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PRODUCTION PAPER

Within-Row Plant Spacing Variability Does Not Affect Corn Yield

^a Dep. of Plant Agric., Univ. of Guelph, Guelph, ON, Canada N1G 2W1
^b Ontario Ministry of Agric. and Food, Crop Science Bldg., Univ. of Guelph, Guelph, ON, Canada N1G 3E1

^* Corresponding author (bdeen{at}uoguelph.ca).

Received for publication March 3, 2003.

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION SUMMARY AND CONCLUSIONS REFERENCES

 
Nonuniform plant spacing within the row in corn (Zea mays L.) may reduce grain yield. To investigate the response of corn to plant spacing variability, experiments were conducted at two locations in south-central Ontario during 2000 and 2001. Six plant spacing treatments, 6.7 to 16.2 cm in standard deviations (SD), were established by planting Roundup Ready corn with increasing proportions of conventional corn seeds and then removing the conventional corn using glyphosate before three-leaf stage. Using SD as well as short gap, long gap, double, and cluster as an index of plant spacing variability, effects of plant spacing variability on corn growth and grain yield were investigated. Averaged across locations and years, grain yield was not significantly affected by plant spacing variability. Plant spacing variability also had no significant effect on leaf number, plant height, leaf area index, and harvest index. There were no correlations between plant spacing variability and stalk lodging and barren or double ears. The lack of strong correlations among plant growth, grain yield, and plant spacing variability indicates that spacing uniformity within the range used in this study is not a significant factor in determining grain yield under commercial conditions and common plant densities used in Ontario.

Abbreviations: LAI, leaf area index • LAR, leaf area ratio • RCI, relative competitive intensity • RR, Roundup Ready • SD, standard deviation

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION SUMMARY AND CONCLUSIONS REFERENCES

 
IN CORN PRODUCTION, uniformity of plant distribution within the row, along with plant density and row spacing, has been a subject that has received much attention. Agronomists and corn producers have assumed that evenly spaced stands of corn have greater yield potential than unevenly spaced stands. Duncan (1984) proposed a theoretical basis for plant competition effects on corn grain yield. The yield of a single corn plant is reduced by the presence of competing neighbors, and the amount of yield reduction for a given environment depends on how near and how numerous the neighboring plants are. He also suggested that equidistant spacing must result in the highest yield for any competing plant population. Improved uniformity of within-row plant spacing is expected to decrease plant-to-plant competition and increase grain yield through more efficient use of available light, water, and nutrients by the plants (Shubeck and Young, 1970).

Reported research results, however, are mixed regarding corn response to variation of within-row plant spacing. Early studies indicated that improved plant spacing uniformity has no significant effect on grain yield (Erbach et al., 1972; Muldoon and Daynard, 1981). In contrast, other research has demonstrated that nonuniform plant spacing may reduce grain yield. In Kansas, Krall et al. (1977) reported a significant decrease of 84 kg ha^–1 in grain yield for each centimeter increase in SD of plant spacing. Vanderlip et al. (1988) found that grain yields decrease when SD values exceeded 6 cm. Nielsen (2001) stated that corn grain yields decrease an average of 62 kg ha^–1 for each centimeter increase in SD of plant spacing when SD is greater than 5 cm. He also reported that the rate of yield loss with increasing SD is not constant but varies among locations in Indiana from 30 to 110 kg ha^–1. A more recent on-farm study undertaken by Doerge and Hall (2001) indicated an average increase in grain yield of 84 kg ha^–1 for every centimeter improvement in SD of within-row plant spacing.

Inconsistent yield benefits from improved within-row plant spacing uniformity in previous studies may be associated with plant density and the measurements of plant spacing variability. For example, SDs were averaged over a population range of 47400 to 64600 plants ha^–1 in the report by Krall et al. (1977). In this case, plant population effects and within-row spacing variability effects could not be distinguished. Nafziger (1996) indicated that SD alone is not a perfect indicator of stand uniformity because, while both gaps and doubles contribute to plant spacing variability, their effects on yield are in opposite directions. Johnson and Mulvaney (1980) also found higher yield losses when within-row plant spacing variability occurred as large gaps rather than smaller gaps, and yield losses were somewhat greater under low than under high plant populations.

