Goosegrass (Eleusine indica) density effects on cotton (Gossypium hirsutum)

Journal of Integrative Agriculture 2015, 14(9): 1778–1785 Available online at www.sciencedirect.com

ScienceDirect

RESEARCH ARTICLE

Goosegrass (Eleusine indica) density effects on cotton (Gossypium hirsutum) MA Xiao-yan1, WU Han-wen2, JIANG Wei-li1, MA Ya-jie1, MA Yan1 1

State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, P.R.China

2

Wagga Wagga Agricultural Institute, NSW Department of Primary Industries, Wagga Wagga New South Wales 2650, Australia

Abstract Goosegrass is one of the worst agricultural weeds on a worldwide basis. Understanding of its interference impact in crop field will provide useful information for weed control programs. Field experiments were conducted during 2010–2012 to determine the influence of goosegrass density on cotton growth at the weed densities of 0, 0.125, 0.25, 0.5, 1, 2, and 4 plants m–1 of row. Seed cotton yield tended to decrease with the increase in weed density, and goosegrass at a density of 4 plants m–1 of row significantly reduced cotton yields by 20 to 27%. A density of 11.6–19.2 goosegrass plant m–1 of row would result in a 50% cotton yield loss from the maximum yield according to the hyperbolic decay regression model. Boll production was not affected in the early growing season. But boll numbers per plant were reduced about 25% at the density of 4 plants m–1 of row in the late growing season. Both cotton boll weight and seed numbers per boll were significantly reduced (8%) at 4 goosegrass plants m–1 of row. Cotton plant height, stem diameter and sympodial branch number were not affected as much as cotton yields by goosegrass competition. Seed index, lint percentage and lint fiber properties were unaffected by weed competition. Intraspecific competition resulted in density-dependent effects on weed biomass per plant, 142–387 g dry weight by harvest. Goosegrass biomass m–2 tended to increase with increasing weed density as indicated by a quadratic response. The adverse impact of goosegrass on cotton yield identified in this study has indicated the need of effective goosegrass management. Keywords: competition, goosegrass, cotton yield, fiber properties, weed biomass

1. Introduction Goosegrass (Eleusine indica (L.) Gaertn.), belonging to the

Received 15 October, 2014 Accepted 6 May, 2015 MA Xiao-yan, Tel: +86-372-2562297, E-mail: [email protected]; Correspondence MA Yan, Tel: +86-372-2562294, E-mail: [email protected] © 2015, CAAS. All rights reserved. Published by Elsevier Ltd. doi: 10.1016/S2095-3119(15)61058-9

family Poaceae, is listed as one of the five most noxious weeds in the world and has been reported to be a significant weed in 46 crops in more than 60 countries (Holm et al. 1977). In China it is a serious weed in orchards, vegetable farms, mulberry plantations and agronomic crops and is also frequently found in most cotton-growing areas and highly pernicious to cotton growers (Zhang 2003; Ma et al. 2010). Goosegrass’s high fecundity, wide emergence window, and its tolerance to a broad range of environmental conditions contribute to its success as an injurious annual grass weed worldwide (Ismail et al. 2002, 2003). Chin (1979) reported that a single plant of goosegrass can produce as many as 140 000 seeds, which contributes to its ability to spread

