Effects of winter wheat cultivars and seed rate ... - Wiley Online Library

Effects of winter wheat cultivars and seed rate on the biological characteristics of naturally occurring weed flora N E KORRES & R J FROUD-WILLIAMS Department of Agricultural Botany, University of Reading, Building 2, Earley Gate, Reading, Berks, UK Received 11 July 2001 Revised version accepted 13 July 2002

Summary Differential competitive ability of six winter wheat cultivars and traits that confer such attributes were investigated for a range of seed rates in the presence or absence of weeds for a naturally occurring weed flora in two successive years in split-plot field experiments. Crop height and tillering capacity were considered suitable attributes for weed suppression, although competitiveness is a relative rather than an absolute characteristic. Maris Huntsman and Maris Widgeon were the most competitive cultivars whereas Fresco was the least

Introduction A knowledge of weed biology is desirable for development of economically and environmentally acceptable weed management systems. Weed infestations reflect the ecological consequences of management practices in the current and previous years as well as edaphic characteristics of the site and regional climate (Thomas & Dale, 1991). The development of an integrated weed management system requires detailed information on weed:crop interactions, including the relative competitive ability of the crop during various phases of development on weed growth (Tollenaar et al., 1994). Cultural, chemical and biological practices exert a selective influence on weed population composition and biology (Moss, 1985; Wilson et al., 1988; Van Acker et al., 1997). A major component of integrated weed management is the use of more competitive crops (Lemerle et al., 1996), although selection for better crop competitiveness is a difficult task (Richards, 1989). Christensen (1995) indicated that traits that confer competitive ability need to be identified. Melander (1993), Wicks et al. (1994) and Grundy & Froud-Williams (1997) recorded

competitive. Manipulation of seed rate was a more reliable factor than cultivar selection for enhancement of weed suppression, although competitiveness of cultivars Buster, Riband and Maris Widgeon was not enhanced by increased seed rate. Crop densities ranging between 125 and 270 plants m)2 were found to offer adequate weed suppression. Linear relationships were observed between individual and total weed species dry weight and reproductive structures per unit area. Keywords: competition, weed suppression, weed biology, weed infestation, integrated weed management.

significant effects of tall cultivars of erect growth habit on individual weed species and populations. Quantitative biological characteristics that have been investigated for increased competitive ability include light penetration within the crop canopy (Seavers & Wright, 1995) cultivar height, (Wicks et al., 1986; Blackshaw, 1994; Lemerle et al., 1996; Ogg & Seefeldt, 1999) vegetative ground cover (Balyan et al., 1991) and tillering capacity (Challaiah et al., 1983; Fofana et al., 1995). Another factor that may be manipulated at relatively low cost is crop density (Doll et al., 1995) for weed suppression (Wilson et al., 1995; Hashem et al., 1998), although Samuel & Guest (1990) failed to obtain benefits from such manipulation. There is an increasing need for improved strategies of weed control. An important element of such management strategies is the development of population models (Thomas & Dale, 1991), where a knowledge of weed response to particular cultural practices can reduce weed incidence (Anderson et al., 1998) and hence yield losses. Therefore, the importance of an appropriate and accurate method of describing and predicting possible responses to various weed management systems will

Correspondence: N E Korres, Department of Agricultural Botany, University of Reading, Building 2, Earley Gate, Reading RG6 6AU, UK. Tel: (+44) 777 9301044; Fax: (+44) 118 9351804; E-mail: [email protected] or [email protected] European Weed Research Society Weed Research 2002 42, 417–428

418 N E Korres & R J Froud-Williams

enable producers to select effective and appropriate weed management strategies (Orson, 1997). For this reason, different approaches to modelling weed populations viz. empirical, deterministic, stochastic or based on spatial distribution have been investigated (Wallinga, 1995; Iriondo, 1996). Cultural practices, as density-independent parameters (Melander, 1993), together with weed demographic data including soil seedbank, seed germination, seedling establishment and dispersal, have been used (Solbrig et al., 1980; Mortimer & Manlove, 1983; Gonzalez-Andujar & Fernandez-Quintanilla 1991; Wilson & Wright, 1993). The objective of this study was to identify characteristics that influence wheat competitive ability and to evaluate the effects of cultivar selection, crop density and their interaction for weed suppression.

