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Why Do Maize Hybrids Respond Differently to Variations in Plant Density?

^a Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) and Unidad Integrada Balcarce, Instituto Nacional de Tecnología Agropecuaria (INTA)–Facultad de Ciencias Agrarias, Universidad Nacional de Mar del Plata (UNMdP), Ruta Nacional 226 km 73.5, C.C. 276, 7620 Balcarce, Buenos Aires, Argentina
^b AACREA. Bolivar 710, Tandil (7000), Buenos Aires, Argentina
^c Dep. of Crop, Soil and Environmental Sciences, Univ. of Arkansas, 1366 Altheimer Dr., Fayetteville, AR 72704, USA

^* Corresponding author (tsarlangue{at}gmail.com)

Received for publication July 7, 2006.

	ABSTRACT

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Maize (Zea mays L.) grain yield responds greatly to plant density (D). However, the hybrid–plant density interaction usually found is not well understood. The objective of this work was to analyze responses of different maize hybrids to D considering their biomass plasticity and reproductive partitioning. Responses to D were analyzed during 2 yr in three hybrids with contrasting maturity and plasticity. The relationships between aboveground biomass per plant at maturity (Bp) and D and between grain yield per plant (Yp) and Bp were used to explain hybrid responses to D. Optimum D ranged from 10.3 to 13.7 plants m^–2. The hybrid with the lowest optimum D presented the greatest biomass plasticity and reproductive partitioning. Increasing D produced an increase in biomass production per unit area in all hybrids. Contrarily, a greater harvest index (HI) with increasing D was only observed in the hybrids with the least plasticity. Increments in grain yield with increasing D were, in all cases, more associated with increases in biomass production than with increments in HI. Parameters of the equations Bp – D and Yp – Bp were related to optimum D. To validate these relationships, an independent data set was used. Some of these parameters were associated with biomass plasticity and reproductive partitioning and could be used to explain and estimate the responses to D.

Abbreviations: Bp, aboveground biomass per plant at maturity • D, plant population density • Yp, grain yield per plant

	INTRODUCTION

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PLANT POPULATION DENSITY has important effects on vegetative (Tetio-Kagho and Gardner, 1988a) and reproductive development of maize (Williams et al., 1965; Tetio-Kagho and Gardner, 1988b). Maize yield is low with low plant density because of little plasticity in leaf area per plant (Williams et al., 1968; Tetio-Kagho and Gardner, 1988b; Cox, 1996). Additionally, maize plants have small capacity to develop new reproductive structures in response to an increase in available resources per plant (Edmeades and Daynard, 1979; Loomis and Connor, 1996). On the other hand, if plant density is too high, the decrease in the availability of resources per plant in the period surrounding silking generates a marked fall in yield per plant that is not offset by the increase in the number of plants (Andrade et al., 1999; Vega et al., 2001).

It has been shown, however, that the optimum plant population density (number of plants that maximize grain yield) depends on the hybrid (Collins et al., 1965; Cox, 1996; Widdicombe and Thelen, 2002). Optimum plant population density is usually higher for short-season than for full-season hybrids (Brown et al., 1970; Beech and Basinski, 1975; Edwards et al., 2005). For short-season hybrids more plants are needed to reach the same amount of cumulative intercepted radiation (Edwards et al., 2005) because of their small leaf area per plant and small leaf area plasticity (Tollenaar, 1977; Dwyer et al., 1994; Otegui and Melón, 1997; Epinat-Le Signor et al., 2001) and a shorter duration of growth. This would indicate that hybrids with large leaf area per plant or large vegetative plasticity would have lower optimum plant density. We will refer to biomass plasticity as the capacity of the plant to modify its total aboveground biomass in response to a change in plant population density.

