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Journal of Food, Agriculture & Environment Vol.10 (3&4): 795-801. 2012

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Effects of plant density and row spacing on biomass production and some of physiological indices of corn (Zea maize L.) in second cropping Raouf Seyed Sharifi 1* and Nayer Nabi Zadeh 2 Department of Agronomy and Plant Breeding, College of Agriculture, University of Mohaghegh Ardabili, Ardabil, Iran. 2MSc Student, College of Agriculture, University of Mohaghegh Ardabili, Ardabil, Iran. *e-mail: [email protected]

1

Received 25 June 2012, accepted 6 October 2012.

Abstract In order to evaluate effects of plant density and row spacing on biomass production and some physiological indices of corn (Zea maize L.) in second cropping, a factorial experiment based on randomized complete block design was conducted in Research Farm, University of Mohaghegh Ardabili in 2007. Factors were plant population at three levels (7, 9 and 11 plants m-2 ) with row spacing at three levels (45, 60 and 75 cm). The results showed that various levels of plant population and row spacing affected biomass production and growth indices of corn (Zea maize L.). Mean comparisons showed that maximum total biomass was obtained at 11 plants m-2. Row spacing had different response to total biomass. Maximum total biomass was obtained in row spacing of 45 cm and minimum in row spacing of 75 cm. Investigation of variances trend of dry matter accumulation indicated that in all of treatment compounds, it increased slowly until 28 days after sowing and then increased rapidly till 77-84 days after sowing. From 84 days after sowing till time of harvest, it decreased due to increasing aging of leaves, decreasing of leaf area index, net assimilation rate and crop growth rate. Increase in plant population also significantly increased the crop growth rate and the maximum of it was observed by the plots that was applied 11 plants m-2 with row spacing of 45 cm. In addition, in all of treatment compounds, CGR increased slowly until 52 days after sowing and then decreased slowly till 53-54 days after sowing. From 54 days after sowing till harvest time, it decreased rapidly due to decreasing of leaf area index and net assimilation rate. Thus, it can be suggested that in order to increasing of total biomass, crop growth rate, leaf area index, net assimilation rate and the other of physiological indices should be applied 11 plants m-2 with row spacing of 45 cm in conditions of Ardabil Plain in second cropping. Key words: Corn, plant population, physiological indices, row spacing.

Introduction Corn (Zea mays L.) belongs to the family Poaceae (Gramineae) and the tribe Maydeae. It is one of the most important cereal crop grown in Iran. Maize grain is used for both human consumption and poultry feed. It has a great utility in agro-industry. This crop has much higher grain protein content than our staple food rice. Based on area and production, maize is the 3rd most important cereal crop after wheat and rice in world 1. Corn is among the least tolerant of crops to high population densities 2. One of the most important effective factors is non application of optimal plant population per hectare 3. As maize do not have tillering capacity to adjust to variation in plant stand, agronomic practices such as plant population and row spacing are known to affect crop environment, which influence the yield 4. Optimum population levels should be maintained to exploit maximum natural resources, such as nutrients, sunlight, soil moisture and to ensure satisfactory yield. On the other hand, in order to increase yield, we must plant maize at proper plant population. When plant density is too high, it encourage inter plants competition for resources. Then crop net photosynthesis process will be affected due to less light penetration in the crop canopy as well as increase in the competition for available nutrient which will affect yield. On the other hand, application of optimum plant density in corn production helps for the proper utilization of solar radiation. If plant population is lower than optimum plant population then per hectare production will be low and weeds will also be more 5.