Materials and methods Crop management

Two randomized split-plot experiments with three replicates were conducted at the University of Reading Field Unit at Shinfield during 1995–96 and 1996–97. All necessary land preparations (ploughing and tine cultivation) were conducted to establish a fine seedbed before sowing. Six winter wheat cultivars (Triticum aestivum L.) were selected from the National Institute of Agricultural Botany (NIAB) recommended list of cereals (Anonymous, 1995–96). The selections chosen, based on their

differing growth attributes (Table 1), were two traditional tall cultivars Maris Huntsman (Expt 1) and Maris Widgeon (Expt 2) and five modern semi-dwarf cultivars, Fresco, Riband, Flame, Buster and Hussar, the latter replaced by Rialto in Expt 2. The selected cultivars were sown at a range of crop target densities using a modified Ojord seed drill. The target crop densities were 150, 250, 350 and 450 plant m)2 for Expt 1 and 150, 300, and 450 plant m)2 for Expt 2. Experimental plots were arranged with wheat cultivars and seed rates as main plots and presence ⁄ absence of the natural weed flora as subplots. Main plot size was 2 m wide · 8 or 9 m long (Expts 1 and 2 respectively), whereas final harvest area was 1 m2 for any of the subplot treatments in either experiment. Details of crop management for both experiments are presented in Table 2. Nitrogen fertilizer (Nitram 34.5% nitrogen for both experiments) was applied by hand to Expt 1 in one application, whereas in Expt 2 it was split in three amounts (40, 40 and 80 kg ha)1) to achieve 160 kg ha)1. In Expt 1, propiconazole (Radar, 259 g a.i. L)1, Novartis) at 130 g a.i. ha)1 and pirimicarb (Aphox, 50% wt ⁄ wt, Zeneca) at the recommended rate of 280 g a.i. ha)1, using a knapsack sprayer fitted with 04-F110 flat fan nozzles delivering 250 L ha)1 at a spray pressure of 210 kPa, were applied at GS 69 (Zadoks et al., 1974) to control Septoria leaf spot (Septoria tritici Blotch) and aphids (Sitobion avenae Fab.)

Table 1 Vegetative characteristics of the cultivars used in this study according to NIAB recommended list of cereals 1995–96

Straw length Growth habit Flag-leaf

Buster

Flame

Fresco

Hussar

Short to medium Semi-erect

Short to medium Intermediate

Erect

Erect to semi-erect

Short to Short to medium medium Prostrate Intermediate to semi-prostrate Erect Erect

Maris Huntsman

Maris Widgeon

Rialto

Riband

Long to very long Intermediate

Very long

Medium

Medium

Intermediate

Intermediate

Prostrate

Semi-recurved

Semi-erect to Erect semi-recurved

Erect

Table 2 Crop management during the experimental growing season Crop growth stage Expt 1 Sowing date Hand weeding Fertilizer application

Insecticide application Fungicide application Final harvest

7 ⁄ 11 ⁄ 95 25–29 ⁄ 3 ⁄ 96 30 ⁄ 3 ⁄ 96 – – 30 ⁄ 6 ⁄ 96 30 ⁄ 6 ⁄ 96 7–12 ⁄ 8 ⁄ 96

Expt 2 – Stem elongation (30–33) Stem elongation (30–33) – – End of flowering (69) End of flowering (69)

8 ⁄ 10 ⁄ 96 10–16 ⁄ 3 ⁄ 97 20 ⁄ 3 ⁄ 97 6 ⁄ 4 ⁄ 97 1 ⁄ 5 ⁄ 97 – 29 ⁄ 5 ⁄ 97 7–14 ⁄ 8 ⁄ 97

– Stem elongation (30–33) Stem elongation (30–33) Stem elongation (30–33) Booting (40–42) – Inflorescence emergence-heading (53)

Numbers in parentheses indicate cereal growth stages (Zadoks et al., 1974). European Weed Research Society Weed Research 2002 42, 417–428

Wheat cultivars and density for weed suppression 419

respectively. In Expt 2, it was not necessary to control aphids as the infestation was negligible, but the fungicide propiconazole was applied as described above at GS 53 (Table 2). Weeds were removed by hand from appropriate subplots in each crop in March. Sampling methods

Two and four intermediate samples were collected of crop and weeds for Expts 1 and 2 respectively (Table 3), in addition to final harvest where crop yield components and weed assessments were determined. Duplicate weed samples for both experiments were taken using a quadrat (30 cm · 30 cm) for each treatment at the dates indicated in Table 3. Samples were separated by species and number of individual weed species, dry weight, leaf area as appropriate and reproductive structures (number of panicles for Poa annua L., number of whorls for Lamium spp., flowers and number of seed capsules for Stellaria media (L.) Vill., number of flower heads and flower buds for Chamomilla spp. and Matricaria spp., flowers or seed fruits for Capsella bursa-pastoris L., Viola arvensis Murr., Veronica spp. and flower heads for Senecio vulgaris L.) from each sampling quadrat, recorded by hand and expressed per unit area for statistical analysis. In addition to dominant weed species in Expt 1 (P. annua, S. media, Chamomilla spp., Matricaria spp.), other species recorded were C. bursa-pastoris, Lamium spp., Aphanes arvensis L., Veronica spp., V. arvensis, and S. vulgaris. In Expt 2, the dominant species recorded were P. annua, S. media, Lamium spp., Chamomilla spp. and Matricaria spp. Additionally, C. bursa-pastoris, V. arvensis and Veronica spp. were sparsely present. Records for the two mayweed species Matricaria and Chamomilla were pooled for statistical analyses and are reported henceforth as Matricaria spp. Statistical analysis

