mean
98.083333
93.541667
92.000000
B
C
Means followed by same letter are not different.
69