Vega et al. (2000) have shown that maize presents high and constant harvest index (HI) with intermediate values of total aboveground biomass per plant at maturity (Bp), and that it decreases when plants are very small (high plant density) and when plants are very large (low plant density). They concluded that this response is a consequence of the curvilinear relationship between yield per plant (Yp) and Bp. This relationship is different in hybrids from different eras (Echarte and Andrade, 2003) and could also be different in hybrids of contrasting maturity and reproductive allometry. Hybrids with a high reproductive partitioning at high Bp values would have lower optimum plant population density than those with less reproductive partitioning because reproductive growth would be less sink limited at low plant density in the former hybrids. The capacity of the plant to increase its grain yield in response to an increase in its total biomass will be taken herein as an indicator of reproductive partitioning.

Tollenaar (1989) found that increasing plant density produced an increase in total dry matter production and a decrease in harvest index and that optimum plant density was a trade-off of both effects. As pointed out by Donald and Hamblin (1976), to study biomass production and harvest index separately permits a far more analytical interpretation of environmental and genotypic influences than is possible from grain yields alone. No work, as far as we know, has shown the simultaneous effect of plant population density on biomass production and harvest index in maize hybrids differing in maturity (and with contrasting biomass plasticity and reproductive partitioning). An approach including the relationship between aboveground biomass per plant and plant density, the information of reproductive partitioning obtained from the individual plant-level analysis, and mathematical analysis may be useful to improve the understanding of maize grain yield response to plant population density.

We tested the hypothesis that the response of grain yield to plant population density would depend on the biomass plasticity and reproductive partitioning of the hybrid under evaluation. This hypothesis predicts that grain yield would increase more with increasing plant population density for hybrids with low biomass plasticity or low reproductive partitioning at high Bp values than for hybrids with opposite characteristics.

	MATERIALS AND METHODS

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Site and Crop Management
Two experiments were conducted at the Instituto Nacional de Tecnología Agropecuaria Balcarce Experimental Station (37°45' S, 58°18' W; 130 m altitude), during 2000–2001 (Exp. 1) and 2003–2004 (Exp. 2) seasons. The soil was a Typic Argiudoll with a minimum effective depth of 1.5 m and with an organic matter content of more than 50 g kg^–1 of soil in the first 25 cm of depth. Both experiments were seeded under conventional tillage at the optimal date (mid-October) and conducted under irrigation without any discernable water limitation. Nitrogen and P fertilizers were applied as recommended from soil tests. Pests and weeds were adequately controlled.

Plant Material and Experimental Design
Experiment 1 consisted of a factorial combination of three hybrids differing in maturity: KWS Romario (herein, Romario), Pioneer 37P73 (P37P73), and Dekalb 688 (DK688) and three plant population densities (5, 8, and 15 plants m^–2). The experiment was a complete block design with three replications. Growing degree days from emergence to physiological maturity were 1221, 1400, and 1595°C d for Romario, P37P73 and DK688, respectively (base temperature = 8°C; Capristo, 2004). Plot size was four rows 0.70 m apart and 12 m long.

Experiment 2 consisted of a factorial combination of the same three hybrids, six plant populations (4, 6, 8, 10, 12, and 14 plants m^–2) and two row spacings (0.52 and 0.7 m). Only the data from 0.7-m row spacing were included in this work. A split-strip-plot design with three replications was used with row spacing as main plot and hybrids as subplots. The different plant populations were assigned in strips within the subplots. Sub-sub-plots consisted of four rows with a length that permitted the harvest of 16 plants from the central rows while maintaining appropriate borders.

Measurements
In Exp. 1 the two central rows were harvested at physiological maturity. In Exp. 2, eight plants with appropriate border plants from each of the two central rows of the plot were harvested individually at physiological maturity. Actual plant density was calculated for each plot in Exp. 1 and for each row in Exp. 2. Plants were oven-dried at 65°C to constant weight, and Yp and Bp were determined. Harvest index was calculated as the ratio between Yp and Bp.

Data Analysis
Optimum plant population for each combination of hybrid and year was obtained by setting to zero the first derivative of the quadratic equation relating grain yield (g m^–2) and plant density (D; plants m^–2) (Eq. [1]) and solving for D.