Analysis of variance was conducted for assessment of differences between the means of each dependent

Table 3 Intermediate sampling and final harvest dates Expt 1

Expt 2

Sampling date

Crop

Sampling Weeds date

3–17 ⁄ 5 ⁄ 96 2–15 ⁄ 6 ⁄ 96

+ +

+ +

Final harvest

7–12 ⁄ 8 ⁄ 96

12–22 ⁄ 12 ⁄ 96 12–19 ⁄ 4 ⁄ 96 22–27 ⁄ 6 ⁄ 97 1–9 ⁄ 7 ⁄ 97 7–14 ⁄ 8 ⁄ 97

Crop

Weeds

+ + + +

+ + + + +

European Weed Research Society Weed Research 2002 42, 417–428

parameter for each treatment using GENSTAT 4.1 (Lawes Agricultural Trust, 1997) for Windows, whereas the appropriate transformations were performed (square roots or log(x + 1), see captions where applicable) to achieve normal distribution. An attempt to describe weed infestation throughout the growing season was conducted using log-linear modelling. The adoption of this method is based on the nature of the data (counts) and on the assumption that they follow a Poisson distribution. This assumes that discrete values are from 0 onwards and that the occurrence of an event must be independent of prior occurrences within the sampling unit (Sokal & Rohlf, 1995). As the experimental area used was uncropped before the experiment, there is no reason to reject the above assumption. Brain & Cousens (1990), Wallinga (1995) and Cardina et al. (1997) constructed models of weed populations on the assumption that weed dispersion is aggregated, which conforms to a negative binomial distribution. The experimental subplots in this investigation were relatively small (3 m · 3 m), hence the assumption that the dispersion of weeds is a random event for the adoption of the log-linear modelling is accepted. Furthermore, Hausler & Nordmeyer (1999) found that, in an attempt to characterize the pattern of weed distribution for six fields under conventional use, single and grouped species with high mean weed densities were less clumped than species of low abundance. This method of analysis was applied to weed species that were dominants within the experimental area.

Results Crop establishment

Percentage crop establishment was calculated from the predetermined harvest area. In Expt 1, target densities were grossly underachieved owing to a combination of late drilling and bird damage, necessitating the adoption of three crop density classes, namely low (< 50) intermediate (> 50 < 100) and high (> 150 plants m)2) for statistical purposes. In Expt 2, percentage crop establishment ranged from 84% to 100% with the exception of Fresco, which achieved 60% of its target density. Means across cultivars and treatments gave crop densities of 125, 270 and 380 m)2. Effects of cultivar on vegetative characteristics of weed flora

Significant differences were recorded for S. media (Table 4) at 210 and 190 days after sowing (DAS) for Expts 1 and 2 respectively. Fresco was the least


Table 4 Effects of cultivar on weed vegetative characteristics (mean of three crop densities) A. Expt 1 (210 DAS) (Stellaria media)

Leaf area (cm2 m)2) Reproductive structures m)2

Buster

Flame

Fresco

Maris Huntsman

Hussar

Riband

SED

F prob.

1263 3815

918 3251

1872 5637

739 3361

1221 3381

757 2924

301.2 864.2

** *

Buster

Flame

Fresco

Maris Widgeon

Rialto

Riband

SED

F prob.

B. Expt 2 (190 DAS)

Stellaria media Dry weight (g m)2) Leaf area (cm2 m)2) Reproductive structures m)2

33.8 44.6 71.0 1279 (35.1) 1662 (40.1) 2790 (51.9) 4635 5488 8898

26.4 33.0 44.2 1039 (31.5) 1215 (33.9) 1793 (41.6) 3185 3609 5024

9.91 ** (5.18) ** 1158.9 ***

Stellaria media, Poa annua, Matricaria spp., Lamium spp. Dry weight (g m)2) 66.9 81.7 128.6 49.4 76.4 70.7 Reproductive structures m)2 6426 (79.3) 7277 (84.9) 10691 (102.8) 4231 (65.1) 4526 (66.8) 6090 (77.9)

14.08 *** (6.59) ***

* ¼ 5%, ** ¼ 1%, *** ¼ 0.1% significance level. Numbers in parentheses represent the square root of the raw data. SED refers to transformed values where appropriate (d.f. ¼ 41 and 34 for Expts 1 and 2 respectively).