The primary objective of this research was to quantify the response of corn yield to within-row plant spacing variability for corn grown under a plant density that is commonly used in Ontario conditions. A secondary objective was to determine the relationships between within-row plant spacing SD and the nature of spacing components (i.e., gaps, doubles, and clusters). The hypothesis being tested was that plant spacing uniformity is required to achieve maximum corn yield potential.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION SUMMARY AND CONCLUSIONS REFERENCES

 
Field experiments were conducted in 2000 and 2001 at the Elora Research Station (43°39' N, 80°25' W; elevation 376 m) and the Woodstock Research Station (43°08' N, 79°06' W; elevation 317 m) in south-central Ontario, Canada. The growing season is rated as receiving 2650 crop heat units (Brown and Bootsma, 1993) at Elora and 2850 crop heat units at Woodstock. At Elora, the loam soil is an imperfectly drained medium, mixed, weakly to moderately calcareous Typic Hapludalf with tile drainage and an organic matter content of 3.8 to 4.0%. The loam soil at Woodstock is a well-drained medium, mixed, alkaline, moderately to very strongly calcareous Typic Hapludalf with 2 to 3% organic matter.

The experimental area was plowed in previous fall and cultivated before sowing. In both years, corn was grown in rotation after alfalfa (Medicago sativa L.) at Elora and soybean [Glycine max (L.) Merr.] at Woodstock. Corn was planted on 5 May 2000 and 9 May 2001 at Elora and on 15 May 2000 and 2 May 2001 at Woodstock using a four-row vacuum planter (John Deere 1750, John Deere, Moline, IL).

The experiments at each location were established as a randomized complete block design with four replications. The experimental unit was a four-row plot with a row spacing of 0.76 m and length of 20 m. Treatments were within-row plant spacing variability, which was generated by planting mixed seed lots consisting of Roundup Ready (RR) corn and conventional corn. The RR corn hybrids planted were ‘DK335’ and ‘DK C42-21RR’ at Elora and Woodstock, respectively. The conventional corn hybrid used at both sites was ‘DK325’. This hybrid has similar seed size and kernel weight as the two RR hybrids. To achieve six treatments consisting of the same plant population but varying deviations of within-row plant spacing, hybrid seed of RR corn was mixed with increasing rates of conventional corn. The six treatments were established by planting 69.8 x 10³ seeds ha^–1 RR corn plus 0, 10, 20, 35, 50, and 70% of 69.8 x 10³ seeds ha^–1 conventional corn. Before the three-leaf tip stage at leaf tip appearance (Tollenaar et al., 1979), conventional corn was removed by spraying glyphosate [N-(phosphonomethy)glycine] to all treatments at a rate of 2.5 L ha^–1. Within-row plant-to-plant spacing was measured by recording the distances between 61 consecutive plants in each of the two middle rows 2 wk after silking. This measurement was taken both by hand and using a Space Cadet stand analyzer (Version 1.9, Space Cadet, Bagley, IA). Standard deviations of spacing for the six resulting treatments were 6.7, 9.5, 10.7, 12.2, 14.8, and 16.2 cm [LSD(0.05) = 1.2]. A perfect stand with a SD value of 0 was not achieved since variability of plant spacing is always produced because of planter performance limitations and because a small percentage of seed does not germinate. A SD value of 6.7 cm is a reasonable maximum precision with mechanical planting. Nielsen (1995) suggested that a SD of 5 cm is about the best a producer can actually obtain in field corn production. Actual population densities of the six treatments ranged from 6.9 to 7.1 plants m^–2. Averaged over locations and years, plant densities did not differ significantly among treatments. This plant density is in the range of optimum plant density for grain yield that is recommended by the Ontario Corn Producers' Association (Stewart, 2000) and Pioneer Hi-Bred International (Wiersma and Paszkiewicz, 1999).

