I. Introduction
III. Results
1) Higher plant populations will result in greater plant-to-plant grain yield variability due to
greater intraspecific competition for limited resources.
2) Higher N rates will reduce plant-to-plant grain yield variability by enhancing stand uniformity.
3) Application of N will reduce intraspecific competition more at high plant populations than at
low plant populations.
Overall Study Objective:
•
Per Plant Grain Yield Mean (g)
Per Plant Grain Yield Mean (g)
LSD ==9.0
(A) LSD
9.0g g
200
175
150
125
100
150
125
100
Key Results:
75
330
165
0
Nitrogen Rate (kg ha-1)
40
35
30
25
20
15
Per plant grain yield decreases with
increasing plant population (A).
Per plant grain yield increases with
increasing N rate (B).
Plant-to-plant grain yield variability
increases with increasing plant
population (C).
Plant-to-plant grain yield variability
decreases with increasing N rate (D).
Increasing the N rate from 165 kg N
ha-1 to 330 kg N ha-1 does not
significantly increase per plant grain
yield or decrease plant-to-plant grain
yield variability.
(D) LSD = 4.5%
•
40
35
•
30
25
•
20
15
54,000 79,000 104,000
Plant Population (plants ha-1)
•
•
45
(C) LSD = 3.5%
yield mean (A,B) and CV (C,D) for
each plant population and N rate
averaged across all other effects.
Error bars equal one-half of the least
significant difference (LSD) at
P = 0.05. Means are significantly
different where error bars do not
overlap.
175
54,000 79,000 104,000
Plant Population (plants ha-1)
To understand the effects of hybrid, plant population, and N rate on the morphology and
physiology of intraspecific competition through the examination of the hierarchical
distribution (i.e., “dominating” vs. “dominated” plants) and growth and developmental
variability of individual corn plants.
(B) LSD = 6.5 g
200
75
45
Figure 4 (A-D):
330
165
0
Nitrogen Rate (kg ha-1)
100
II. Materials and Methods
Cumulative Percentage of Grain Yield
Experimental Setup:
54,000 plants ha
104,000 plants ha-1
1:1 Line of Equality
60
60
40
40
•
•
•
•
•
At 54,000 plants ha-1, 9.2% of the plants at 0 kg N ha-1
(A) and 6.1% of the plants at 330 kg N ha-1 (B) have a
grain yield that is ≤ 66% of the per plant grain yield
mean.
At 104,000 plants ha-1, 23.4% of the plants at 0 kg N
ha-1 (C) and 12.6% of the plants at 330 kg N ha-1 (D)
have a grain yield that is ≤ 66% of the per plant grain
yield mean.
At both N rates, higher plant populations result in
increased barrenness (A-D).
The most positive skewness (and, therefore, greatest
hierarchically-dominated grain yield pattern) exists
at 104,000 plants ha-1 with 0 kg N ha-1 (C).
The most negative skewness (and, therefore, least
hierarchically-dominated grain yield pattern) exists
at 54,000 plants ha-1 with 330 kg N ha-1 (B).
0 kg N ha
330 kg N ha-1
1:1 Line of Equality
(A)
(B)
• Hybrid (whole unit):
0
100
20
40
60
80
54,000 plants ha-1;
0 kg N ha-1
54,000 plants ha-1;
330 kg N ha-1
1:1 Line of
Equality
80
60
0
100
100
80
60
20
40
60
80
100
104,000 plants ha-1;
0 kg N ha-1
104,000 plants ha-1;
330 kg N ha-1
1:1 Line of
Equality
•
•
40
•
20
(D)
•
0
0
0
20
40
60
80
100
0
20
40
60
80
Cumulative Percentage of Population
100
At 54,000 plants ha-1, 31% of the population accounts
for 20% of the overall grain yield; however, at
104,000 plants ha-1, 38% of the population accounts
for 20% of the overall grain yield (A).
At 0 kg N ha-1, 38% of the population accounts for
20% of the overall grain yield; however, at 330 kg N
ha-1, 33% of the population accounts for 20% of the
overall grain yield (B).
Plant-to-plant grain yield variability is similar for 0 kg
N ha-1 and 330 kg N ha-1 at 54,000 plants ha-1 (C).
Greater N application reduces plant-to-plant grain
yield variability more at 104,000 plants ha-1 (D) than
at 54,000 plants ha-1 (C).
•
Higher plant populations and lower N rates result in decreased per plant grain yields (Figures 4A and
4B) and increased plant-to-plant grain yield variability (Figures 4C, 4D, 5A, and 5B) as a result of
greater intraspecific competition for limited resources.
Per Plant Measurements
(Partial List) (≈ 4,000 plants):
•
Corn canopies at higher plant populations are composed of a large number of low-yielding individuals
(Figure 5A), particularly when N is not applied (Figure 5D).