[1]

and

[2]

where Y is grain yield (g m^–2), D is plant population density (plants m^–2), and a, b, and c are parameters.

The relationship between total aboveground biomass per plant at maturity (Bp) and plant population density was investigated. From the different models presented in Willey and Heath (1970), we chose the one proposed by Duncan (1958) and used by Major et al. (1991) for the relationship between yield per plant and plant population. We used ln instead of log to simplify the calculus. The equation used was

[3]

where a₁ and b₁ are constants and D is plant population density. Higher values of a₁ represent larger Bp values at very low plant density and low values of b₁ indicate a steeper decrease in Bp with increasing plant density. One curve was fit for each year since differences in environmental conditions among years can lead to differences in dry matter production (Aguilar and López-Bellido, 1996).

For the relationship between Bp and Yp (including first and second ears), a hyperbolic function with x intercept was used.

[4]

Parameters of this model are a₂, which represents the initial slope of the relationship; Bt (g per plant), which indicates the Bp threshold for yield (minimum Bp that produces yield), and b₂, which represents the degree of curvilinearity of the relationship. Low values of b₂ indicate that the curve approaches a straight line. This model is statiscally sound, includes biologically meaningful parameters, and has been widely used (Edmeades and Daynard, 1979; Tollenaar et al., 1992; Vega et al., 2000; Echarte and Andrade, 2003). The model was fit for each hybrid in both years. Wald-tests (Huet et al., 1996) confirmed that the parameters from both years were not different (P > 0.05) as expected from Andrade et al. (2002). Thus, one curve including the data from both years was fit and the resulting parameters were used for further analysis.

The maximum value of Bp used to fit Eq. [4] was the one for the lowest plant density in all cases. The relationships were adjusted by Table Curve Software (Jandel Scientific, Corte Madera, CA).

Statistical analyses of the parameters among hybrids were performed by Wald-tests. The relationship between harvest index and Bp was derived from the relationship between Yp and Bp (HI = Yp Bp^–1).

Equations [3] and [4] were combined to obtain the relationship between grain yield per plant and plant density (Eq. [5]).

[5]

Equations [3] and [5] were multiplied by D to obtain the relationships between total biomass per square meter (B) and D (Eq. [6]) and grain yield per square meter (Y) and D (Eq. [7]). The function relating harvest index and plant density was obtained as the ratio between Eq. [7] and Eq. [6].

[6]

and

[7]

The first derivatives of the relationships were set to zero and solved for D to obtain the optimum plant density for grain yield, biomass production, and harvest index. Optimum plant population density for grain yield was obtained through the bisection method (Hamming, 1986). Briefly, this method estimates Y' for different values of X until Y' is very close to 0. In that value of X there is an extreme point. The optimum is determined after checking that the extreme point is a maximum.

The parameters of Eq. [3] and Eq. [4] were evaluated to determine the relationship between each of them and the optimum plant density for each hybrid–year combination. Literature (Tollenaar, 1992) and unpublished data were used to study these relationships in a wider range of hybrids and environments. Correlation analyses among all the parameters were performed.

	RESULTS

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Optimum Plant Density in the Different Hybrids
The relationships between plant density and grain yield for the different hybrids are presented in Fig. 1 . The estimated optimum plant density was 13.7 and 13.5 plants m^–2 for Romario, 13 and 12.5 for P37P73, and 10.3 and 11.6 for DK688 in the years 2000 and 2003, respectively. These values, derived from Eq. [1] and [2], were similar to those obtained from Eq. [7] (r = 0.8; P = 0.06). Averaged across years, Romario and P37P73 presented higher optimum plant density than DK688 (P < 0.05, Faraway, 2006). Romario had the greatest increase in grain yield with increasing plant density, and DK688 the least. An increase in plant density from 5 to 10 plants m^–2 resulted in a 52, 37, and 23% increase in grain yield (averaged across years) for Romario, P37P73, and DK688, respectively.