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rapidly. Studies in Malaysia indicated that goosegrass seedlings started emerging in the beginning of April and continued through the late-September (Chuah et al. 2004), which was consistent with our observation in the uncultivated land and cotton field in central China (Ma et al. 2010). As an effective, reliable and cheap method of weed control, various herbicides have been synthesized and utilized for reducing weed infestation. However, excessive use of a particular herbicide in the same areas on the same types of weeds has led to a dramatic increase in herbicide-resistant weed biotypes. Since trifluralin-resistant goosegrass was primarily found in cotton field in North Carolina, USA (Heap 2014), to date, goosegrass has evolved resistance to several herbicides, including the dinitroaniline herbicides (Mudge et al. 1984), acetyl CoA carboxylase inhibitors (Leach et al. 1995), glyphosate (Lee and Ngim 2000), glufosinate and paraquat (Chuah et al. 2010). In China, goosegrass primarily evolved herbicide resistance to paraquat in southern orchards (Chen and Han 2009), and glyphosate-resistant goosegrass was also confirmed in fruit-cultivation and vegetable farm (Yang et al. 2012; Chen et al. 2014). Haloxyfop-resistant goosegrass has recently been found in cotton field in Hunan Province, China (Li et al. 2014). Few reports covered the seriousness of herbicide resistance of goosegrass in China since farmers often rely on excessive use of herbicides by more frequent applications and higher dose rates. The herbicide resistance of goosegrass makes it more challenging for growers to control in cropping system. For successful and sustainable management of goosegrass, it is important to understand its competitive ability and interference impact in crops. To date, there are very few reports about the competition of goosegrass with crops. Wandscheer et al. (2013) evaluated the impact of goosegrass in corn with the replacement series model and found that for shoot and total dry mass and height, corn plants reduced productivity compared to monoculture when the weed density was greater than corn. The effects of goosegrass competition in other crops, especially in cotton production, are not known. However, competitive effects of other weeds have been well documented in cotton. Bridges and Chandler (1987) indicated that, at johnsongrass (Sorghum halepense (L.) Pers.) density from 1 to 32 plants 9.8 m–1 of row, seed cotton yield was reduced from 1 to 70% compared with the weed-free control. Wood et al. (2002) reported that cotton lint yields were reduced by 30 kg ha–1 for each increase of 1 johnsongrass plant 15 m–1 of row. Another study in Turkey indicated that 2 johnsongrass plants m–1 of row reduced cotton yields by as much as 50% (Uludag et al. 2007). Sicklepod (Cassia obtusifolia L.) and tall morningglory (Ipomoea purpurea (L.) Roth) had a seed cotton yield loss threshold of 8 plants 7.31 m–1 of row (Buchanan and Burns 1971a). Cocklebur (Xanthium pensylvanicum Wallr.) reduced seed

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cotton yield by 20 to 60% at a density of 8 plants 7.31 m–1 of row, and redroot pigweed (Amaranthus retroflexus L.) reduced cotton yield by 45 to 70% at a density of 8 plants 7.31 m–1 of row at one location and 48 plants 7.31 m–1 of row at another location (Buchanan and Burns 1971b). In the Yellow River and Yangzi River cotton-producing areas of China, goosegrass is one of the dominant and problematic weed species in the cotton fields. In general, goosegrass emerges from May to September, with the peak of seedling emergence from early June to early July (Ma et al. 2010). So far, there is limited information on interference impact of goosegrass on cotton growth and yield. Therefore, the present studies were carried out to estimate the influence of several goosegrass densities on cotton growth, yield and fiber properties and to determine the damage threshold density of goosegrass when grown with cotton over the entire growing season.

2. Results 2.1. Cotton height, stem diameter and sympodial branch number Goosegrass interference did not significantly reduce cotton plant height. Cotton height in the weed-free control was 112 cm, while cotton with the goosegrass at the highest density (4 plants m–1 of row) was 107 cm, only 5% reduction as compared with the weed-free control. Stem diameter was significantly reduced when weed density reached to 2–4 plant m–1 of row, and there was only 6% reduction at these two densities when compared to the weed-free control. There were no significant reductions in sympodial branch number per cotton plant as a result of weed competition at the densities of 0.125–2 goosegrass plant m–1 of row. The only density which significantly reduced sympodial branch numbers was 4 plants m–1 of row. However, the sympodial branch numbers was only reduced by 6% at the highest density when compared with the weed-free control (Table 1).

