ORIGINAL PAPER

Ecological significance of rice (Oryza sativa) planting densityand nitrogen rates in managing the growth and competitive abilityof itchgrass (Rottboellia cochinchinensis) in direct-seeded ricesystems

Tahir Hussain Awan • Pompe C. Sta Cruz •

Bhagirath Singh Chauhan

Received: 15 January 2014 / Accepted: 14 June 2014

� Springer-Verlag Berlin Heidelberg 2014

Abstract Current understanding is that high planting

density has the potential to suppress weeds and crop–weed

interactions can be exploited by adjusting fertilizer rates.

We hypothesized that (a) high planting density can be used

to suppress Rottboellia cochinchinensis growth and (b) rice

competitiveness against this weed can be enhanced by

increasing nitrogen (N) rates. We tested these hypotheses

by growing R. cochinchinensis alone and in competition

with four rice planting densities (0, 100, 200, and 400

plants m-2) at four N rates (0, 50, 100, and 150 kg ha-1).

At 56 days after sowing (DAS), R. cochinchinensis plant

height decreased by 27–50 %, tiller number by 55–76 %,

leaf number by 68–84 %, leaf area by 70–83 %, leaf bio-

mass by 26–90 %, and inflorescence biomass by 60–84 %,

with rice densities ranging from 100 to 400 plants m-2. All

these parameters increased with an increase in N rate.

Without the addition of N, R. cochinchinensis plants were

174 % taller than rice; whereas, with added N, they were

233 % taller. Added N favored more weed biomass pro-

duction relative to rice. R. cochinchinensis grew taller than

rice (at all N rates) to avoid shade, which suggests that it is

a ‘‘shade-avoiding’’ plant. R. cochinchinensis showed this

ability to reduce the effect of rice interference through

increased leaf weight ratio, specific stem length, and

decreased root-shoot weight ratio. This weed is more

responsive to N fertilizer than rice. Therefore, farmers

should give special consideration to the application timing

of N fertilizer when more N-responsive weeds are present

in their field. Results suggest that the growth and seed

production of R. cochinchinensis can be decreased con-

siderably by increasing rice density to 400 plants m-2.

There is a need to integrate different weed control mea-

sures to achieve complete control of this noxious weed.

Keywords Biomass partitioning � Crop–weed

competition � Light � Shade � Seed rate �Weeds suppression

Introduction

Weeds are unwanted plants that grow out of place and have

economic implications (Griffin 1991; DFID Weeds Project

2002). They compete with crops for nutrients, water, solar

radiation, and space, and this subsequently reduces crop

yield and quality (Oyewole and Ibikunle 2010). To over-

come food insecurity, besides other challenges to be

overcome, problems associated with weeds, especially

noxious weeds such as Rottboellia cochinchinensis (Lour.)

W. D. Clayton (itchgrass), must be faced (Oyewole and

Ibikunle 2010).

Rottboellia cochinchinensis has jointed inflorescences

that can easily disintegrate and shed partly on the ground as

they are ripening. This weed produces a large number of

seeds throughout the growing season (Smith and Fonseca

2001; NAPPO 2003). Its control is very difficult because of

Communicated by M. Traugott.

T. H. Awan (&)

Weed Science, Crop and Environmental Sciences Division,

International Rice Research Institute (IRRI), Los Banos,

Philippines

e-mail: t.awan@irri.org; tahirawanrri@gmail.com

T. H. Awan � P. C. Sta Cruz

Crop Science Cluster, College of Agriculture, University of

Philippines Los Banos, Los Banos, Philippines

B. S. Chauhan

Queensland Alliance for Agriculture and Food Innovation

(QAAFI), The University of Queensland, Toowoomba,

QLD 4350, Australia

123

J Pest Sci

DOI 10.1007/s10340-014-0604-4

seed dormancy, which can persist for up to 4 years (Etejere

and Ajibola 1990; NAPPO 2003). Its seedlings can emerge

even from a soil burial depth of 8 cm (Bolfrey-Arku et al.

2011; Chauhan and Johnson 2009). R. cochinchinensis can

grow well in low-moisture conditions (Bolfrey-Arku et al.

2011), frequently wet places, and shallow standing water

(NAPPO 2003; Oyewole and Ibikunle 2010). It is a major

and important weed of agricultural crops, including rice,

and its importance is increasing day by day as a noxious

weed; it has been reported to occur in at least 18 crops in

various agro-ecological conditions in 45 countries (Holm

et al. 1977; NAPPO 2003; Oyewole and Ibikunle 2010). It

is now one of the most noxious weeds in the Philippines.

Rottboellia cochinchinensis, being a C4 weed, has a high

CO2 fixation rate and water-use and nitrogen (N)-use effi-

ciency (Migo et al. 1991; Ampong-Nyarko and De Datta

1993), which makes this weed highly competitive with

rice. It can reduce rice yield from 30 to 100 % (Ampong-

Nyarko and De Datta 1993). In Costa Rica, farmers spend

34 % of total crop inputs on controlling R. cochinchinensis

(Calvo et al. 1996). It also has an allelopathic effect on

crops, such as maize and rice (Valverde 2003), and weeds

(Meksawat and Pornprom 2010).

In South and Southeast Asia, water scarcity reduces

grain yield on 23 million ha of area planted to rainfed rice

(Huke and Huke 1997). By 2025, 22 million ha of rice may

experience severe water scarcity (Tuong and Bouman

2003). The major rice establishment method in Asia is

manual transplanting of seedlings, which is more laborious

and requires more water (Chauhan 2012). Because of labor

and water scarcity, dry-seeded rice (DSR) is increasing

among farmers in South and Southeast Asian countries.

DSR is a resource-conserving technology relative to

transplanted rice, except that it is prone to heavy weed

infestation (Chauhan 2012). Manual hand weeding is very

expensive, time-consuming, and sometimes not feasible,

especially for weeds having a fibrous root system (e.g., R.

cochinchinensis). Manual removal of this weed is very

difficult because of the fiberglass-like hairs on its stems,

which can penetrate the skin and cause severe irritation

(Chauhan 2013). Therefore, herbicide control is becoming

more popular. In other parts of the world, because of the

non-judicious use of herbicides, R. cochinchinensis has

developed a resistance to nicosulfuron and other acetolac-

tate synthase (ALS)-inhibitor herbicides (Valverde 2007).

Because of concerns related to herbicide usage, there is a

need to explore other weed management practices such as

the use of high planting densities, optimum N fertilization,

competitive varieties, and narrow row spacing to achieve

sustainable weed control (Chauhan 2012). A better under-

standing of weed biology and ecology is important for

developing cultural weed management strategies, which

could increase the competitive ability of crops over weeds

and delay the buildup of herbicide resistance in weeds

(Mohler 2001; Blackshaw and Brandt 2008). The use of

weed-competitive rice cultivars will slow down the

development of resistance in weeds by suppressing weeds

and reducing herbicide loads on agro-ecosystems (Gibson

et al. 2001; Chauhan and Johnson 2010a). Integrated weed

management (IWM) is not used in direct-seeded rice

because of limited and inadequate knowledge of the basic

biology and ecology of problematic weeds (Chauhan and

Johnson 2010a).