View larger version (13K): [in this window] [in a new window]   Fig. 1. Grain yield (g m–2) as a function of plant population density (plants m–2) for hybrids KWS Romario, Pioneer 37P73, and Dekalb 688 in 2 yr (2000 and 2003). Quadratic equations were fitted to the data.

View larger version (14K): [in this window] [in a new window]   Fig. 2. Total aboveground biomass per plant (g plant–1) as a function of plant population density (plants m–2) for KWS Romario, Pioneer 37P73, and Dekalb 688 in 2 yr (2000 and 2003). Parameters and coefficients of determination (r2) of the exponential equations are presented in Table 1.

View this table: [in this window] [in a new window]   Table 1. Parameters of the relationships between total aboveground biomass per plant (Bp, g plant–1) and plant population density (D, plants m–2) for hybrids KWS Romario, Pioneer 37P73, and Dekalb 688 in 2 yr. Different letters within columns mean significant differences ( < 0.05). Comparisons among hybrids were performed by Wald-tests. SE of the parameters are shown in parentheses. Bp was modeled using Eq. [3].

View larger version (18K): [in this window] [in a new window]   Fig. 3. Grain yield per plant (g plant–1) as a function of total aboveground biomass per plant (g plant–1) for KWS Romario, Pioneer 37P73, and Dekalb 688 in 2 yr (2000 and 2003). The solid lines are the hyperbolic fit. Parameter and coefficients of determination (r2) of the hyperbolic equations are presented in Table 2.

View this table: [in this window] [in a new window]   Table 2. Parameters of the hyperbolic relationship between yield per plant and total aboveground biomass per plant (Eq. [4]) for hybrids KWS Romario, Pioneer 37P73, and Dekalb 688. Different letters within columns mean significant differences ( < 0.05). Comparisons among hybrids were performed by Wald-tests. SE of the parameters are shown between parenthesis.

View larger version (20K): [in this window] [in a new window]   Fig. 4. Harvest Index as a function of total aboveground biomass per plant (g plant–1) for KWS Romario, Pioneer 37P73, and Dekalb 688. The functions were derived from the hyperbolic fit in Fig. 3.

	DISCUSSION

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At low plant density, short-season hybrids intercept less radiation and produce less biomass than full-season ones because of the low biomass plasticity of short-season hybrids (Williams et al., 1965; Beech and Basinski, 1975; Major et al., 1991; Westgate et al., 1997). As illustrated in Fig. 2, DK688 and Romario greatly differed in Bp at the lowest plant density (maximum Bp value) but Bp values were similar at high plant density, indicating that the hybrids showed highly contrasting biomass plasticities.

There were also differences among hybrids in how grain yield per plant responded to total aboveground biomass per plant (Fig. 3). Grain yield can be also limited at low plant density if the hybrid presents low reproductive partitioning (Prior and Russell, 1975; Capristo, 2004; Hashemi et al., 2005). In those cases, as found by Dungan et al. (1958), harvest index is low at low plant density. This appeared to be the case of hybrid Romario (Fig. 4). Because of their small ears (Ritchie et al., 1993; Westgate et al., 1997; Capristo, 2004), short-season hybrids would be more prone to show a limitation of growth by reproductive sink capacity at low plant densities. At higher plant densities, this reproductive sink limitation would have been alleviated and harvest index increased. On the other hand, hybrids with high reproductive partitioning at high Bp, such as DK688, performed better than Romario and P37P73 at low plant density because grain yield would have been less reproductive-sink-limited for those conditions (i.e., greater prolificacy and potential grain number per ear at high Bp values; Fig. 4). Accordingly, small yield decreases at low plant density have been documented for hybrids with high potential yield per plant (Collins et al., 1965; Duvick, 1974; Prior and Russell, 1975; Sarquis, 1998; Tokatlidis, 2001; Tokatlidis et al., 2001).