2.2. Goosegrass biomass Individual goosegrass dry weight showed a reduction from 386.9 g plant–1 at the 0.125-weed density to 141.6 g plant–1 at the 4-plant density averaged across years. Differences in dry weed weight were distributed as 0.125, 0.25, 0.5<1<2<4, where “<” indicated significant differences at the 0.05 probability level. Densities of 0.125, 0.25, and 0.5 weed m–1 of row produced equivalent biomass which differed from the biomass produced by densities of 1, 2, and 4 weeds m–1 of row. The regression analyses indicated that there was a quadratic relationship between individual weed dry weight (y) and weed density (x) and the equation was

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y=413.7–129.6x+15.2x2 (r2=0.99). Goosegrass biomass m–2 tended to increase with increasing weed density and the results also fit quadratic model well (y=47.6+336.1x–43.2x2, r2=0.98). The lowest density of 0.125 goosegrass plant m–1 of row produced about 60 g m–2 of dry matter, and the highest density of 4 weed plants m–1 of row produced dry biomass 708 g m–2 (Table 1).

2.3. Cotton yield Seed cotton yield in the present study tended to decrease as the goosegrass density increased in all three experimental years. Because of differences in yield across years, yield data were presented separately (Fig. 1). Seed cotton yield under weed-free conditions ranged from

1 838.4 kg ha–1 in 2010 to 3 782.2 kg ha–1 in 2012. The lower cotton yield in 2010 might be due to the heavier rainfall or more cloudy days in August and September, which resulted in more decayed cotton bolls. Although seed cotton yields appeared to be lower with the increasing of weed density from 0 to 2 plants m–1 of row, the difference in yields from the six densities was not significant. The threshold density at which significant yield reduction appeared in all 3 years was 4 goosegrass plants m–1 of row, which reduced seed cotton yield by 20 to 27% when compared with the weed-free control. The hyperbolic decay regression model estimated that a goosegrass density of 11.6–19.2 plant m–1 of row would result in a 50% reduction in seed cotton yield as compared with the maximum yield achieved in this study (Fig. 1).

Table 1 Influence of goosegrass densities on cotton growth and yield components and on goosegrass biomass Goosegrass density (no. m–1 of row (no. m–2)) 0 0.125 (0.16) 0.25 (0.31) 0.5 (0.63) 1 (1.25) 2 (2.50) 4 (5.00) Year (Y) Density (D) Y×D

Yield components Lint Seed percentage numbers (%) (no. boll–1) 39.2 a 35.0 a 39.1 a 34.5 a 39.1 a 35.4 a 38.7 a 34.7 a 39.4 a 34.8 a 38.8 a 33.3 ab 39.0 a 32.4 b

Plant height (cm)

Stem diameter (mm)

Sympodial branch (no. plant–1)

112.2 a 111.7 a 107.2 a 108.9 a 110.9 a 110.4 a 107.0 a

16.0 a 15.5 ab 15.4 ab 15.8 ab 15.4 ab 15.0 b 14.9 b

14.2 a 14.0 ab 14.1 ab 14.2 a 13.9 ab 13.6 ab 13.4 b

Boll weight (g) 6.0 a 6.0 a 6.0 a 5.9 a 5.9 a 5.7 ab 5.5 b

***

***

**

***

***

***

*

NS NS

NS NS

NS NS

**

NS

**

NS

**

NS

NS NS

Seed index (g 100 seed–1) 10.2 a 10.3 a 10.2 a 10.1 a 10.1 a 10.2 a 9.9 a

Weed biomass Individual dry Total dry weight weight (g plant–1) (g m–2) – – 386.9 a 60.4 f 379.9 a 118.7 e 360.8 a 225.5 d 316.6 b 395.8 c 200.9 c 502.3 b 141.6 d 708.1 a NS NS ***

***

NS

NS

Means calculated over all three experiments, and means within columns followed by the same letters are not significantly different between treatments at the 0.05 probability level as determined by LSD test. – indicates no data; NS indicates no significance; ***, ** and * indicates significance at P levels of 0.001, 0.01 and 0.05, respectively. The same as in Table 2.

Seed cotton yield (kg ha–1)

4 500

2.4. Cotton yield components

2010 2011 2012

4 000 3 500

r =0.79 2

3 000 2 500

*

r2=0.89*

2 000 r2=0.65*

1 500 1 000

0 0.25 0.5

1 2 Weed density (plants m–1 of row)

4

Fig. 1 Seed cotton yield as influenced by goosegrass competition at seven infestation densities. Equations were y=1 796.6×13.2/(13.2+x), y=3 532.5×11.6/(11.6+x), and y=3 649.5×19.2/(19.2+x) in 2010, 2011, and 2012, respectively, and all were significant at the 0.05 probability level. Vertical bars are standard errors. The same as below.