Immediately after germination, crop seedlings are

usually larger than weed seedlings. This size-asymmetric

competition in the crop–weed interaction would increase

crop growth at the expense of the weeds. The benefit of

seedling size in crop–weed competition increases with an

increase in crop density (Schwinning and Weiner 1998;

Weiner et al. 2001). Several researchers suggested having

a high planting density in direct-seeded rice to suppress

weeds and to achieve high rice yield (Chauhan and

Johnson 2010a; Chauhan 2012; Chauhan and Abugho

2013). A high planting density of 160 kg ha-1 provides

good rice yield and minimizes losses caused by weeds

(Phuong et al. 2005). At high planting densities, however,

a crop may need more nutrients to achieve high grain

yield. What the effect of N fertilizer will be on weed-crop

competitive interaction has not yet been studied in Asia.

Crop–weed interference can be affected by fertilizer

management and planting densities and N is one of the

crucial components of crop–weed competitive interaction

(Liebman and Janke 1990). Some weeds consume high

quantities of N, reduce crop N uptake, and suppress the

growth, biomass, and yield of rice (Ampong-Nyarko and

De Datta 1993). Other researchers claim that high doses

of N fertilizer enhance crop growth and yield compared

with weeds, whereas weed response to added N decreases

(Evans et al. 2003). The N effect on crop–weed compe-

tition may be species-specific (Blackshaw et al. 2003).

Low N-response weed species are not affected by

increased N rates, whereas high N-response weed species

respond positively to high N rates (Blackshaw and Brandt

2008).

N rates could prejudice the effect of crop density on

weed suppression. The effect of high crop density could be

more prominent at low N rates because weeds grow slowly

in that condition (Blackshaw et al. 2003). On the other

hand, high N rates may increase crop growth, but may

suppress weeds when sown at a higher density. It is

important to know the weed response to increased N rates

in order to improve strategies that decrease N availability

to weeds (Liebman and Gallandt 1997). Fertilization is

more important in the early stages because optimally fer-

tilized crops become more competitive with weeds than

poorly fertilized crops (Jordan et al. 1987).

J Pest Sci

123

Weed control practices that enhance the competitive

ability of crops over weeds should be a fundamental part of

an IWM strategy. However, before improving IWM strat-

egies that rely on crop competitiveness, there is a need to

test the hypotheses that increased planting density sup-

presses the growth of R. cochinchinensis and that increased

N rates increase the growth of rice and make the crop more

competitive than weeds. To test these hypotheses, a study

was conducted to determine the effect of the interaction of

N rates and rice planting densities on the growth parame-

ters of rice and R. cochinchinensis, N-use efficiency, and

rice–weed competitiveness.

Materials and methods

Seeds of R. cochinchinensis were collected during 2011

from upland rice fields around Los Banos, Philippines. Rice

variety use in this study is NSICRc222 (IR154). The study

was conducted two times from 18 April to 16 June 2012

(first experiment) and from 4 May to 29 June 2012 (second

experiment) in a screenhouse at the International Rice

Research Institute (IRRI), Los Banos, Philippines. The

screenhouse was made of a large iron-steel frame covered

with a 2-mm steel mesh on all sides to maintain environ-

mental conditions similar to those of field conditions. The

study was conducted by growing weed and rice plants in

plastic pots 25 cm in diameter and 30 cm in height, with

holes at the bottom and filled with sieved soil (8.3 kg

pot-1). The soil texture was 22 % sand, 38 % silt, and

40 % clay. It had a pH of 6.0, 0.99 % organic carbon,

0.107 % N, 0.121 % Kjeldahl N, 43 mg kg-1 of available

P2O5, and 1.26 meq 100 g-1 soil of available K.

The 16 treatment combinations had two factors: four N

rates (0, 50, 100, and 150 kg ha-1) and four planting

densities [0 (0 plants pot-1), 100 (5 plants pot-1), 200 (10

plants pot-1), and 400 plants m-2 (20 plants pot-1)]. The

experiment was laid out in a 4 9 4 factorial randomized

complete block design in three replications. Phosphorus

(P) and potash (K) fertilizers were applied basally in the

form of solophos (20 % P2O5) and muriate of potash (60 %

K2O) at 40 and 40 kg ha-1, respectively. N was applied in

the form of urea (46 % N) in two equal splits at 20 and

40 DAS. Two to three weed seeds were sown at the center

of each pot and then covered with a thin layer of soil. For 5

rice plants per pot (100 plants m-2), the rice seeds were

planted around the weed seeds at a distance of 5 cm in a

single circle. In the case of 10 and 20 rice plants per pot,

these were planted in two circles. The placement of the first

circle was the same with the treatment described above for

5 rice plants per pot, and the distance of the second circle

was 2.5 cm from the first circle. In each circle, rice seeds

were planted at equal distances from each other. At 7 DAS,

thinning was done to maintain the required rice and weed

densities per pot.

Weeds other than R. cochinchinensis were removed. The

pots were placed at a distance of 30 cm from each other to

avoid a mutual shading effect. Fortnightly, the pots were

rotated to new positions to reduce experimental errors. Pots

were irrigated two to three times a day with a sprinkler

system. Plant height, number of leaves per plant, number of

tillers per plant, and SPAD values (Minolta SPAD meter-

502) were measured at 14, 28, 42, and 56 DAS. The height

of weed and rice plants was measured from the ground to

the tip of the longest leaf. SPAD values were measured for

both rice and weed plants to assess their respective N

uptakes. Three readings were recorded per pot for both rice

and weed plants, measuring from different parts of the

topmost fully expanded leaf using a Minolta SPAD meter-

502. The chlorophyll meter (SPAD meter) is a tool that

measures the greenness, relative chlorophyll, or N content

of leaves.

Rice and weed plants were harvested from the ground

level at weed maturity, at 56 DAS. After detaching leaves

for leaf area measurements, shoots were separated into

stems and inflorescence. Leaf area was measured using a

leaf area meter (LI-COR model LI-3100, USA). After

measuring the leaf area, stems, leaves, and inflorescences

were oven-dried in separate paper bags at 70 �C for 72 h.

From each pot, roots were removed and the soil was

washed through a steel strainer. Weed and rice roots were

separated and oven-dried at 70 �C for 72 h. After oven-

drying, stem, leaf, inflorescence, and root biomass were

measured.