Nafziger (1996) suggested that SD alone is not a good means of predicting yield responses to stand variability because of the differing and interactive effects of row skips and doubles. This indicated that the nature of the deviation was important, so we characterized within-row plant spacing variability by determining plant spacing SD, short gaps, long gaps, doubles, and clusters. Short gaps and long gaps were defined as any spacing with one plant missing and two or more plants missing, or 36 to 55 cm and 55 cm or greater distance between two adjacent plants, respectively. Double plants were defined as any plants within 6 cm of each other. Clusters were defined as three or more consecutive plants with spacing of 6 cm or less of each other.

Starter fertilizer was applied through the planter at a rate of 20 kg N ha^–1, 80 kg P₂O₅ ha^–1, and 40 kg K₂O ha^–1. Additional N was injected between rows at 4 to 5 wk after planting, as urea ammonium nitrate at a rate of 150 kg N ha^–1. Glyphosate was sprayed about 5 to 6 wk after planting at a rate of 3.5 L ha^–1 for weed control.

Five weeks after emergence, plant height and leaf number were measured for 10 consecutive plants in each plot. These measurements were repeated with the same plants at 2 wk postsilking. Plant height was measured from ground to the tip of the top leaf (5 wk after emergence) and to the tip of the tassel (2 wk after silking). Plant samples were taken at 5 wk after emergence and 2 wk after silking. At each sampling date, the aboveground biomass of 10 consecutive plants was harvested from a premarked sampling area. The sampling area was bordered by two rows on each side and a 2-m border area within the row at each end. Green leaf area of all harvested plants was measured with a LI-3000 leaf area meter (LI-COR, Lincoln, NE). The leaves and stems of sample plants were dried at 80°C for 72 h before measurement of plant dry matter. At maturity, ears were hand-harvested from each of two 6-m-long central rows in each plot. Grain yields were adjusted to moisture content of 155 g kg^–1. The numbers of plants that had lodged, were barren, or had double ears were recorded. A 10-plant sample was harvested and separated into ears and stover. Ears were shelled after oven drying for 72 h at 80°C. Harvest index was determined by calculating the ratio of grain dry weight and total aboveground dry matter.

The growth parameters leaf area index (LAI) and leaf area ratio (LAR) were calculated using formula LAI = LA/GA and LAR = LA/W_T, respectively, where LA is one-side leaf area, GA is ground area of sample site, and W_T is total aboveground dry matter on the sampling. Net assimilation rate (NAR) was computed using two successive sampling dates (Hunt, 1990). The formula used for computing NAR was

where T corresponds with sample date 1 (5 wk after emergence) or 2 (2 wk after silking).

An important measure of plant competition intensity was defined as the combined (negative) effects of all neighbors on the performance of an individual or population. A relative index rather than absolute differences should be used as a measure of competition intensity (Grace, 1990). The control treatment (RR) was assumed to be evenly spaced, with each plant causing an equal competition effect. An index that reflected the proportional impact of competition on plant performance for other treatments with higher plant spacing variability would be relative competitive intensity (RCI). It can be defined as:

where P_C is the performance (yield, plant height, etc.) of the control treatment and P_T is the performance of the treatments.

Analyses of variance were performed using SAS version 6.12 (SAS Inst., Cary NC). Residual homogeneity was evaluated by creating residual plots using PROC PLOT procedure. The Shapiro–Wilk (W) statistic with the PROC UNIVARIATE procedure was also used to test if the residuals were normally distributed. Studentized residuals were computed based on the SD of the residual variable in the normality test. The studentized residuals were used to detect outliers in the data. Data were combined over years and locations by using the PROC MIXED procedure. The effect of spacing deviation on measured parameters was identified using linear regression. Unless indicated, effects were considered significant in all statistical calculations if P 0.05.