Weed densities did not result in significant reduction in boll numbers when measured in mid July in all three experiments (data not shown); however, the weed density started to show negative impact on boll numbers when assessed in August and September in 3 years. Data of August or September were combined and analyzed across years because there were no significant year-by-density interactions. The relationship between boll numbers and weed density was exponential (Fig. 2). The threshold densities at which significant boll reductions appeared were 4 goosegrass plants m–1 of row when measured in August and only 0.5 goosegrass plant m–1 of row when measured in September, indicating the prolonged weed competition had significant impact on cotton boll production. Goosegrass at the density of 4 goosegrass plants m–1 of row caused nearly 25% reductions in boll numbers when compared with the weed-free control.

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3. Discussion

Boll numbers plant–1

19 Aug. Sep.

17

15

r2=0.57*

13

11

r2=0.71* 0 0.25 0.5

1

4

2

Weed density (plants m–1 of row)

Fig. 2 Influence of goosegrass densities on boll numbers. Regression equations were y=16.5e–0.042x and y=14.6e–0.053x in August and September, respectively, and both were significant at the 0.05 probability level.

All goosegrass treatments from 0.125 to 2 plants m–1 of row had similar boll weight (6 g boll–1) to the weed-free control; however, goosegrass at densities of 4 goosegrass plants m–1 of row caused significant reductions (8%) in boll weight when compared with the weed-free control. Seed numbers per boll were reduced only at the highest density of 4 goosegrass plants m–1 of row and the reduction was 7% at this density. Cotton lint percentage and seed index were not affected by goosegrass competition (Table 1).

2.5. Cotton fiber quality Cotton fiber quality was evaluated to determine if goosegrass densities affected fiber length, fiber length uniformity, micronaire, breaking elongation and fiber strength of the hand-harvested samples. Results from our studies indicated that goosegrass did not affect any evaluated fiber quality characteristic when combined over the three experiments (Table 2).

Present study demonstrated that cotton plant height, stem diameter and sympodial branch number did not appear to be detrimentally influenced by goosegrass competition. This result is consistent with some previous studies which showed that cotton vegetative growth was not affected by weed competition (Buchanan and Mclaughlin 1975; Snipes et al. 1982; Askew and Wilcut 2002a, b, c). However, the adverse impacts on cotton growth due to weed competition have also been reported. Cotton height reductions resulted from full-season competition of spurred anoda (Anoda cristata (L.) Schlecht.), prickly sida (Sida spinosa L.), velvetleaf (Abutilon theophrasti), and venice mallow (Hibiscus trionum) at a density of 5.3 plants m–1 of row were 45, 30, 39, and 31%, respectively (Chandler 1977). Mercer et al. (1987) documented that cotton height was reduced by 43% at the unicorn-plant (Proboscidea louisianica) density of 3.2 plants m–1 of row. Barnett and Steckel (2013) found that cotton height could be reduced by half due to the competition of giant ragweed (Ambrosia trifida) at 1.6 plants m–1 of row. Similarly, Buchanan and Burns (1971a, b) claimed that, at the density of 6.6 plants m–1 of row, sicklepod, tall morningglory, common cocklebur, and redroot pigweed reduced cotton height by 27, 40, 37, and 33%, and stem diameter by 39, 41, 52, and 43%, respectively, when compared with the weed-free control. The inconsistencies between reports on weed impact on cotton growth could be due to the differences in weed species, density, as well as local edaphic and climatic conditions. Cotton yield is generally more sensitive than vegetative growth when exposed to weed competition (Poonguzhalan et al. 2013). Seed cotton yield tended to decrease as the goosegrass density increased in all 3 experimental years. It may be a result of the cotton plants being under severe weed competition stress and producing fewer and smaller boll than normal, and thus decreasing seed cotton yield. Other researchers had reported similar results that yield