The following parameters were calculated: root-to-shoot

weight ratio (RSWR), specific leaf area (SLA), leaf weight

ratio (LWR), and leaf area ratio (LAR). The LAR is the

ratio of leaf area to total plant biomass that indicates how

photosynthates are being partitioned within the plant parts:

Leaf area ratio LARð Þ ¼ Leaf area cm2ð ÞTotal plant biomass gð Þ :

LAR is a multiple of two components, that is,

LAR ¼ LWR� SLA,

Leaf weight ratio LWRð Þ ¼ Leaf biomass gð ÞTotal plant biomass gð Þ ;

Specific leaf area SLAð Þ ¼ Leaf area cm3ð ÞTotal leaf biomass gð Þ ;

Specific stem length SSLð Þ ¼ Stem length cmð ÞStem weight gð Þ :

Data from both experiments (first and second) were

subjected to ANOVA (GenStat 2005) for combined ana-

lysis. The ANOVA results indicated that there were no

J Pest Sci

123

significant interactions between the experiments and

treatments. Therefore, data from the repeated experiments

were combined before being subjected to ANOVA. Data

variance was visually inspected by plotting residuals to

confirm homogeneity of variance before statistical analysis.

The data underwent regression analysis. Treatment means

were separated using standard error of difference (SED) at

the 5 % level of significance.

Data on plant height, tiller number, and leaf number

were analyzed using a three-parameter sigmoid model:

Y ¼ a= 1 þ e½� x� d50ð Þ=b�n o

;

where Y is the estimated plant height, tiller number, or leaf

number at time x; a is the maximum plant height, tiller

number, or leaf number; and d50 is the time (d) required to

reach 50 % of maximum plant height, tiller number, or leaf

number. Parameter b provides an indication of the rate of

plant height, tiller number, or leaf number.

An exponential decay model with two parameters,

y ¼ a � e�bx;

was fitted to the leaf and inflorescence biomass, where y is

the estimated leaf or inflorescence biomass, a is the max-

imum of the parameter, and b is the slope.

An exponential decay model with three parameters,

y ¼ y0 þ að Þ � e�bx;

was fitted to leaf area, stem, and whole-plant biomass

obtained at different planting densities and N rates, where

y is the estimated leaf area, stem, or whole-plant biomass as

a function of rice planting density and N rates or DAS (x);

a is the minimum parameter at the highest rice density of

400 plants m-2 and y0 ? a is the maximum parameter at

the lowest rice density (0 plants m-2); and b is the slope. R2

values were used to determine the fitness of the selected

model. Parameter estimates of each model were compared

using their standard error.

Results

Plant height

The plant height of R. cochinchinensis at different crop

densities increased in a sigmoid manner (Fig. 1a; Table 1).

Height was affected by the increased planting density from

100 to 400 plants m-2. The fitted sigmoid model predicted

the maximum height of 260 cm (Fig. 1a) of weed plants

when they were grown alone, whereas this was only

100 cm at a density of 400 plants m-2. The rate of height

increase in R. cochinchinensis was 400 %, whereas it was

only 123 % in rice. The height of R. cochinchinensis

decreased by 27, 41, and 49 % at crop densities of 100,

200, and 400 plants m-2, respectively. R. cochinchinensis

reached 50 % of the maximum height at 42 DAS, when it

was grown by itself. The days to reach 50 % of the max-

imum height decreased with an increase in planting den-

sities, that is, 35, 29, and 25 DAS at densities of 100, 200,

and 400 plants m-2.

The height of R. cochinchinensis was also affected by

varying N rates. At 56 DAS, compared with 14 DAS, the

rate of increase in height for the weeds was 408, 581, 640,

and 584 %, whereas in rice it was only 68, 110, 139, and

146 % when fertilized with 0, 50, 100, and 150 kg N ha-1,

respectively (Fig. 1b; Table 1). In total, weed height was

210, 180, and 157 % higher than that of rice plants at crop

densities of 100, 200, and 400 plants m-2, respectively,

whereas weed height was 174, 210, 221, and 233 % higher

than that of rice plants at 0, 50, 100, and 150 kg N ha-1,

respectively (Fig. 1a; Table 1).

Number of tillers and leaves per plant

A sigmoid growth-response curve was observed in R. co-

chinchinensis for the number of tillers and leaves per plant

(Fig. 1c–f). R. cochinchinensis produced an average of 5

tillers per plant when grown alone. This decreased to 2, 1.5,

and 1 tiller plant-1 when grown with rice densities of 100,

200, and 400 plants m-2, respectively. Rice tillers

increased to 500, 680, and 820 m-2 at planting densities of

100, 200, and 400 plants m-2 (Table 1). Regression ana-

lysis showed that, with the increase in rice tillers, there was

an exponential (t = 92.8�e-0.002x, P = 0.001, R2 = 0.99)

decline in the tiller number of R. cochinchinensis, with a

slope of 0.002 (Table 2). Tiller number for R. cochin-

chinensis increased by 44, 71, and 129 % when applied

with 50, 100, and 150 kg N ha-1, respectively (Fig. 1).

The fitted sigmoid model predicted the maximum

number of leaves per plant as 64 when weed plants were

grown alone, whereas only 9 leaves plant-1 occurred at a

crop density of 400 plants m-2. At 56 DAS, rice density of

100, 200, and 400 plants m-2 reduced leaf number by 68,

83, and 84 %, respectively (Fig. 1e). The number of leaves

increased significantly with increased N rates. Averaged

over the three planting densities, the increased N rate (50,

100, and 150 kg N ha-1) increased leaf number by 122,

225, and 420 %, respectively, compared with 0 kg N ha-1

(Fig. 1f; Table 1).

Leaf area

Increased rice planting densities significantly reduced the

leaf area of R. cochinchinensis. An exponential decay

model was fitted to leaf area at different N rates and

planting densities (Fig. 2). Compared to the weed leaf area

J Pest Sci

123

without rice competition, densities of 400 plants m-2

reduced leaf area by 77, 82, 87, and 84 % at N rates of 0,

50, 100, and 150 kg ha-1, respectively (Fig. 2). Significant

increases in leaf area were observed with increased N

application. Leaf area increased by 169, 287, and 452 %

with the application of 50, 100, and 150 kg N ha-1,

respectively, compared with 0 kg N ha-1.

Leaf stem and inflorescence biomass

An exponential model was fitted to the leaf stem and

inflorescence biomass of R. cochinchinensis at different

rice planting densities and N rates. At each rice planting

density, leaf biomass was always lowest at 0 kg N ha-1

compared with added N treatments. The application of

150 kg N ha-1 produced maximum leaf biomass. Rot-

tboellia cochinchinensis leaf biomass increased by 20, 43,

and 52 % with the application of 50, 100, and

150 kg N ha-1, respectively (Fig. 3a; Table 3). Increased

rice planting densities reduced leaf biomass by 26, 64, and

90 % at rice densities of 100, 200, and 400 plants m-2,

respectively.