Photosynthetic efficiency and growth in maize are strongly related to the effect of canopy architecture on the vertical distribution of light within the canopy 6. Increasing plant density is one of the ways of increasing the capture of solar radiation within the canopy7. However, the efficiency of the conversion of intercepted solar radiation into maize yield decreases with a high plant population density because of mutual shading in the plants. In addition, a plant population density resulting in interplant competition affects vegetative and reproductive growth 8. Akman9 stated that plant height and ear yield of sweet corn increased as the plant density increased, but ear length, ear diameter and filled ear length decreased in high plant density. Increasing of corn plant population from 53,333 to 88,888 plants/ha significantly increased the fresh ear yield 10. Akbar et al. 11 reported that the most proper sowing density in corn was 100,000 plants/ha. Many studies have been conducted with the aim of determining the optimum plant density for maize. Unfortunately, there is no single recommendation for all conditions, because the optimum plant density varies depending on environmental factors such as soil fertility, moisture supply, genotype 12, planting date, planting pattern, plant population and harvest time 13, 14. Generally, the yield of a single maize plant decreases with increasing plant population density whereas the yield per unit area increases 15. Fasoula and Fasoula 16 emphasized the importance of low stress conditions (i.e., very low plant density, so that competition among

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plants is avoided) in optimizing the effectiveness of selection for improved potential yield per plant, tolerance to stresses and responsiveness to input. Growth analysis is still the most simple and precise method to evaluate the contribution of different physiological processes in plant development. The physiological indices such as leaf area index (LAI), total dry matter (TDM), crop growth rate (CGR) and relative growth rate (CGR) are influenced by genotypes, plant population, climate and soil fertility 17. Rao et al.18 suggested that leaf area index (LAI) and leaves architecture are two main characteristics that define light interception in the canopy. Egly and Guffy 19 reported that total dry matter is influenced by relative growth rate, crop growth rate and net assimilation rate. Dwyer et al.20 reported that increase in population plant decreased leaf area index and net assimilation rate (NAR) per plant, but increased them in per area. The aim of this study was to determine the effects of plant density and row spacing on biomass production and the some of physiological indices of corn (hybrid SC-302) in conditions of Ardabil Plain in second cropping. Materials and Methods In order to determine the effects of plant density and row spacings on biomass production and some of physiological indices of corn (hybrid SC-302) under conditions of Ardabil Plain in second cropping. A factorial experiment based on randomized complete block design was conducted in Research Farm, University of Mohaghegh Ardabili, in 2007. Factors were plant population (7, 9 and 11 plants m-2) with row spacing at three levels (45, 60 and 75 cm). Climatically, the area placed in the semi-arid temperate zone with cold winter and hot summer. Average rainfall is about 385 mm and the most rainfall is concentrated between winter and spring. Table 1 shows physicochemical properties of farm soil used in the experiment. Temperature mean and rainfall during the period of corn growth season (June –Sep) is presented in Fig. 1. The soil was silt loam with pH about 8.2. The field was prepared well before sowing by plowing twice with tractor followed planking to make a fine seed bed. In each plot there were 6 rows 6 m long. Plots and blocks were separated by 5 m unplanted distances. Corn seeds were sown in the third week of June. Nitrogen fertilizer was applied 150 kg/ha in the form of urea as 1/3 at sowing, 1/3 at 6-7 leafy and 1/3 at appearance of tasseling. Weeds were controlled manually. All other agronomic operations except those under study were kept normal and uniform for all treatments. For estimation of growth analysis, from 0.2 m2 in each plot was sampled randomly in each treatment compound and averaged for recording the change in dry weight in shoots (aboveground). Sampling intervals were seven days at different stages of the corn growth (28, 35,42, 49, 56, 63, 70, 77, 83 and 91 days after sowing). For dry weight determination, samples were oven dried at 70±5oC to constant weight. The variances of total dry matter (TDM), crop growth rate (CGR), net assimilation rate and relative growth rate (RGR) were determined using equations 1-4 21 , 22. Leaf area index was determined by dividing leaf area over ground area and was estimated using of Eq. 5.