Table 2 Influence of goosegrass densities on cotton fiber quality Goosegrass density (no. m–1 of row (no. m–2)) 0 0.125 (0.16) 0.25 (0.31) 0.5 (0.63) 1 (1.25) 2 (2.50) 4 (5.00) Year (Y) Density (D) Y×D

Fiber length (mm) 29.0 a 28.7 a 28.7 a 28.8 a 28.8 a 28.8 a 28.5 a

Length uniformity (%) 83.4 a 83.8 a 83.8 a 83.7 a 83.8 a 83.5 a 83.3 a

Micronaire 4.9 ab 4.9 ab 5.1 a 5.0 ab 5.1 a 4.9 ab 4.7 b

Breaking elongation (%) 6.5 a 6.5 a 6.4 a 6.4 a 6.4 a 6.4 a 6.4 a

Fiber strength (cN tex–1) 27.4 a 27.0 a 27.1 a 27.0 a 26.7 a 27.1 a 27.4 a

***

***

***

***

***

NS NS

NS NS

NS NS

NS NS

NS NS

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reduction caused by weed competition was primarily a result of reduction in cotton boll number and weight (Castner et al. 1989; Tingle and Steele 2003). Both boll weight and seed number per boll were reduced to some extent in some of the goosegrass competition treatments while the lint percentage was not affected by goosegrass competition, which was consistent with the earlier studies (Buchanan and Burns 1971a, b; Crowley and Buchanan 1978). The cotton seed index was also not affected by goosegrass competition, which was in agreement with Buchanan and Burns (1971b). In conclusion, the goosegrass interference could reduce cotton boll weight and seed number per boll, but did not affect the lint percentage or seed weight. Results from this study indicated that cotton could tolerate goosegrass competition at 0.1 to 2 plants m–1 of row without suffering significant yield loss. The threshold density at which statistically significant yield reduction appeared was at 4 goosegrass plants m–1 of row, which approximately reduced cotton seed yield by 25%. A 50% reduction in seed cotton yield occurred when goosegrass density reached to 11.6–19.2 plant m–1 of row. Previous studies reported that Palmer amaranth (A. palmeri) at 0.38–0.87 plant m–1 of row reduced cotton yield by 50% (Rowland et al. 1999; Morgan et al. 2001). Snipes et al. (1982) reported that 0.37–0.53 common cocklebur plant m–1 of row reduced cotton yield by 50%. Similarly, Barneet and Steckel (2013) reported that a density of 0.26 giant ragweed plant m–1 of row would result in a 50% cotton yield loss. It is known that competitiveness of weeds with crop depends on weed morphology (Buchanan and Burns 1971a, b), its phenology (Buchanan and Burns 1970) and its differential response to environmental factors such as light, water and nutrients (Ballaré and Casal 2000; Saberali et al. 2012). In general, aboveground competition is primarily a function of canopy development and competition for available light. If weeds germinate simultaneously with the crop and are allowed to form a leaf canopy over cotton, they will shade the crop and are more competitive (Buchanan and Burns 1970; Tingle and Steele 2003). In contrast, inability to shade cotton and compete for light early in the growing season could result in an overall lack of competitiveness (Askew and Wilcut 2002a, b, c). Moreover, cotton has been shown to be relatively intolerant to shade, as it can lead to abscission of squares and bolls (Goodman 1955). Goosegrass grows semiprostrate with a compressed, tufted stem and seldom exceeds 90 cm in vertical height. This low-growing grass often grows shorter than cotton plant during the whole growth period, resulting in less efficient use of light than cotton. This might be one of the reasons that goosegrass was not competitive with cotton at 0.1 to 2 plants m–1 of row. However, goosegrass could reduce cotton yield if the density is over 4 plants m–1 of row due to intensified competition for water and nutrients. As a