Compared to the stem biomass of weeds grown without

rice competition, densities of 400 rice plants m-2 reduced

stem biomass of R. cochinchinensis by 67, 78, 70, and

73 % at N rates of 0, 50, 100, and 150 kg ha-1, respec-

tively (Fig. 3b). Stem biomass increased by 159, 218, and

337 % with the application of 50, 100, and 150 kg N ha-1,

respectively, compared with 0 kg N ha-1 (Table 3).

Similar to other aboveground plant parts, increased

planting density significantly reduced R. cochinchinensis

inflorescence biomass, whereas this increased significantly

with an increase in N rates (Fig. 3c). The average reduction

in inflorescence biomass was 60, 76, and 84 % at rice

densities of 100, 200, and 400 plants m-2, respectively,

compared with the inflorescence biomass of weeds grown

without rice competition. There was an increase of 89, 117,

and 138 % in inflorescence biomass at N rates of 50, 100,

and 150 kg ha-1, respectively, compared with

0 kg N ha-1 (Table 3).

Days after sowing

Lea

ves

(no

. pla

nt-1

)

0

10

20

30

40

50

60

(a)

Pla

nt

hei

gh

t (c

m)

50

100

150

200RC : PD 0

RC : PD 100

RC : PD 200

RC : PD 400

R : PD 100

R : PD 200

R : PD 400

Till

ers

(no

. pla

nt-1

)

1

2

3

4

5

RC : N 0 RC : N 50

RC : N 100

RC : N 150

R : N 0

R : N 50

R : N 100

R : N 150

RC : PD 0

RC : PD 100RC : PD 200

RC : PD 400

RC : N 0

RC : N 50 RC : N 100

RC : N 150

Days after sowing

10 20 30 40 50 10 20 30 40 50

(f)(e)

(d)(c)

(b)(a)Fig. 1 Plant height of both rice

and weed (a, b), number of

tillers (c, d), and number of

leaves (e, f) per plant of

Rottboellia cochinchinensis

(RC) with different rice planting

densities (PD), that is, 0, 100,

200, and 400 plants m-2, at

different nitrogen rates (0, 50,

100, and 150 kg ha-1). Vertical

bars represent standard error of

means. Lines represent a

sigmoid model fitted to the plant

height of both rice and weed,

and tiller and leaf number

plant-1 of Rottboellia

cochinchinensis data

J Pest Sci

123

Total plant biomass (above- and belowground)

Increased rice densities (100–400 plants m-2) raised rice

biomass from 600 to 800 g m-2 and increased N rates

raised biomass from 300 to 1,000 g m-2 (Table 3), which

suppressed the growth of R. cochinchinensis (Fig. 3d).

Increased rice density from 100 to 400 plants m-2 signif-

icantly (P \ 0.001) reduced the total biomass of R. co-

chinchinensis, whereas increased N rates significantly

(P \ 0.001) raised the total biomass of R. cochinchinensis.

The reduction in the biomass of the weeds was 54, 68, and

74 % at densities of 100, 200, and 400 plants m-2,

respectively, compared with 0 plants m-2. N application at

50, 100, and 150 kg ha-1 increased weed biomass by 131,

256, and 360 %, respectively, compared with 0 kg N ha-1

(Table 3). Regression analysis showed that the relation

(b = 1004�e-0.002x, P = 0.009, R2 = 0.98) of crop and R.

cochinchinensis biomass was inversely related, with a

slope of -0.002.

SPAD values

The interaction between N rates and planting densities for

SPAD values was non-significant for both weed and rice

plants. Increased rice densities decreased (P \ 0.001) the

SPAD values of weed and rice plants, whereas the SPAD

values increased (P \ 0.001) with an increase in N rates

for both rice and R. cochinchinensis plants. The SPAD

values were maximum ([40 SPAD unit for weed plants) at

42 DAS, 1 week after the application of the second split of

N, compared with other observation dates. Irrespective of

observation dates, the SPAD values of R. cochinchinensis

were higher than those of rice at all planting densities and

N rates (Table 4).

Biomass partitioning

Leaf weight ratio

High rice planting density increased (P \ 0.001) LWR by

86, 95, and 89 % at rice densities of 100, 200, and 400

plants m-2, respectively, in comparison with the LWR of

weed plants grown without competition. N at 50, 100, and

150 kg ha-1 reduced LWR by 34, 43, and 50 %, respec-

tively, compared with 0 kg N ha-1 (Fig. 4a, b).

Root-to-shoot weight ratio

The interaction between planting density and N rates was

significant for RSWR. Planting densities (P \ 0.001) and

N rates had a significant decreasing effect on RSWR

(Fig. 4c, d). RSWR was maximum (0.15) when weed

plants were grown without competition, but declined to

0.06 (63 %), 0.04 (73 %), and 0.03 (77 %) at densities of

Table 1 Parameter estimates (a is the maximum plant height, tiller

number, and leaf number; d50 is the time (d) required to reach 50 %

of the maximum parameter; and b is the slope) of a three-parameter

sigmoid model, Y ¼ a= 1þ e � x�d50ð Þ=b½ �� �, fitted to the plant height,

tiller number, and leaf number of Rottboellia cochinchinensis when

grown alone or in competition with different rice planting densities

(PD) (0, 100, 200, and 400 plants m-2) and N rates

PD (plants

m-2)

Plant height (cm) Tillers (no. plant-1) Leaves (no. plant-1)

a b d50 R2 a b d50 R2 A b d50 R2

0 260.53

(63.40)

13.07

(3.55)

41.68

(7.76)

0.99 4.71

(0.08)

6.74

(0.51)

20.61

(0.59)

0.99 63.99

(2.74)

10.19

(0.75)

37.13

(1.24)

0.99

100 168.95

(47.00)

12.75

(5.52)

35.31

(9.34)

0.94 2.04

(0.04)

0.66

(1599)

13.92

(3.00)

0.99 21.33

(8.05)

16.65

(9.47)

32.25

(15.22)

0.97

200 121.94

(9.67)

10.04

(2.03)

28.84

(2.53)

0.99 1.46

(0.001)

5.12

(0.11)

10.02

(0.09)

0.99 8.84

(1.05)

8.91

(6.74)

13.30

(4.44)

0.92

400 100.21

(12.01)

9.75

(3.54)

25.39

(3.93)

0.98 1.17

(0.04)

0.69

(36)

12.77

(649)

0.86 Model could not fit

N (kg ha-1)

0 96.73

(18.59)

11.56

(5.08)

28.74

(6.45)

0.98 1.42

(0.002)

5.75

(0.19)

8.15

(0.19)

0.99 7.91

(0.09)

7.05

(0.77)

11.81

(0.48)

0.99

50 161.10

(48.09)

13.10

(5.82)

35.83

(10.14)

0.98 2.03

(0.019)

5.36

(0.59)

12.81

(0.30)

0.99 18.69

(3.38)

12.21

(5.51)

25.93

(6.27)

0.97

100 187.73

(39.69)

12.27

(4.08)

35.74

(6.91)

0.99 2.44

(0.028)

6.74

(0.46)

16.01

(0.38)

0.99 36.65

(7.54)

16.02

(3.22)

42.18

(7.60)

0.99

150 192.77

(21.05)

11.38

(2.27)

33.84

(3.49)

0.99 3.34

(0.105)

6.05

(1.03)

17.80

(1.07)

0.99 58.30

(4.95)

13.42

(1.11)

44.01

(2.68)

0.99

Values in parentheses represent standard error of the mean

J Pest Sci

123

100, 200, and 400 rice plants m-2, respectively. The

RSWR of weed plants was 0.09, in which no N was

applied; this ratio decreased to 0.06 (30 %), 0.06 (30 %),

and 0.07 (24 %) at N rates of 50, 100, and 150 kg ha-1,

respectively.