2

3

TDM=ea+bt+ct +dt

(1)

RGR=b+2ct+3dt2

(2) 2

3

CGR=(b+2ct+3dt2)×e(a+bt+ct +dt )

(3)

NAR=CGR/LAI

(4)

2

LAI=e(a+bt+ct )

(5)

In these equations, t is the intervals of sampling or in the other hand, the beginning and end of the interval sampling and a, b and c are coefficients of equations. Total biomass was estimated from 1 m2 from the three middle rows in each plot. Analysis of variance and regression were performed using SAS and Excel computer software packages. The main effects and interactions were tested using the LSD test. Results and Discussion Total dry matter: Trend of variances of total dry matter in treatment combination row spacing × plant population levels in Fig. 2 shows that in all of treatment combinations, total dry matter increased during plant growth with increasing plant population and decreasing of row spacing and reached to a maximum level at 7784 days after planting,and showed a declining trend at harvest (84-91 DAS). Similar results were also reported by Egly and Guffy19. The increase in total dry matter with the increasing plant population and decreasing row spacing indicates the favorable response of biomass produced by corn to plant population. It is perhaps related to accelerating the photosynthesis activity that caused dry matter accumulation increase. Dry matter accumulation in row spacing of 45 cm in various levels of plant population shows that dry matter increased slowly until 28 days after sowing and then increased rapidly till 77-84 days after sowing. From 84 days after sowing till time of harvest, accumulation of dry matter decreased due to decreasing crop growth rate and net assimilation rate (Figs 3 and 4). In addition, regression equations are given in Table 2. On the other hand, total dry matter in unit of area increased with increasing level of plant population, as the maximum and the minimum biomass in unit area were obtained from 7 and 11 plants m-2, respectively (Fig. 5). The total dry matter in other row spacings (60 and 75 cm) indicated that in all of row spacings it increased with increasing plant population and trend of variances was similar to dry matter accumulation in row spacing of 45 cm. Increasing leaf area index is one of the ways of increasing the capture of solar radiation within the canopy and production of dry matter. Hence, total dry matter decreases when leaf area index is decreased (Fig. 6). In this study, the maximum value of total dry matter was obtained in the maximum value of leaf area index. It is perhaps related to relationship between leaf area index and total dry matter. Our findings are in agreement with observations made by Winter and Ohlrogge 23 in corn.

Table 1. Soil physico-chemical properties at depth of 0-30 cm. Depth of sampling (cm)

pH

(%) SP

CaCO3 (%)

Clay (%)

Loam (%)

Sand (%)

Texture

O.C (%)

N total (%)

P available (mg/kg)

0-30

8.2

46

18.3

5

70

24

Silty-loam

78

16

16

796

K available (mg/kg) 385

Journal of Food, Agriculture & Environment, Vol.10 (3&4), July-October 2012

min temprature (0 C)

rainfall (mm)

25

20

20

15

15 10

10

5

5 0

0 June

July

Agu

(a) Crop growth rate (g/m2.day)

25

rainfall (mm)

30

Rainfall (mm)

percipitation (0 C)

max temprature (0 C)

Sep

Figure 1. Minimum and maximum temperatures and rainfall recorded during the period of corn growth (June –Sep) in 2007. Days after sowing

Total biomass (g/m2)

(a)

Estimated 9 plants/m2 Observed 9 plants/m2´´ Estimated 7 plants/m2 Observed 7 plants/m2´´ Estimated 11 plants/m2´´ Observed 11 plants/m2´´

Days after sowing

Crop growth rate (g/m2.day)

(b)

(b)

Estimated 7 plants/m2 Observed 7 plants/m2 Estimated 9 plants/m2´´ Observed 9 plants/m2´´ Estimated 11 plants/m2 Observed 11 plants/m2´´

Days after sowing

Total biomass (g/m2)

(c)

(c)

Crop growth rate (g/m2.day)

Total biomass (g/m2)

Days after sowing

Days after sowing Estimated 7 plants/m2 Observed 7 plants/m2 Estimated 11 plants/m2 Observed 11 plants/m2 Estimated 9 plants/m2 Observed 11 plants/m2

Days after sowing

Figure 2. Variances of total dry matter in different plant population with row spacing of 45 cm (a), 60 cm (b) and 75 cm (c).

Figure 3. Variances of crop growth rate in different plant population with row spacing of 45 cm (a), 60 cm (b) and 75 cm (c).