deep-rooted grass, the more dense growth of goosegrass, the more water and nutrients are required. Competition for water and nutrients is frequently credited with reduced crop yield (Buchanan and Mclaughlin 1975; Rushing et al. 1985a; Castner et al. 1989). Except for the interspecific competition between cotton and weed, the density-dependent effects on weed biomass per plant indicated that intraspecific competition of goosegrass occurred in the range of densities evaluated. Increasing weed density from 0.125 up to 4 plants m–1 of row resulted in biomass production of goosegrass that was only 12 times higher than in the treatment with 0.125 weed plant m–1 of row. This result agreed with many other reports for buffalobur (Solanum rostratum), common cocklebur, tumble pigweed (A. albus), and unicorn-plant (Snipes et al. 1982; Rushing et al. 1985a, b; Mercer et al. 1987). Goosegrass at various densities did not significantly affect fiber length, fiber length uniformity, micronaire, breaking elongation and fiber strength of the hand-harvested samples. This result was similar to earlier reports that fiber quality traits were not as sensitive as cotton yield in assessing weed interference effects (Crowley and Buchanan 1978; Smith et al. 2000; Barnett and Steckel 2013). However, other studies have indicated that certain weed species, including ivyleaf morningglory (I. hederacea), hogpotato (Hoffmanseggia glauca), unicorn-plant, and johnsongrass, could reduce fiber quality at high densities (Mercer et al. 1987; Castner et al. 1989; Rogers et al. 1996; Wood et al. 2002).

4. Conclusion Results from this study demonstrated that the interference of goosegrass can significantly reduce cotton yield at a density of 4 plants m–1 of row. Growers need to control goosegrass early in the growing season to maintain cotton yield. Although the effects of goosegrass density on phenotypic traits of cotton, including vegetative and reproductive growth indices and quantity and quality characteristics, were described clearly in this study, the results should only be used to guide the goosegrass control in the study area and should not be extrapolated to other cotton-growing areas and tillage systems. As a worldwide serious agricultural weed, future studies should evaluate the interference potential of goosegrass at various cotton growing environment, and investigate the effect of weed removal at various cotton growth stages. These studies will provide critical information for timely management of goosegrass. In addition, it is necessary to address effects on leaf area index, photosynthetically active radiation, and growth rate, which are the better growth indices involved in competitiveness of crop against weed (Amini et al. 2014; Ghanizadeh et al. 2014).

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5. Materials and methods 5.1. Field arrangement The experiments were conducted in the experimental field at the Institute of Cotton Research of Chinese Academy of Agricultural Sciences (36.13°N, 114.85°E) from April to October in 3 consecutive years (2010, 2011 and 2012). The soil was a sandy loam with a pH of 8.0 and an organic matter of 1.5%. Some local meteorological data during the experimental periods are presented in Table 3. This location is a representative of the Yellow River cotton-producing area of China. The field was irrigated, disked, harrowed, and fertilized with compound fertilizer at 1 500 kg ha–1 (N:P2O5:K2O=24:11:5, ≥40%; Zhengzhou Naweigao Fertilizer Co., Ltd., Henan Province, China) prior to planting. CCRI 79, a commonly grown cotton cultivar in the region, was sown by hand at about 200 seeds 8 m–1 of row on 28 April 2010, 29 April 2011 and 30 April 2012, respectively. After plant emergence (approximately 10 d after sowing), seedlings were thinned to about 4 seedlings m–1 of row (50 000 cotton plants ha–1). Plots were 8 m long and four 80-cm rows wide. The experimental design was a randomized complete block with four replications. After fertilizers, 150 kg ha–1 urea (N≥46.4%; Anyang Chemical Industry Co., Ltd., Henan Province, China) and 300 kg ha–1 compound fertilizer, were used in mid-June and mid-July to optimize cotton growth, and insect and disease control practices were applied as required. No herbicides or irrigation treatments were used during these experiments.