	RESULTS AND DISCUSSION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION SUMMARY AND CONCLUSIONS REFERENCES

 
Response of Grain Yield to Within-Row Plant Spacing Variability
The air temperature at both sites and years was within 2°C of the normal (30-yr average), but the two growing seasons differed dramatically in their precipitation pattern at both locations (Fig. 1). The trial in 2000 received a favorable moisture supply at early crop development whereas experiments in 2001 may have been affected by water shortage until well after mid–grain filling. The 2001 growing season received 30 and 54% less rain than the 2000 season at Elora and Woodstock, respectively. Compared with the long-term average, 26% more rain in 2000 and 12% less rain in 2001 was received at Elora; and 55% more in 2000 and 29% less in 2001 was received at Woodstock. Grain yields of corn, averaged over all treatments, were 7.57 and 8.80 Mg ha^–1 in 2000 and 6.36 and 8.61 Mg ha^–1 in 2001 at Elora and Woodstock, respectively. Grain yield was lower at Elora than at Woodstock. In spite of the differences in environment and yield, there were no significant interactions between plant spacing variability (treatment) and locations and between plant spacing variability (treatment) and years; therefore, data were averaged across locations and years.

View larger version (45K): [in this window] [in a new window]   Fig. 1. Weekly rainfall and mean air temperature from May to September at Elora and Woodstock, ON, in 2000 and 2001. Dates represent the middle of the week.

View larger version (28K): [in this window] [in a new window]   Fig. 2. Corn grain yield and relative competitive intensity (RCI) response to standard deviation (SD) of within-row plant spacing at Elora and Woodstock, ON, in 2000 and 2001.

Similar to the SD of plant spacing, significant differences of doubles, clusters, short gaps, and long gaps were also observed among treatments (Fig. 3). As expected, the short gaps, long gaps, and doubles basically followed the SD response pattern, which increased as more conventional corn seeds were added at planting. Clusters changed differently from other parameters of plant spacing variability and had a low occurrence of 0 to 1.4% per 100 plant spaces.

View larger version (72K): [in this window] [in a new window]   Fig. 3. Numbers of short gap, long gap, double, and cluster in 100 measured plant spacings at Elora and Woodstock, ON, in 2000 and 2001. Data were averaged across two locations and years. LSD (0.05) = 2.06 (short gaps), 1.26 (long gaps), 2.91 (doubles), and 0.56 (clusters).

This equation explained 77% of the variance (R² = 0.77). In other words, all of the above parameters made significant contributions, and the order in which they contributed to variation in SD, based on the coefficient values in the above equation, were long gap > cluster > short gap > double. This result indicates that gaps influence calculated SD more than doubles.

Both crowded plants (doubles and clusters) and gaps (short and long gaps) increase the SD and contribute to plant spacing variability. Nafziger (1996) reported that the effects of gaps and doubles on grain yield occur in opposite directions. Hence, yield decreases due to gaps can be minimized by doubles. A higher gap frequency was generally associated with a higher frequency of crowded plants. The greatest gap frequency was 14% and the greatest double frequency 16% in the least-uniform plant spacing treatment with the SD of 16.2 cm.

Growth Analysis of Corn under Varied Within-Row Plant Spacing
Rate of development is affected by plant competition (Vyn, 1978, p. 63) and, therefore, may be indirectly influenced by plant spacing variability. Plant leaf number before emergence of the topmost leaf is an indication of stage of development. Mean leaf number per plant did not differ significantly among treatments at either location or sampling date (Table 1). Compared across locations and years, there was no trend toward increasing or decreasing leaf number from low plant spacing variability to high plant spacing variability. The lack of impact of spacing variability on leaf number indicates that variation of plant spacing does not cause severe plant competition on plant development in terms of phenological development within a corn canopy.

Both LAI and LAR are good indicators of competition severity as they are directly associated with the photosynthetic tissue of the plant (Hunt, 1990). Averaged over the locations and years, neither LAI nor LAR was affected by plant spacing variability (Table 1).

Competition among plants of the same species can result in weight per plant reduction (Brown, 1984), particularly if population increases under increasing competition. In this study, population was held constant as plant spacing variability, double plants, and clusters increased. Under constant population, aboveground biomass measured at 5 wk after emergence, 2 wk postsilking, and at maturity was not affected by increasing spacing deviation (Table 1).