Our mathematical approach allowed consideration of not only how hybrids produce biomass (capturing resources) but also how that biomass is partitioned. Previous experiments have not considered these mechanisms by which hybrids may respond to plant population density. In our case, harvest index increased between the minimum plant density and plant density for maximum grain yield in Romario and P37P73 (Table 3, Fig. 4). DK688, contrarily, presented a slightly larger harvest index at the minimum plant density than at the optimum plant density for grain yield in both years (Table 3). The increase in biomass production per unit of area from the minimum plant density to plant density for maximum grain yield was greatest in the short-season, poorly plastic hybrids (Table 3). The more plastic hybrid (DK688) was able to explore more resources at low plant density, and hence, presented a smaller increase in biomass production in response to increases in plant density.

Briefly, hybrids with low biomass plasticity and with low reproductive partitioning had the greatest responses to increasing plant population density for two possible reasons: (i) an alleviation of the reproductive–sink limitation that produced an increase in harvest index; and (ii) an increase in the capacity to explore resources and hence, in biomass production. As seen, the last reason was more important than the first one in all cases. Hybrids with high reproductive partitioning will increase grain yield due to an increase in biomass production at higher densities but not an increase of harvest index.

The regression analysis between optimum plant density (estimated from the quadratic fit between grain yield and plant density) and each of the parameters of Eq. [3] and [4] is presented in Table 4. Optimum plant density was positively associated with parameters b₁, a₂, and b₂ and negatively associated with parameter a₁ [Table 4(A)]. Parameter Bt was not related to optimum plant density [P = 0.79; Table 4(A)]. It is noteworthy, however, that the low number of plants with very low Bp may have diminished the accuracy of Bt estimation. Excluding Bt, all the parameters of Eq. [3] and [4] were highly correlated (|r| > 0.89).

This analytical approach should be taken carefully when different environmental conditions are considered. As seen for Romario, the environment can affect the Bp–plant density relationship. On the other hand, there is evidence that indicates the robustness of the Yp–Bp relationship across environments (Andrade et al., 2002). Nevertheless, contrasting conditions during vegetative and reproductive stages could affect harvest index, which would lead to deviations from the Yp–Bp curve (Cirilo and Andrade, 1994, Andrade et al., 1999).

In the present work, we used an approach that included the relationship between aboveground biomass per plant at maturity and plant density, information about reproductive partitioning, and a mathematical analysis to study maize grain yield response to plant population density. The effect of plant population density clearly depends on the characteristics of the hybrids. A hybrid with high biomass plasticity and high reproductive partitioning at high Bp will have a low optimum plant density. These conditions would be more likely to be met in full-season hybrids. Opposite features, usually found in short-season hybrids, would generate an increase in optimum plant density. In a future work the biomass plasticity and the reproductive partitioning of the hybrids will be related to hybrid maturity class.

	ACKNOWLEDGMENTS

 
The authors thank Pedro Capristo for the data collection from the 2000–2001 experiment; Professors Gabriela Cendoya and Graciela Duffard for the mathematical and statistical support; Dr. Pedro Laterra for the Ecological discussions; and the 2006 Advanced Eco-Physiology Course (Unidad Integrada Balcarce) for the useful suggestions. This work was supported by the Instituto Nacional de Tecnología Agropecuaria (INTA); Facultad de Ciencias Agrarias Univ. Nac. de Mar del Plata (UNMdP), and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). This work is part of a thesis by Tomás Sarlangue in partial fulfillment for the requirements for the Doctor's degree, UNMdP. Tomás Sarlangue holds a scholarship from CONICET.