• Emergence Date (GDD Post-planting)
• Plant Spacing (cm)
• Plant Height (cm) [V5, V13, R6]
• 6th Internode Stalk Diameter (mm)
[V15, R3, R6]
• Leaf Chlorophyll Content/SPAD
[V13, R1, R3, R5]
• Ear Leaf Position (V-Stage Location)
• Total Leaf Number
• Silk Emergence Date (GDD Post-planting)
• Total Kernel Number
• Total Grain Weight (g)
• Grain Moisture Content (%)
•
Intense intraspecific competition, as indicated by an L-shaped frequency distribution (i.e., a few
“dominating” and many “dominated” plants), is evident at 104,000 plants ha-1 for 0 kg N ha-1 (Figure
6C).
•
At 104,000 plants ha-1 for 0 kg N ha-1, per plant grain yields show trends typical of markedly hierarchical
populations, including large plant-to-plant variability (Figure 5D) and positive skewness (Figure 6C)
(Vega and Sadras, 2003).
•
The formation of plant hierarchies for per plant grain yield at 104,000 plants ha-1 for 0 kg N ha-1 (Figure
6C) likely results from asymmetric intraspecific competition, in which large individuals (i.e., greater V15
stalk diameter and R6 plant height) acquire a disproportionate share of resources relative to small
individuals (Weiner and Thomas, 1986).
• Analysis of Variance (ANOVA) and the
Least Significant Difference (LSD) mean
separation test were conducted using
SAS® PROC GLM.
• Regression analysis was performed using
SAS® PROC REG.
25
20
20
15
15
10
10
5
5
0
0
0
35
50
100
150
200
250
300
0
35
(C) 104,000 plants ha-1; 0 kg N ha-1
Skewness = 0.06; Mean = 79 g
30
25
20
20
15
15
10
10
5
5
0
0
50
100
150
200
250
300
50
100
150
200
250
300
(D) 104,000 plants ha-1; 330 kg N ha-1
Skewness = -0.74; Mean = 132 g
30
25
0
Skewness = -2.13; Mean = 217 g
30
25
Figure 7 displays the regression of
Per Plant Grain Yield [Y] on V15
Stalk Diameter [D] and R6 Plant
Height [H] at 104,000 plants ha-1 for 0
kg N ha-1 (A) and 330 kg N ha-1 (B).
Regression Models:
(A) Y = -137.28 + (8.83*D) + (0.11*H);
R2 = 0.77**
(B) Y = -103.90 + (9.14*D) + (0.09*H);
R2 = 0.77**
Important Note:
Of all per plant measurements at
104,000 plants ha-1 for 0 kg N ha-1
and 330 kg N ha-1, stalk diameter at
V15 and plant height at R6
accounted for the largest proportion
of variation in per plant grain yield.
0
50
100
150
200
250
300
•
•
The highly significant regression of per plant grain yield on stalk diameter at V15 and plant height at R6
(Figure 7) suggests that an individual plant’s size strongly determines its final grain yield.
The lower yields of “dominated” plants likely result from (a) reduced assimilate allocation to
reproductive structures and lower late-season N uptake due to a smaller stalk diameter (Figure 7)
(Maddonni and Otegui, 2006b) along with (b) lower light interception due to a reduced plant height.
0 kg N ha-1
(B)
330 kg N ha-1
(A)
Key Results:
•
•
Per plant grain yield increases with
increasing V15 stalk diameter and
R6 plant height.
V15 stalk diameter has a greater
effect on per plant grain yield than
R6 plant height.
IV. Conclusions
Statistical Analyses:
Skewness = -0.71; Mean = 159 g
(B) 54,000 plants ha-1; 330 kg N ha-1
Figure 7:
Key Results:
0
0
(C)
Figure 3: Determination of individual plant total
kernel number, total grain weight, and grain
moisture content using Symbol® personal data
assistants and the MaizeMeister Phenotypic Data
Collection and Seed Management System.
35
(A) 54,000 plants ha-1; 0 kg N ha-1
30
Key Results:
Figure 5 displays Lorenz Curves (Damgaard and
Weiner, 2000) of per plant grain yield for:
• (A) 54,000 plants ha-1 and 104,000 plants ha-1,
• (B) 0 kg N ha-1 and 330 kg N ha-1,
• and 0 kg N ha-1 and 330 kg N ha-1 at 54,000 plants
ha-1 (C) and 104,000 plants ha-1 (D).
For the creation of the curves, individuals are ranked
by grain yield. The 1:1 Line of Equality indicates the
theoretical situation in which all plants have the
same grain yield. Lorenz curves below this line
indicate grain yield variability.
20
20
20
Figure 2: Measurement of V5 plant height (using the
extended-leaf method) (left) and R3 stalk diameter at
the 6th internode (right) on individual plants.