Crop growth rate: Variances of crop growth rate showed that in all of treatment combinations, the crop growth rate was low in the beginning of sampling, thereafter increased considerably up to 47-48 days after sowing with a peak in 52 days after sowing (Fig. 3), and showed a declining trend at 53-54 days after sowing. Regression equations are given in Table 2. The increase in CGR

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(a)

Relative growth rate (g/gr.day)

Net assimilation rate (g/m2.day)

(a)

Days after sowing

Days after sowing

(b)

Relative growth rate (g/g.day)

Net assimilation rate (g/m2.day)

(b)

Days after sowing

Relative growth rate (g/g.day)

Days after sowing

Net assimilation rate (g/m2.day)

(c)

(c)

Days after sowing

Figure 5. Variances of relative growth rate in different plant population with row spacing of 45 cm (a), 60 cm (b) and 75 cm (c).

Days after sowing

with the increasing rate of plant population may be due to accelerating the photosynthesis activity and the positive response of crop growth rate to plant population. Similar results were also reported by Jeffrey et al. 24. The decrease in crop growth rate up to harvesting time is due to senescence of leaves and decrease of leaf area index and net assimilation rate (Figs 4 and 6). Similar results were reported by Egly and Guffy 19 in soybean.

between plants for light and other resources (Fig. 4), and decreased considerably up to harvesting time. This might be related to shading and competition between plants for light and other resources. The increase in NAR with the increasing of plant population and decreasing of row spacing may be due to accelerating the photosynthesis activity. Moderras et al.7 reported that increasing plant density is one of the ways of increasing the capture of solar radiation within the canopy and increasing of net assimilation rate. In this study, net assimilation rate per area increased with increasing of plant population and decrease of row spacing. Similar results have been reported by Weber et al. 25 in soybean.

Net assimilation rate: Trend of variances of net assimilation rate showed that in all of treatment combinations, it was high in the beginning of sampling (28 days after sowing) due to high light penetration in the crop canopy and less shading and competition

Relative growth rate: In the initial stages of the plant growth the ratio between alive and dead tissues is high and almost the entire cells of productive organs are activity engaged in vegetative matter production. In all of treatment compounds, RGR decreased during

Figure 4. Variances of net assimilation rate in different plant population with row spacing of 45 cm (a), 60 cm (b) and 75 cm (c).

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Journal of Food, Agriculture & Environment, Vol.10 (3&4), July-October 2012

Days after sowing

Leaf area index

(b)

Estimated 11 plants/m2´´ Observed 11 plants/m2´´ Estimated 9 plants/m2 Observed 11 plants/m2 2 Estimated 7 plants/m2´´ Observed 7 plants/m Days after sowing

Leaf area index

(c)

Estimated 7 plants/m2 Observed 7 plants/m2 Estimated 9 plants/m2 Observed 9 plants/m2 Estimated 11 plants/m2´´2 Observed 11 plants/m Days after sowing

Figure 6. Variances of leaf area index in different plant population with row spacing of 45 cm (a), 60 cm (b) and 75 cm (c).

plant growth with decreasing plant population and reached to a minimum level at 84-91 days after planting (Fig. 5). Regression equations are given in Table 2. The reason of decreasing RGR at the final stage can be related to increasing of the dead and woody tissues comparing to the alive and active texture and decrease of leaf area index. Similar observations have been reported by Shukla et al. 26 in Indian mustard and Jeffrey et al. 24 in corn.

Biomass produced: The biomass produced was significantly affected by both row spacing and plant population. Plant population significantly increased the biomass produced. The biomass produced varied between 390.39 g/m2 in 7 plants m-2 and 528.66 g/m2 in 11 plants m-2 (Fig. 7). Row spacing had different response to biomass produced. The biomass produced varied between 484.44 g/m2 in row spacing of 45 cm and 434.28 g/m2 in row spacing of 75 cm (Fig. 8). Our findings are in agreement with observations made by Wiersma 28. These results are in agreement with total dry matter and leaf area index. This might be related to correlation between biomass with crop growth rate and leaf area index. Weber et al. 25 reported that both total dry matter and leaf area index were poor predictors of yield. Winter and Ohlrogge 23 suggested that yield in each of treatment combination increased when leaf area index and total dry matter increased. In this study, biomass produced increased when leaf area index and total dry matter increased.