Specific leaf area

SLA of R. cochinchinensis decreased (P \ 0.001) with

increased rice density and N rate. SLA decreased by 53, 44,

and 51 % at rice densities of 100, 200, and 400 plants m-2,

respectively. SLA decreased by 38, 53, and 49 % at 50, 100,

and 150 kg N ha-1, respectively, compared with the SLA

of the plants in which no N was applied (Fig. 4e, f).

Specific stem length

High rice planting density increased specific stem length

(SSL) by 30, 99, and 106 % at rice densities of 100, 200,

and 400 plants m-2, respectively, in comparison with the

SSL (12.39 cm g-1) of weed plants grown without com-

petition (Fig. 4a). N at 50, 100, and 150 kg ha-1 decreased

SSL by 54, 36, and 46 %, respectively, compared with SSL

(27.8 cm g-1) at 0 kg N ha-1 (Fig. 4g, h).

Discussion

The height of R. cochinchinensis was affected by rice

planting density and N rate. N application had a more

positive effect on weed plant height (400 %) than on rice

(123 %). Other researchers reported similar findings that

weed species with high growth rates were more responsive

to increased rates of N (Andersson and Lundegardh 1999).

The height of R. cochinchinensis decreased with increased

crop planting densities. Earlier researchers found similar

results for Cyperus iria and Echinochloa crus-galli (P.)

Beauv, in which their height decreased with increased rice

density; however, these weeds were taller than rice

(Chauhan and Johnson 2010a, b). In another study, Cor-

taderia selloana (Schultes) A. and G. plants grown at high

N rates were taller than plants grown at ambient N rates

(Vourlitis and Kroon 2013). Our results are in line with

earlier findings on E. crus-galli, in which weed height was

affected by the interaction of N and crop density (Chauhan

and Abugho 2013). The results depicted that the weed was

always taller than rice, irrespective of planting density and

N rate, mainly by overcoming the effects of shade by

capturing sunlight for photosynthesis, which is necessary

for its survival. Earlier researchers reported similar results

(Gibson et al. 2004; Marenco and Reis 1998). R. cochin-

chinensis was always taller than rice because it has shade-Ta

ble

2R

ice

bio

mas

s(s

ho

ot,

roo

t,an

dw

ho

lep

lan

t),

roo

t-to

-sh

oo

tw

eig

ht

rati

o(R

SW

R),

and

rice

till

ers

atd

iffe

ren

tp

lan

tin

gd

ensi

ties

(PD

)an

dn

itro

gen

(N)

rate

s

PD

(pla

nts

m-

2)

Ric

eb

iom

ass

(gp

ot-

1)

RS

WR

(gg

-1)

Ric

eti

ller

sp

ot-

1N

(kg

ha-

1)

Ric

eb

iom

ass

(gp

ot-

1)

RS

WR

(gg

-1)

Ric

eti

ller

sp

ot-

1

Sh

oo

tR

oo

tW

ho

lep

lan

tS

ho

ot

Ro

ot

Wh

ole

pla

nt

0–

––

––

09

.57

5.3

61

4.9

20

.57

22

.61

10

01

9.4

41

0.4

52

9.8

80

.56

25

.92

50

19

.64

10

.95

30

.59

0.5

62

7.8

3

20

02

2.7

89

.71

32

.50

0.4

53

4.2

51

00

28

.48

13

.67

42

.15

0.4

93

7.5

0

40

02

6.2

81

3.9

44

0.2

20

.55

40

.71

15

03

3.6

51

5.4

94

9.1

40

.48

46

.56

S.E

.D0

.97

0.7

61

.36

0.0

31

.36

S.E

.D1

.12

0.8

81

.56

90

.04

1.5

8

P\

0.0

01

\0

.00

1\

0.0

01

0.0

02

\0

.00

1P

\0

.00

1\

0.0

01

\0

.00

10

.03

\0

.00

1

J Pest Sci

123

avoiding characteristics and a C4 pathway of photosyn-

thesis. It has greater potential for growth (height) than rice

(C3) in a tropical environment (Sage 2000).

Leaf area and number of leaves and tillers per plant of R.

cochinchinensis decreased significantly with increased rice

density (0–400 plants m-2) and increased with increased N

rates. Reason of this may be that N is the component of

chlorophyll content. Higher N means higher chlorophyll and

photosynthesis, which become the cause of more biomass

production and allocation. Similar results were reported for

C. iria and E. crus-galli, in which leaf and tiller numbers

decreased with an increase in crop density (Chauhan and

Johnson 2010b). Our results are also supported by another

study on E. crus-galli, in which leaf production decreased

with increased rice density and increased with increased N

rates (Chauhan and Abugho 2013). In an earlier study on

Echinochloa phyllopogon, number of tillers and leaf area

increased with an increase in N from 0 to 224 kg ha-1

(Gibson et al. 2004). In another study, C. selloana plants

grown at high N rates produced more tillers than with the

ambient N rate (Vourlitis and Kroon 2013).

With increased rice planting densities, there was a

decrease in the biomass of aboveground (stem, leaves, and

inflorescence) and belowground (root) plant parts of R.

cochinchinensis. At all rice planting densities, N enrich-

ment increased the biomass of all plant parts. Andersson

and Lundegardh (1999) reported similar results. In another

study, E. phyllopogon biomass decreased under shaded

conditions, whereas it increased with an increase in N rates

from 0 to 224 kg ha-1 (Gibson et al. 2004). Our results are

also consistent with an earlier study on E. crus-galli, in

which aboveground biomass (85 %) and seed production

(85 %) decreased significantly with increased rice density

(16 plants pot-1) and increased with increased N rates

(Chauhan and Abugho 2013). Earlier researchers reported

similar results that inflorescence biomass decreased by

67 % in C. iria and by 87 % in E. crus-galli when grown

with rice interference instead of without interference

(Chauhan and Johnson 2010b).