5.2. Plant survey Immediately after cotton emergence, goosegrass seedlings at 3–5 leaf stage, which were either pre-cultured for 1 month near the experimental field under the plastic mulch in 2010 or collected from nearby fields in 2011 and 2012, were transplanted at the required density of 0, 1, 2, 4, 8, 16, and 32

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plants 8 m–1 of cotton row, or to 0, 0.125, 0.25, 0.5, 1, 2, and 4 plants m–1 of row, at the distance of 10 cm away from the cotton row in the center two rows of each plot. The outside rows of each plot were weed free and served as border rows between adjacent plots. The maximum density of goosegrass we set was equivalent to 50 000 plants ha–1, which was accordant with the practice in the cotton field as described in Ma et al. (2010). Goosegrass was watered as needed for the first few days, and all plants resumed growth after the transplanting in 0–5 d. All other weeds were removed at weekly intervals throughout the season by hand-hoeing. After the establishment, the goosegrass developed quickly and set seed earlier than cotton did. Approximately 2 to 3 weeks prior to cotton harvest (at mid-September), all goosegrass plants became senescent and were removed from plots. 2–5 randomly selected goosegrass plants from each plot were cut at ground level with pruning shears, oven-dried at 60°C for 48 h, and weighed to determine the individual weed dry biomass. Cotton plant height, stem diameter and sympodial branch number were measured from two randomly parts (5 contiguous plants for each part) in the center two rows of each plot in mid-September each year. Height was measured in cm from the soil surface to the apical meristem, and stem diameter was determined at the soil line with calipers to the nearest 0.01 mm. In addition, the boll numbers per plant were recorded in mid-July, mid-August and mid-September. At the end of the growing season, cotton of the center two rows was hand-harvested twice from each plot, first at 50% open bolls and the second at 100% open bolls. Weights of the total hand-harvested cotton were recorded. Immediately before cotton harvest, one mature boll of middle branch was harvested from each of 25 randomly selected plants in each plot and was ginned together on a small single roller gin to determine boll weight, lint percentage, seed number per boll and seed index (Du and Zhou 2005). Lint percentage is an expression of the ratio of the weight of the lint to the total weight of the seed cotton. The seed was acid delinted prior to weight determination. Four lots of 100-seed random

Table 3 Monthly mean temperature and total precipitation from April 1 to October 31 for 2010–2012 at the experimental site (Anyang Meteorological Bureau, China) Month April May June July August September October Total

2010 12.0 20.8 26.3 28.0 24.8 20.6 14.3 –

Temperature (°C) 2011 14.8 21.0 27.0 27.3 24.6 18.2 14.9 –

2012 16.5 22.4 26.8 27.9 25.0 20.9 16.0 –

2010 19.6 57.0 20.2 89.4 223.8 111.5 7.8 529.3

Precipitation (mm) 2011 7.6 41.2 15.4 98.3 126.9 118.7 32.4 440.5

2012 14.1 8.2 45.2 185.3 145.9 29.3 12.5 440.5

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samples were collected from each plot and measured, and the average weight was regarded as the seed index. After the measurement, a 100-g lint sample was subjected to fiber quality tests, which included fiber length, length uniformity, micronaire, breaking elongation and fiber strength, at the Supervision, Inspection and Test Center of Cotton Quality, Ministry of Agriculture, China.

5.3. Data analysis Data were analyzed using the general linear models (GLMs) treating goosegrass density as fixed factor and year as random factor to test for significant main effects and interactions. There was no significant weed density by year interaction for cotton growth, quantity and quality characteristics, and thus they were summarized and analyzed across years (Tables 1 and 2). Means were separated using Fisher’s protected least significance difference (LSD) test at the 95% level of probability. Regression analyses were performed to analyze the influence of goosegrass densities on boll number per plant, seed cotton yield and weed biomass. A two-parameter hyperbolic decay regression model (Barnett and Steckel 2013) was used to describe the density-dependent effects of goosegrass on seed cotton yield: y=ab/(b+x), where y is the seed cotton yield, a is the asymptote or estimate of maximum cotton yield, b is the estimate of the goosegrass density at which 50% yield loss occurs, and x is the weed density per meter of crop row. Coefficients of determination (r2) were reported to indicate the amount of variation in the dependent variables that can be explained by the independent variable. Analysis was performed with the statistical software SPSS 13.0.

Acknowledgements This research was funded by grants from the National Key Technology R&D Program of China (2012BAD19B05) and the Fundamental Research Funds for Central Public Welfare Research Institutes, China (SJB1005). We thank Xi Jianping, Li Xifeng and Lu Yanrong at Institute of Cotton Research of CAAS for their assistance in the field.

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