Total biomass (g/m2)

Estimated 7 plants/m2 Observed 7 plants/m2 Estimated 11 plants/m2 Observed 11 plants/m2 Estimated 9 plants/m2 Observed 9 plants/m2

Leaf area index: Study of variances of leaf area index in Fig. 6 showed that in all of treatment compounds, leaf area index increased during plant growth with increasing plant population and reached to a maximum level at 63 days after planting, and showed a declining trend at 63-70 days after sowing. From 70 days after sowing till time of harvesting, leaf area index decreased rapidly due to increasing aging of leaves, shading and competition between plants for light and other resources. Increasing leaf area index is one of the ways of increasing the capture of solar radiation within the canopy and production of dry matter. Hence, dry matter produced decreases with decreasing of leaf area index. In the present study, trend of variances of leaf area index in treatment compounds of row spacing ×various levels of plant population was according to crop growth rate. These results are in agreement with trend of variances of total dry matter. Similar results have also been reported by Faris and De Pauw 27 and Wiersma 28 in wheat.

Plant population (plants/m2)

Figure 7. Means comparison of total biomass in different plant population.

Total biomass (g/m2)

Leaf area index

(a)

Row spacing (cm)

Figure 8. Means comparison of total biomass in row spacing.

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Table 2. Regression equations between physiological indices of corn as affected by row spacing× plant population. Treatment combination (row spacing× plant population) 7 plants m-2 with row spacing of 45 cm 9 plants m-2 with row spacing of 45 cm 11 plants m-2 with row spacing of 45 cm 7 plants m-2 with row spacing of 60 cm 9 plants m-2 with row spacing of 60 cm 11 plants m-2 with row spacing of 60 cm 7 plants m-2 with row spacing of 75 cm 9 plants m-2 with row spacing of 75 cm 11 plants m-2 with row spacing of 75 cm 7 plants m-2 with row spacing of 45 cm 9 plants m-2 with row spacing of 45 cm 11 plants m-2 with row spacing of 45 cm 7 plants m-2 with row spacing of 60 cm 9 plants m-2 with row spacing of 60 cm 11 plants m-2 with row spacing of 60 cm 7 plants m-2 with row spacing of 75 cm 9 plants m-2 with row spacing of 75 cm 11 plants m-2 with row spacing of 75 cm 7 plants m-2 with row spacing of 45 cm 9 plants m-2 with row spacing of 45 cm 11 plants m-2 with row spacing of 45 cm 7 plants m-2 with row spacing of 60 cm 9 plants m-2 with row spacing of 60 cm 11 plants m-2 with row spacing of 60 cm 7 plants m-2 with row spacing of 75 cm 9 plants m-2 with row spacing of 75 cm 11 plants m-2 with row spacing of 75 cm 7 plants m-2 with row spacing of 45 cm 9 plants m-2 with row spacing of 45 cm 11 plants m-2 with row spacing of 45 cm 7 plants m-2 with row spacing of 60 cm 9 plants m-2 with row spacing of 60 cm 11 plants m-2 with row spacing of 60 cm 7 plants m-2 with row spacing of 75 cm 9 plants m-2 with row spacing of 75 cm 11 plants m-2 with row spacing of 75 cm