	REFERENCES

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 

• Aguilar, M., and L. López-Bellido. 1996. Growth and yield of irrigated maize under Mediterranean conditions: The effect of cultivar and plant density. Cereal Res. Commun. 24:499–506.
• Andrade, F.H., C.R.C. Vega, S.A. Uhart, A. Cirilo, M.G. Cantarero, and O.R. Valentinuz. 1999. Kernel number determination in maize. Crop Sci. 39:453–459.[Abstract/Free Full Text]
• Andrade, F.H., L. Echarte, R.H. Rizzalli, A. Della Maggiora, and M. Casanovas. 2002. Kernel number prediction in maize under nitrogen or water stress. Crop Sci. 42:1173–1179.[Abstract/Free Full Text]
• Beech, D.F., and J.J. Basinski. 1975. Effect of plant populations and row spacings on early and late maize hybrids in the Ord Valley. Aust. J. Exp. Agric. 15:406–413.
• Brown, R.H., E.R. Beaty, W.J. Ethredge, and D.D. Hayes. 1970. Influence of row width and plant population on yield of two varieties of corn (Zea mays L.). Agron. J. 62:767–770.[Abstract/Free Full Text]
• Capristo, P.R. 2004. Comportamiento de híbridos de maíz de diferente largo de ciclo en la localidad de Balcarce. Tesis de Magister Scientiae, UNMdP, Balcarce, Buenos Aires, Argentina.
• Cirilo, A.G., and F.H. Andrade. 1994. Sowing date and maize productivity: II. Kernel number determination. Crop Sci. 34:1246–1252.
• Collins, W.K., W.A. Russell, and S.A. Eberhart. 1965. Performance of two-ear type of Corn Belt maize. Crop Sci. 5:113–116.[Free Full Text]
• Cox, W.J. 1996. Whole-plant physiological and yield responses of maize to plant density. Agron. J. 88:489–496.[Abstract/Free Full Text]
• Donald, C.M., and J. Hamblin. 1976. The biological yield and harvest index of cereals as agronomic and plant breeding criteria. Adv. Agron. 28:361–405.
• Duncan, W.G. 1958. The relationship between corn population and grain yield. Agron. J. 50:82–84.[Abstract/Free Full Text]
• Dungan, G.H., A.L. Lang, and J.W. Pendleton. 1958. Corn plant population in relation to soil productivity. Adv. Agron. 10:435–472.
• Duvick, D.N. 1974. Continuous backcrossing to transfer prolificacy to a single-eared inbred line of maize. Crop Sci. 14:69–71.[Abstract/Free Full Text]
• Dwyer, L.M., B.L. Ma, L. Evenson, and R.I. Hamilton. 1994. Maize physiological traits related to grain yield and harvest moisture in mid to short-season environments. Crop Sci. 34:985–992.[Abstract/Free Full Text]
• Echarte, L., and F.H. Andrade. 2003. Harvest index stability of Argentinean maize hybrids released between 1965 and 1993. Field Crops Res. 82:1–12.
• Edmeades, G.O., and T.B. Daynard. 1979. The relationship between final yield and photosynthesis at flowering in individual maize plants. Can. J. Plant Sci. 89:585–601.
• Edwards, J.T., L.C. Purcell, and E.D. Vories. 2005. Light interception and yield of short-season maize (Zea mays L.) hybrids in the Midsouth. Agron. J. 97:225–234.[Abstract/Free Full Text]
• Epinat-Le Signor, C., S. Dousse, J. Lorgeou, J.B. Denis, R. Bonhomme, P. Carolo, and A. Charcosset. 2001. Interpretation of genotype environment interactions for early maize hybrids over 12 years. Crop Sci. 41:663–669.[Abstract/Free Full Text]
• Faraway, J.J. 2006. Extending the linear model with R. Chapman & Hall/CRC Press, Boca Raton, FL.
• Hamming, R.W. 1986. Numerical methods for scientists and engineers. Dover Publ., Mineola, NY.
• Hashemi, A.M., S.J. Herbert, and D.H. Putnam. 2005. Yield response of corn to crowding stress. Agron. J. 97:839–846.[Abstract/Free Full Text]
• Huet, S., A. Bouvier, M.A. Gruet, and E. Jolivet. 1996. Statistical tools for nonlinear regression. Springer, New York.