In our study, there was a linear negative relationship

between rice and R. cochinchinensis biomass. Similar

results were reported for other crops in competition with R.

cochinchinensis; for example, maize intercropped with

velvet bean at high density (50,000 or 80,000 plants ha-1)

reduced R. cochinchinensis biomass by 75–95 % (Valverde

et al. 1995). In our study, 11 % of the total weed biomass

was allocated to the inflorescence at high competition (400

rice plants m-2), suggesting that R. cochinchinensis can

produce viable seeds under high interference, which

Planting density (plants m-2)

0 100 200 300 400

Lea

f ar

ea (

cm2 p

lan

t-1)

0

500

1000

1500

2000

2500

3000

N 100 kg ha-1, [ y = 218 (+48), a = 1473 (+64), b = 0.012 (+0.002)]

N 150 kg ha-1, [y = 398 (+38), a = 2015 (+61), b = 0.021 (+0.003)]

N 0 kg ha-1, [y = 102 (+5), a = 335 (+8), b = 0.020 (+0.002)]

N 50 kg ha-1, [y = 202 (+24), a = 975 (+41), b = 0.037 (+0.017)]

Fig. 2 Leaf area of Rottboellia cochinchinensis at different rice

planting densities and nitrogen rates. Lines represent an exponential

model fitted to the leaf area data. Vertical bars represent standard

error of means

Table 3 Parameter estimates (a is the intercept and b is the slope) of

a three-parameter exponential growth decay model,

y = (y0 ? a)e-bx, fitted to the stem and whole-plant biomass data,

where y is the stem and whole-plant biomass at different rice planting

densities (plants m-2), y0 is the minimum value at rice planting

density of 400 plants m-2, and (y0 ? a) is the maximum value at rice

planting density of 0 plants m-2

N

(kg ha-1)

Rottboellia cochinchinensis biomass (g plant-1)

Leaf Stem Inflorescence Whole plant

a b R2 y0 a b R2 a b R2 y0 a b R2

0 11.30

(1.58)

0.006

(0.002)

0.95 2.78

(2.5)

5.68

(3.2)

0.01

(0.002)

0.79 4.9

(0.2)

0.02

(0.004)

0.99 4.27

(1.75)

13.97

(2.49)

0.014

(0.007)

0.97

50 12.11

(1.42)

0.005

(0.001)

0.93 4.87

(2.2)

17.00

(3.0)

0.013

(0.006)

0.97 9.2

(0.4)

0.02

(0.002)

0.99 7.05

(0.69)

39.19

(0.94)

0.013

(0.001)

0.99

100 14.40

(0.88)

0.005

(0.001)

0.98 8.18

(0.6)

18.75

(0.8)

0.013

(0.002)

0.99 10.5

(0.3)

0.01

(0.001)

0.99 14.81

(1.83)

44.26

(2.31)

0.009

(0.001)

0.99

150 16.07

(0.58)

0.005

(0.001)

0.99 10.12

(0.4)

26.87

(0.6)

0.018

(0.002)

0.99 11.6

(1.6)

0.01

(0.001)

0.82 25.69

(0.06)

50.68

(0.09)

0.018

(0.001)

0.99

A two-parameter exponential growth decay model y = a�e-bx is fitted to the leaf and inflorescence biomass of Rottboellia cochinchinensis, where

y is the predicted biomass and a is the maximum leaf and inflorescence biomass. Values in parentheses represent standard error of the mean

J Pest Sci

123

ensures the survival of this weed for the next generations.

This trait makes R. cochinchinensis opportunistic to prop-

agate under the inconsistent situations prevailing in rice

fields (Bakar and Nabi 2003).

Increased rice densities decreased (P \ 0.001) SPAD

values, whereas increased N rates increased the SPAD

values of both rice and weed plants. The SPAD values of R.

cochinchinensis were higher than those of rice plants,

Ste

m b

iom

ass

(g p

lan

t-1)

0

10

20

30

40(b)

Lea

f b

iom

ass

(g p

lan

t-1)

02468

1012141618 (a) N 0 kg ha-1

N 50 kg ha-1

N 100 kg ha-1

N 150 kg ha-1

Planting density (plants m-2)T

ota

l pla

nt

bio

mas

s(g

pla

nt-1

)

0

20

40

60

80(d)

Planting density (plants m-2)

0 100 200 300 4000 100 200 300 400

Infl

ore

scen

ce b

iom

ass

(g p

lan

t-1)

0

2

4

6

8

10

12

14 (c)

Fig. 3 Leaf biomass (a), stem biomass (b), inflorescence biomass (c),

and total plant biomass (d) of Rottboellia cochinchinensis at different

rice planting densities and nitrogen rates. Lines represent an

exponential model fitted to the leaf, stem, inflorescence, and total

plant biomass data. The vertical bars represent standard error of

means

Table 4 SPAD values at 14, 28, 42, and 56 days after sowing (DAS) for both rice and weed at different rice planting densities (PD) and nitrogen

(N) rates

PD (plants m-2) SPAD values at different days after sowing

28 DAS 42 DAS 56 DAS

Weed Rice Weed Rice Weed Rice

0 39.28 NA 40.17 NA 35.77 NA

100 36.13 32.89 33.62 31.60 30.31 28.63

200 32.79 30.97 30.54 29.55 29.05 28.34

400 32.51 29.62 29.61 28.92 27.38 27.72

S.E.D 0.844 0.405 0.644 0.277 0.856 0.457

P \0.001 \0.001 \0.001 \0.001 \0.001 0.357

N (kg ha-1)

0 28.46 25.82 23.28 23.15 24.09 22.95

50 35.50 31.63 32.87 29.53 29.40 26.97

100 38.03 33.13 37.94 32.75 33.47 30.49

150 38.72 34.06 40.84 34.66 35.55 32.52

S.E.D 0.844 0.467 0.644 0.320 0.856 0.527

P \0.001 \0.001 \0.001 \0.001 \0.001 \0.001

NA not available

J Pest Sci

123

suggesting that the weed had a higher capacity for the

uptake of N than rice plants, which made the weed more

competitive to interfere with the growth of rice. Similar

findings were reported in an earlier study, in which NPK

uptake by Ischaemum rugosum Salisb. was higher than that

of rice and the weed was a stronger competitor than rice for

nutrients (Singh and Kolar 1993).

The results revealed that, with an increase in N, carbon

allocation to all aboveground plant parts of the weed

increased the growth of the whole shoot, which, in turn,

decreased LWR, SLA, SSL, and RSWR. Our results are in

line with earlier findings, in which increased N increased

the biomass allocation to shoots relative to roots (Funk

2008). Reason could be that, under high N availability,

plant could not need more and deeper root for N uptake,

that’s why low biomass was allocated to root compared to

the shoot. Reynolds and Antonio (1996) made 77 studies

representing 129 species and found that RSWR decreased

with increased N availability. Bonifas et al. (2005) reported

that RSWR decreased for both Abutilon theophrasti Medik.