Regression equation TDM = e (-2.94 + 0.314x - 0.00366x2 + 0.0000145x3) TDM = e (-2.7 + 0.31x - 0.00361x2 + 0.0000142x3 ) TDM = e (-2.53 + 0.292x - 0.00327x2 + 0.0000122x3) TDM = e (-2.93 + 0.299x - 0.0034x2 + 0.0000131x3) TDM = e (-2.91 + 0.302x - 0.00342x2 + 0.000013x3) TDM = e (-3.31+ 0.327x - 0.00385x2 + 0.0000152x3) TDM = e (-3.13 + 0.303x - 0.00346x2 + 0.0000134x3) TDM = e (-3.0028 + 0.299x - 0.00338x2 + 0.0000128x3) TDM = e (-3.27 + 0.318x - 0.00371x2 + 0.0000146x3) CGR= (0.314 - 0.00732x +0.0000435x2 ) e (-2.94 + 0.314x - 0.00366x2 + 0.0000145x3) CGR= (0.31 - 0.00722x + 0.0000426x2 ) e (-2.7 + 0.31x -0 .00361x2 + 0.0000142x3) CGR= (0.292 - 0.00654x + 0.0000366x2 ) e (-2.53 + 0.292x -0.00327x2 + 0.0000122x3) CGR= (0.299 - 0.0068x + 0.0000393x2 ) e (-2.93 + 0.299x - 0.0034x2 + 0.000014x3) CGR= (0.302 - 0.00684x + 0.000039x2 ) e (-2.91 + 0.302x -0.00342x2 + 0.000013x3) CGR= (0.327 – 0.0077x + 0.0000456x2 ) e (-3.31 + 0.327x - 0.00385x2 + 0.000015x3) CGR= (0.303 - 0.00692x + 0.0000402x2 ) e (-3.13 + 0.303x - 0.00346x2 + 0.0000134x3) CGR= (0.299 – 0.00676x + 0.0000384x2 ) e (-3.0028 + 0.299x -0.00338x2 + 0.0000128x3) CGR= (0.318 - 0.00742x + 0.0000438x2 ) e (-3.27 + 0.318x - 0.00371x2 + 0.0000146x3) RGR= (0.314 - 0.00732x + 0.0000435x2 ) RGR= (0.31 - 0.00722x + 0.0000426x2 ) RGR= (0.292 - 0.00654x + 0.0000366x2 ) RGR= (0.299 - 0.0068x + 0.0000393x2 ) RGR= (0.302 - 0.00684x + 0.000039x2 ) RGR= (0.327 - 0.0077x + 0.0000456x2 ) RGR= (0.303 - 0.00692x + 0.0000402x2 ) RGR= (0.299 - 0.00676x + 0.0000384x2 ) RGR= (0.318 - 0.00742x + 0.0000438x2 ) LAI = e (-9.94 + 0.342x - 0.00262x2) LAI = e (-9.87 + 0.344x - 0.000366x2) LAI = e (-10.25 + 0.355x - 0.00037x2) LAI = e (-9.93 + 0.343x - 0.000265x2) LAI = e (-10.35 + 0.357x - 0.00276x2) LAI = e (-9.97 + .345x - .000266x2) LAI = e (-8.67 + 0.298x - 0.00236x2) LAI = e (-8.51 + 0.299x - 0.00241x2) LAI = e (-8.61 + 0.311x - 0.00256x2)

Conclusions In this experiment, plant population showed significant effects on biomass produced and physiological indices of corn (SC-302 hybrid) such as total dry matter, crop growth rate, relative growth rate, net assimilation rate and leaf area index. The highest biomass and physiological indices recorded in application of 11 plants m-2 with row spacing of 45 cm. It can be suggested that in conditions of Ardabil Plain in second cropping SC-302 hybrid should be applied to 11 plants m-2 with row spacing of 45 cm. Acknowledgements We want to thank Department of Agronomy and Plant Breeding, College of Agriculture, University of Mohaghegh Ardabili, Ardabil, Iran, that helped in all the time of research. References Tollenaar, M. and Dwyer, L. M. 1999. Physiology of maize. In Smith,D. L. and Hamel, C. (eds). Crop Physiology and Processes. Springer Verlag, Berlin, Heidelberg, pp. 169-199. 2 Yoshida, S. 1972. Physiological aspects of grain yield. Ann. Rev. Plant Physiology 23:437-484. 3 Sangoi, L. R. and Salvador, J. 1998. Influence of plant height and leaf number on maize production at high plant densities. Agronomy Journal 33:297-306. 1

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0.92 0.87 0.89 0.88 0.91 0.94 0.94 0.91 0.89 0.91 0.89 0.92 0.87 0.89 0.88 0.91 0.94 0.94 0.91 0.89 0.91 0.92 0.87 0.89 0.88 0.91 0.94 0.94 0.91 0.89 0.91 0.92 0.87 0.89 0.88 0.91

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