35
Figure 5 (A-D):
-1
80
40
Treatments:
• Pioneer 31G68
• Pioneer 33N09
• Plant Population (sub unit):
• 54,000 plants ha-1
• 79,000 plants ha-1
• 104,000 plants ha-1
• N (UAN) Rate (sub-sub unit):
• 0 kg N ha-1
• 165 kg N ha-1 (V3)
• 330 kg N ha-1 (V3, V5)
100
-1
80
Figure 1: Use of bar-coded tags and stakes
indicating emergence dates for the monitoring of
individual plant growth and development in a per
plant sampling area.
Figure 6 presents frequency distributions of per
plant grain yield for:
• (A) 0 kg N ha-1 and (B) 330 kg N ha-1 at 54,000
plants ha-1 and
• (C) 0 kg N ha-1 and (D) 330 kg N ha-1 at 104,000
plants ha-1.
Per plant grain yields ≤ 25 g indicate barren plants.
Per Plant Grain Yield (g)
Lorenz Curves for Per Plant Grain Yield at
Various Plant Populations and Nitrogen Rates
• Year: 2005
• Location: Purdue University
Agronomy Center for Research
and Education (ACRE)
• Soil-type: Chalmers silty clay loam
(4% Organic Matter)
• Layout:
• Split-split Plot Design
• Four Blocks
• 6 Rows Plot-1
• Per Plant Sampling Area:
• Rows 3 and 4
• 4 m Row-1
• Tillage: Fall Strip-tillage
• Starter Fertilizer: 9-18-9 at 150 L ha-1
Frequency Distributions for Per Plant Grain Yield at
Various Plant Populations and Nitrogen Rates
Figure 6 (A-D):
Figure 4 presents the per plant grain
225
Per Plant Grain Yield CV (%)
Poster Hypotheses:
225
Per Plant Grain Yield CV (%)
The optimum plant population for maximum grain yield in corn (Zea mays L.) has continually
increased over the past 70 years as a result of improvements in high plant population
tolerance (Tokatlidis and Koutroubas, 2004). Yet higher plant populations facilitate greater
intraspecific competition (i.e., competition in a community among members of the same
species) between individual plants resulting in increased plant-to-plant variability for grain
yield and other morpho-physiological traits (Edmeades and Daynard, 1979; Vega et al., 2000;
Vega and Sadras, 2003). Furthermore, higher intraspecific competition leads to the
appearance of individuals with varying ability to capture limited resources (i.e., “dominating”
vs. “dominated” plants) (Maddonni and Otegui, 2006a). Increased plant-to-plant variability
thus reduces per-unit-area corn grain yields due to lower resource (e.g., water, nutrients, and
light) availability per plant. The creation and maintenance of stand uniformity is therefore
essential for high productivity levels. The application of nitrogen (N) fertilizer is one method
by which individual plant resource availability can be improved at high plant populations,
thus reducing intraspecific competition and resulting plant-to-plant variability.
Per Plant Grain Yield Means and CVs for
Each Plant Population and Nitrogen Rate
Frequency (%)
Background:
V. Literature Cited
• Damgaard, C., and J. Weiner. 2000. Describing inequality in plant size or fecundity. Ecology 81:1139-1142.
• Edmeades, G.O., and T.B. Daynard. 1979. The development of plant-to-plant variability in maize at different planting densities.
Can. J. Plant Sci. 59:561-576.
• Maddonni, G.A., and M.E. Otegui. 2006a. Intra-specific competition in maize: Contribution of extreme hierarchies to grain yield,
grain yield components and kernel composition. Field Crops Res. 97:155-166.
• Maddonni, G.A., and M.E. Otegui. 2006b. Intra-specific competition in maize: early establishment of hierarchies among plants
affects final kernel set. Field Crops Res. 85:1-13.
• Tokatlidis, I.S., and S.D. Koutroubas. 2004. A review of maize hybrids’ dependence on high plant populations and its implications
for crop yield stability. Field Crops Res. 88:103-114.
• Vega, C.R.C., V.O. Sadras, F.H. Andrade, S.A. Uhart. 2000. Reproductive allometry in soybean, maize and sunflower.
Ann. Bot. 85:461-468.
• Vega, C.R.C., V.O. Sadras. 2003. Size-dependent growth and the development of inequality in maize, sunflower and soybean.
Ann. Bot. 91:795-805.
• Weiner, J., and S.C. Thomas. 1986. Size variability and competition in plant monocultures. Oikos 47:211-212.
VI. Acknowledgements
Funding:
• Pioneer Fellowship in Plant Sciences
(2006-present)
• Purdue University Andrews Fellowship
(2004-2006)
• Purdue University Research Foundation
Equipment and Materials:
• Pioneer Hi-Bred International, Inc.
• Deere & Company
• Purdue University Agronomy
Center for Research and
Education (ACRE)