• Loomis, R.S., and D.J. Connor. 1996. Crop ecology. Productivity and management in agricultural systems Cambridge Univ. Press, Cambridge.
• Major, D.J., B.W. Beasley, and R.I. Hamilton. 1991. Effect of maize maturity on radiation use efficiency. Agron. J. 83:895–903.[Abstract/Free Full Text]
• Otegui, M.E., and S. Melón. 1997. Kernel set and flower synchrony within the ear of maize: I. Sowing date effects. Crop Sci. 37:441–447.[Abstract/Free Full Text]
• Prior, C.L., and W.A. Russell. 1975. Yield performance of nonprolific and prolific maize hybrids at six plant densities. Crop Sci. 15:482–486.[Abstract/Free Full Text]
• Ritchie, S.W., J.J. Hanway, and G.O. Benson. 1993. How a corn plant develops. Special Report N° 48. Coop. Ext. Service, Ames, IA.
• Sarquis, J.I. 1998. Yield response of two cycles of selection from a semiprolific early maize population to plant, sucrose infusion and pollination control. Field Crops Res. 55:109–116.
• Tetio-Kagho, F., and F.P. Gardner. 1988a. Responses of maize to plant population density: I. Canopy development, light relationships, and vegetative growth. Agron. J. 80:930–935.[Abstract/Free Full Text]
• Tetio-Kagho, F., and F.P. Gardner. 1988b. Responses of maize to plant population density: II. Reproductive development, yield, and yield adjustments. Agron. J. 80:935–940.[Abstract/Free Full Text]
• Tokatlidis, I.S. 2001. The effect of improved potential yiel per plant on crop yield potential and optimum plant density in maize hybrids. J. Agric. Sci. 137:299–305.
• Tokatlidis, I.S., M. Koutsika-Sotiriou, and A.C. Fasoulas. 2001. The development of density-independent hybrids in maize. Maydica 46:21–25.[Web of Science]
• Tollenaar, M. 1977. Sink-source relationships during reproductive development in maize. A review. Maydica 22:49–75.
• Tollenaar, M. 1989. Genetic improvement in grain yield of commercial maize hybrids grown in Ontario from 1959 to 1988. Crop Sci. 29:1365–1371.[Abstract/Free Full Text]
• Tollenaar, M. 1992. Is low plant density a stress in maize? Maydica 37:305–311.[Web of Science]
• Tollenaar, M., L.M. Dwyer, and D.W. Stewart. 1992. Ear and kernel formation in maize hybrids representing three decades of grain yield improvement in Ontario. Crop Sci. 32:432–438.[Abstract/Free Full Text]
• Vega, C.R.C., V.O. Sadras, F.H. Andrade, and S.A. Uhart. 2000. Reproductive allometry in soybean, maize and sunflower. Ann. Bot. (Lond.) 85:461–468.[Abstract/Free Full Text]
• Vega, C.R.C., F.H. Andrade, V.O. Sadras, S.A. Uhart, and O.R. Valentinuz. 2001. Seed number as a function of growth. A comparative study in soybean, sunflower and maize. Crop Sci. 41:748–754.[Abstract/Free Full Text]
• Westgate, M.E., F. Forcella, D.C. Reicosky, and J. Somsen. 1997. Rapid canopy closure for maize production in the northern US Corn Belt: Radiation-use efficiency and grain yield. Field Crops Res. 49:249–258.[CrossRef]
• Widdicombe, W.D., and K.D. Thelen. 2002. Row width and plant density effects on corn grain production in the northern Corn Belt. Agron. J. 94:1020–1023.[Abstract/Free Full Text]
• Willey, R.W., and S.B. Heath. 1970. The quantitative relationships between plant population and crop yield. Adv. Agron. 21:281–321.
• Williams, W.A., R.S. Loomis, and C.R. Lepley. 1965. Vegetative growth of corn as affected by population density: I. Productivity in relation to interception of solar radiation. Crop Sci. 5:211–215.[Free Full Text]
• Williams, W.A., R.S. Loomis, W.G. Duncan, A. Dorvrat, and A.F. Nunez. 1968. Canopy architecture at various population densities and the growth and grain yield of corn. Crop Sci. 8:303–308.[Abstract/Free Full Text]

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