(velvetleaf) and maize as N application increased. In

another study, RSWR of C. selloana decreased with

increased N rates (Vourlitis and Kroon 2013). With an

increase in N, there was more growth of weed plants,

which reduced the SLA of R. cochinchinensis. High N rate

produced and allocated more biomass to leaves per unit

Lea

f w

eig

ht

rati

o (

g g

-1)

0.2

0.3

0.4

0.5(a) (b)

Ro

ot

sho

ot

wei

gh

t ra

tio

(g

g-1

)

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

Sp

ecif

ic le

af a

rea

(cm

2 g-1

)

60

80

100

120

140

(c)

(e) (f)

(d)

Nitrogen rate (kg ha-1)

(h)

Planting density (plants m-2)

0 50 100 1500 100 200 300 400

Sp

ecif

ic s

tem

len

gth

(cm

g-1

)

10

15

20

25

30 (g)

Fig. 4 Leaf weight ratio (a, b),

root-to-shoot weight ratio (c, d),

specific leaf area (e, f), and

specific stem length (g, h) of

Rottboellia cochinchinensis at

different rice planting densities

and nitrogen rates. The vertical

bars represent standard error of

means

J Pest Sci

123

area, which may be the reason for lower SLA. In another

study on C. selloana, Vourlitis and Kroon (2013) found

that SLA decreased with an increase in added N. Our

results contradict those reported for some grasses, in which

N had no effect on SLA (Knops and Reinhart 2000). This

trait made R. cochinchinensis a species of poor-resource

habitats (Knops and Reinhart 2000).

Our study showed that increased planting density

increased (P \ 0.001) LWR and SSL, and decreased

(P \ 0.001) RSWR. In contrast, increased N rates signifi-

cantly reduced all these parameters (LWR, SLA, SSL, and

RSWR). Similar findings were reported earlier by Gibson

et al. (2004) for E. phyllopogon, in which SLA and LAR

increased and RSWR decreased with a decrease in light.

Similar findings were reported in an earlier study on C. iria

and E. crus-galli (Chauhan and Johnson 2010b), in which

LWR and SSL increased with an increase in planting

density. These results mean that, under competition, R.

cochinchinensis had a phenotypic plasticity to allocate

more photosynthate to aboveground plant parts than to

belowground parts, and therefore, SSL and LWR increased

and RSWR decreased. Plants with the shade-avoiding

syndrome, such as R. cochinchinensis, show phenotypic

plasticity characteristics. The plants will be able to increase

SSL to adapt to the shade when there is a reduction in

sunlight because of high rice planting density. Higher SSL

under shady conditions demonstrates that this weed species

has the plasticity (ability) to increase shoot length per

allocated biomass for putting its leaves on the top of the

rice canopy to intercept light for photosynthesis, which is

crucial for plant life.

This phenotypic plasticity in plants enables them to alter

their morphology to increase the use of the most growth-

limiting resources (Gibson et al. 2001; Chauhan and

Johnson 2010b). This strategy may help R. cochinchinensis

to survive and avoid shading (imposed by crop interfer-

ence) and produce enough photosynthates to boost its

height to keep its leaves on the top of the rice canopy

(Caton et al. 1997). The ability of weeds to compete with

rice not only for resources but also to alter their mor-

phology by increasing LWR and SSL, and by decreasing

RSWR through biomass partitioning, makes the weeds

more competitive with the crop (Gibson and Fischer 2001;

Gibson et al. 2001) even when it germinates later than rice

in the field (Marenco and Reis 1998; Vourlitis and Kroon

2013). The growth and seed production of R. cochinchin-

ensis was reduced by increased rice planting density, which

supports the recommendation for adequate crop planting

density and agronomic practices that encourage rapid

canopy closure to suppress weeds (Chauhan and Johnson

2010b, Chauhan 2013).

Conclusions

In conclusion, R. cochinchinensis is always taller than rice

at all planting densities, irrespective of N application.

Rottboellia cochinchinensis has the ability to survive and

produce seeds even at high crop densities, suggesting that

management strategies that depend on shade due to crop

interference may not provide complete control of this

weed. Although high planting density of rice can decrease

the biomass of R. cochinchinensis considerably, later, it can

be easily controlled through herbicide applications or

manual weeding. Multiple control practices, such as greater

competition by the crop for light and nutrients, and N

management, along with other weed management prac-

tices, are considered to be essential to achieve maximum

control of this weed.

Acknowledgments The authors would like to thank Bill Hardy and

Grace Canas for providing comments on the manuscript.

References

Ampong-Nyarko K, De Datta SK (1993) Effects of light and nitrogen

and their interaction on the dynamics of rice-weed competition.

Weed Res 33:1–8

Andersson, Lundegardh B (1999) Growth of field horsetail under low

light and low nitrogen conditions. Weed Sci 47:41–46

Bakar BH, Nabi LNA (2003) Seed germination, seedling establish-

ment and growth patterns of wrinklegrass (Ischaemum rugosum

Salisb.). Weed Biol Manag 3:8–14

Blackshaw RE, Brandt RN (2008) Nitrogen fertilizer rate effects on

weed competitiveness is species dependent. Weed Sci

56:743–747

Blackshaw RE, Brandt RN, Janzen HH, Entz T, Grant CA, Derksen

DA (2003) Differential response of weed species to added

nitrogen. Weed Sci 51:532–539

Bolfrey-Arku GEK, Chauhan BS, Johnson DE (2011) Seed germi-

nation ecology of itchgrass (Rottboellia cochinchinensis). Weed

Sci 59:182–187

Bonifas KD, Walters DT, Cassman KG, Lindquist JL (2005) Nitrogen

supply affects root:shoot ratio in corn and velvetleaf (Abutilon

theophrasti). Weed Sci 53:670–675

Calvo G, Merayo A, Rojas CE (1996) Diagnostico de la problematica

de la caminadora (Rottboellia cochinchinensis) en dos zonas

productoras de maız de la provincia de Guanacaste, Costa Rica.