Neither net assimilation rate nor harvest index was affected by plant spacing variability (Table 1) when combined over locations and years (Table 1).

Other Responses of Corn to Within-Row Plant Spacing Variability
At harvest, there were no significant differences in the incidence of lodging and barrenness among all treatments (data not shown). Averaged over locations and years, the lodging rate ranged from 8.4 to 11.8%, with an average of 10.6%. Compared with 2000, a significantly greater proportion of plants with barren ears was observed in 2001 at both locations. The proportion of plants with barren ears was 0.4 and 0.5% in 2000 and 4.8 and 7.6% in 2001 at Elora and Woodstock, respectively. Double ears were only observed in 2001 at Woodstock at a mean proportion of 4.0% and were not significantly different among treatments. Grain moisture at harvest was stable across treatments at both locations and years. Mean grain moisture content was 219 g kg ^–1 and ranged from 217 to 221 g kg ^–1.

Unevenly spaced corn plants represent a combination of high and low plant density within a row. Paszkiewicz and Butzen (2001) reported that stalk lodging increases with higher plant population. Our results indicate that population variations occurring at a scale of several centimeters within a row may not have the same effect on stalk diameter, lodging, and barrenness as population differences occurring at a larger scale.

	SUMMARY AND CONCLUSIONS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION SUMMARY AND CONCLUSIONS REFERENCES

 
The mixed-seed (RR/conventional) planting system as a means to create within-row plant spacing variability was successfully and effectively applied in this study. Within-row plant spacing variability, as measured by SD, was caused by the occurrence of doubles, clusters, short gaps, and long gaps. Gaps, especially long gaps, in the row appeared to contribute most to the actual SD measurement.

Crop growth analysis has been used as a tool by many researchers for quantifying the effect of competition stress under increasing plant density in corn (Tollenaar, 1992; Cox, 1996; Tetio-Kagho and Gardner, 1998). However, this type of analysis has not been used to study corn response to plant spacing variability. Corn plant height, leaf number, LAI, LAR, dry matter accumulation, net assimilation rate, as well as harvest index were not significantly affected by SD of plant spacing.

Averaged over two locations and years, no significant relationship was found between grain yield and within-row plant spacing variability as measured by SD, gaps, doubles, and clusters. The lack of a strong association between plant growth, grain yield, and plant spacing variability suggests that perfect plant spacing uniformity is not a significant contributor to yield loss for corn grown under the conditions in this study. The results support the contention that no significant benefit is obtained with more uniform plant spacing than typically found in commercial corn fields (Erbach et al., 1972; Muldoon and Daynard, 1981).

	REFERENCES

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION SUMMARY AND CONCLUSIONS REFERENCES

 

• Brown, D.M., and A. Bootsma. 1993. Crop heat units for corn and other warm-season crops in Ontario. OMAF Factsheet, Agdex 111/31. Ontario Ministry of Agric. and Food, Toronto.
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• Grace, J.B. 1990. On the relationship between plant traits and competitive ability. p. 51–65. In J.B. Grace and D. Tilman (ed.) Perspectives on plant competition. Academic Press, New York.
• Hunt, R. 1990. Basic growth analysis. Unwin-Hyman, London.
• Johnson, R.R., and D.L. Mulvaney. 1980. Development of a model for use in maize replant decisions. Agron. J. 72:459–464.[Abstract/Free Full Text]
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• Tetio-Kagho, F., and F.P. Gardner. 1998. Response of maize to plant population density: I. Canopy development, light relationships, and vegetative growth. Agron. J. 80:930–935.
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This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (7) Citing Articles via Google Scholar Google Scholar Articles by Liu, W. Articles by Deen, W. Search for Related Content PubMed Articles by Liu, W. Articles by Deen, W. Agricola Articles by Liu, W. Articles by Deen, W. Related Collections Crop Growth and Development Maize Maize Management