1. VI. Acknowledgements I. Introduction Background: 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. Poster Hypotheses: 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: 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. Equipment and Materials: Pioneer Hi-Bred International, Inc. Deere & Company Purdue University Agronomy Center for Research and Education (ACRE) Funding: Pioneer Fellowship in Plant Sciences (2006-present) Purdue University Andrews Fellowship (2004-2006) Purdue University Research Foundation 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. IV. Conclusions 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. 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). 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). 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. III. Results Figure 4 (A-D): Figure 4 presents the per plant grain 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. Key Results: 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. Figure 5 (A-D): 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. Key Results: 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). Figure 7: 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); R 2 = 0.77** (B) Y = -103.90 + (9.14*D) + (0.09*H); R 2 = 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. 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. Figure 6 (A-D): 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. Key Results: 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). II. Materials and Methods Experimental Setup: 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 Per Plant Measurements (Partial List) (≈ 4,000 plants): Emergence Date (GDD Post-planting) Plant Spacing (cm) Plant Height (cm) [V5, V13, R6] 6 th 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 (%) Treatments: Hybrid (whole unit): 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) Statistical Analyses: 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. 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 2: Measurement of V5 plant height (using the extended-leaf method) (left) and R3 stalk diameter at the 6 th internode (right) on individual plants. 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. (A) (B) 0 kg N ha -1 330 kg N ha -1 (C) (D) (B)(A)