Manejo Int Plagas 41:50–52

Caton BP, Foin TC, Hill JE (1997) Phenotypic plasticity of

Ammannia spp. in competition with rice. Weed Res 37:33–38

Chauhan BS (2012) Weed ecology and weed management strategies

for dry-seeded rice in Asia. Weed Technol 26:1–13

Chauhan BS (2013) Growth response of itchgrass (Rottboellia

cochinchinensis) to water stress. Weed Sci 61:98–103

Chauhan BS, Abugho SB (2013) Effects of water regime, nitrogen

fertilization, and rice plant density on growth and reproduction

of lowland weed Echinochloa crus-galli. Crop Prot 54:142–147

Chauhan BS, Johnson DE (2009) Influence of tillage systems on weed

seedling emergence pattern in rainfed rice. Soil Tillage Res

106:15–21

J Pest Sci

123

Chauhan BS, Johnson DE (2010a) The role of seed ecology in

improving weed management strategies in the tropics. Adv

Agron 105:221–262

Chauhan BS, Johnson DE (2010b) Response of rice flatsedge

(Cyperus iria) and barnyardgrass (Echinochloa crus-galli) to

rice interference. Weed Sci 58:204–208

DFID Weeds Project (2002) Realizing sustainable weed management

to reduce poverty and drudgery amongst small-scale farmers in

West African Savannah. International Institute of Tropical

Agriculture (IITA), Ibadan

Etejere EO, Ajibola IO (1990) Studies on seed germination and

dormancy of itchgrass (Rottboellia cochinchinensis). Niger J

Weed Sci 3:19–28

Evans SP, Knezevic SZ, Lindquist JL, Shapiro CA (2003) Influence

of nitrogen and duration of weed interference on corn growth

and development. Weed Sci 51:546–556

Funk JL (2008) Differences in plasticity between invasive and native

plants from a low resource environment. J Ecol 96:1162–1173

GenStat 8.0. (2005) GenStat Release 8 Reference Manual. VSN

International, Oxford, p 343

Gibson KD, Fischer AJ (2001) Relative growth and photosynthetic

response of water-seeded rice and Echinochloa oryzoides (Ard.)

Fritsch to shade. Int J Pest Manag 47:305–309

Gibson KD, Fischer AJ, Foin TC (2001) Shading and the growth and

photosynthetic responses of Ammannia coccinnea. Weed Res

41:59–67

Gibson KD, Fischer AJ, Foin TC (2004) Compensatory responses of

late watergrass (Echinochloa phyllopogon) and rice to resource

limitations. Weed Sci 52:271–280

Griffin J (1991) Itchgrass (Rottboellia cochinchinensis) control

options in soybean (Glycine max). Weed Technol 5:426–429

Holm LG, Plucknett DL, Pancho JV, Herberger JP (1977) The

world’s worst weeds: distribution and biology. University of

Hawaii Press, Honolulu, p 609

Huke RE, Huke EH (1997) Rice area by type of culture: South,

Southeast, and East Asia. International Rice Research Institute,

Los Banos, p 59

Jordan TN, Cobel HD, Wax LM (1987) Weed control. In: Wilcox JR

(ed) Soybeans: improvement, production, and uses, 2nd edn.

ASA, Madison, p 449

Knops JMH, Reinhart K (2000) Specific leaf area along a nitrogen

fertilization gradient. Am Midl Nat 144:265–272

Liebman M, Gallandt ER (1997) Many little hammers: ecological

approaches to management of crop-weed interactions. In:

Jackson LE (ed) Ecology in agriculture. Academic Press, San

Diego, pp 291–346

Liebman M, Janke RJ (1990) Sustainable weed management

practices. In: Francis CA, Flora CB, King LD (eds) Sustainable

agriculture in temperate zones. Wiley, New York, pp 111–143

Marenco RA, Reis ACS (1998) Shading as an environmental factor

affecting the growth of Ischaemum rugosum. Rev Bras Fisiol

Veg 10:107–112

Meksawat S, Pornprom T (2010) Allelopathic effect of itchgrass

(Rottboellia cochinchinensis) on seed germination and plant

growth. Weed Biol Manag 10:16–24

Migo TR, Pamplona RR, Dingkuhn M, De Datta SK (1991)

Interaction of water stress and nitrogen supply on the photosyn-

thetic parameters of two upland rice and two upland weeds.

Philipp J Weed Sci 18:69–89

Mohler CL (2001) Enhancing the competitive ability of crops.

Ecological Management of Agricultural Weeds. Cambridge

University Press, Cambridge

NAPPO (North American Plant Protection Organization) (2003)

PRA/Grains Panel Pest Fact Sheet-Rottboellia cochinchinensis

(Lour.) Clayton. Pamplona, P.P.; B.L. Available at http://www.

issg.org/database/species/ecology.asp. Accessed 15 Nov 2013

Oyewole CI, Ibikunle BAO (2010). The germination of corn weed

(Rottboellia cochinchinensis Lour Clayton) seed: induction and

prevention of germination in seed. Thai J Agric Sci 43:47–54.

http://www.thaiagj.org. Accessed 15 Nov 2013

Phuong LT, Denich M, Vlek PLG, Balasubramanian V (2005)

Suppressing weeds in direct-seeded lowland rice: effects of

methods and rates of seeding. J Agron Crop Sci 191:185–194

Reynolds HL, Antonio CD (1996) The ecological significance of

plasticity in root weight ratio in response to nitrogen: opinion.

Plant Soil 185:75–97

Sage RF (2000) C3 versus C4 photosynthesis in rice: ecophysiological

perspective. In: Sheehy JE, Mitchell PL, Hardy B (eds)

Redesigning rice photosynthesis to increase yield. International

Rice Research Institute, Los Banos, pp 13–35

Schwinning S, Weiner J (1998) Mechanism determining the degree of

size-asymmetry in competition among plants. Oecologia 113:

447–455

Singh T, Kolar JS (1993) Competitive ability of wrinklegrass

(Ischaemum rugosum Salisb.) for utilization of major nutrients

(NPK) in transplanted paddy. Indian J Weed Sci 25:30–35

Smith VM, Fonseca (2001) Integrated management of itchgrass in a

corn cropping system: modeling the effect of control tactics.

Weed Sci 49:123–134

Tuong TP, Bouman BAM (2003) Rice production in water-scarce

environments. In: Kijne JW, Barker R, Molden D (eds) Water

productivity in agriculture: limits and opportunities for improve-

ments. CABI Publishing, Wallingford, pp 53–67

Valverde BE (2003) Progress on Rottboellia cochinchinensis man-

agement. In: Labrada (ed) Weed management for developing

Countries, Addendum 1. FAO Plant Production and Protection

Paper 120 (www.fao.org/documents/show_cdr.asp?url_file=/

DOCREP/006/Y5031)

Valverde BE (2007) Status and management of grass-weed herbicide

resistance in Latin America. Weed Technol 21:310–323

Valverde BE, Merayo A, Rojas CE, Alvarez T (1995). Interaction

between a cover crop (Mucuna sp.), a weed (Rottboellia

cochinchinensis) and a crop (maize). Proc Bright Crop Conf

Weeds 197–200

Vourlitis GL, Kroon JL (2013) Growth and resource use of the

invasive grass, pampasgrass (Cortaderia selloana) in response to

nitrogen and water availability. Weed Sci 61:117–125

Weiner J, Griepentrog HW, Kristensen L (2001) Suppression of

weeds by spring wheat Triticum aestivum increases with crop

density and spatial uniformity. J Appl Ecol 38:784–790

J Pest Sci

123