competitive cultivar against S. media, whereas Maris Huntsman and Maris Widgeon were the most competitive. In Expt 2, in most circumstances, the rank order of cultivars (most to least competitive) was Maris Widgeon, Rialto, Buster, Flame, Riband and Fresco. No significant differences were obtained for the suppression of P. annua, Matricaria spp. and Lamium spp. in either experiment at any sampling occasion for any of the parameters assessed. Nevertheless, Fresco showed negligible weed suppression relative to Maris Huntsman and Maris Widgeon in both experiments (results not shown). In Expt 1, no significant differences were recorded concerning the effects of cultivar on total weed biological characteristics. The results presented here relate to Expt 2 (Table 4) and refer to the dominant species present (S. media, P. annua, Matricaria spp. and Lamium spp.) in which the effects of cultivar on dry weight and reproductive structures were evident 190 DAS at the P < 0.001 significance level. Maris Widgeon reduced total weed dry weight and reproductive structures most and was significantly different from Fresco and Flame (Table 4). Effects of crop density on vegetative characteristics of weed flora

Crop density significantly affected vegetative characteristics of individual and total weed species in both experiments. In Expt 1, significant differences (P < 0.001) were recorded 240 DAS between crop densities, such that greater suppression of the total weed flora (which was dominated at the time of assessment by

P. annua, Matricaria spp. and S. media) was observed at higher crop densities. More specifically, at the low crop density, dry weight and reproductive structures were increased by 31% and 43%, respectively, compared with medium and high crop density (Korres & FroudWilliams, 1999). A similar response was reported for individual weed species, P. annua and Matricaria spp. (Korres & Froud-Williams, 1997). Similarly, in Expt 2 crop density significantly (P < 0.05) affected all weed parameters assessed (dry weight, reproductive structures, leaf area per plant and per unit area) for S. media and Matricaria spp. 190 and 240 DAS, respectively, and dry weight and reproductive structures per plant and per unit area of Lamium spp. and P. annua 190 and 240 DAS, respectively (results not shown). Significant differences (P < 0.01, P < 0.001) were recorded for total weed dry weight and reproductive organs of plots dominated by S. media, P. annua, Matricaria spp. and Lamium spp. at the end of the growing season (Table 5). The effects of increased crop density on total weed dry weight are evident when the higher crop densities are compared with the lowest one, especially at the end of the growing season. Increased crop density resulted in decreased weed biomass (59% and 58% for the 380 and 270 plant m)2 respectively). Comparisons of crop densities of 380 and 270 against 125 plant m)2 showed significant reductions (P < 0.001) of total weed reproductive structures 240 DAS, such that reproductive structures were reduced by 42% and 24% for the high and intermediate crop densities respectively. These reductions were halved 190 DAS and differences were non-significant at 270 and European Weed Research Society Weed Research 2002 42, 417–428


Table 5 Effects of crop density on total weed vegetative characteristics at each sampling occasion in Expt 2 (mean of six cvs) Crop density (plants m)2) Sampling occasion (DAS)

125

270

380

SED

F prob.

70

Dry weight (g m)2) Reproductive structures m)2

31.9 (5.6) 1152 (2.26)

29.0 (5.3) 1075 (1.90)

24.4 (4.9) 876 (2.14)

0.48 0.48

NS NS

90


100.8 7891 (88.8)

75.1 6666 (81.6)

60.9 5062 (70.9)

9.97 4.67

** **

240


52.5 4442 (65.8)

22.2 2736 (51.5)

21.7 1387 (37.0)

4.68 5.14

*** ***

** ¼ 1%, *** ¼ 0.1% significance level. Numbers in parentheses represent square root transformed data, except for reproductive output 70 DAS where log (x + 1) transformation was carried out. SED refers to transformed values where appropriate (d.f. ¼ 34).

380 plant m)2. At the last sampling occasion, significant interactions were observed for total weed dry weight (P < 0.05), such that increased crop density of Flame and Fresco resulted in significant reductions of weed dry weight per unit area (Fig. 1).

Analysis of the weed infestation using log-linear modelling was conducted to evaluate the effects of cultivar selection, crop density and their interactions over time on the overall number of weed species and species composition. In the models used here, it is assumed that the weed population is not significantly affected by environmental conditions. Choice of cultivar did not influence total weed infestation in either experiment. Nevertheless, in Expt 2 infestation of individual weed species (P. annua and Matricaria spp.) was influenced by the choice of cultivar (P < 0.05). For example, suppression of P. annua, relative to Buster in descending order was Flame (24% more than Buster) least suppressive, Fresco (21% more than Buster), Rialto and Riband (14% more than Buster), Maris Widgeon (31% less than

Buster) most suppressive (results not shown). Likewise, for Matricaria spp. Riband was least suppressive enabling a significant (P < 0.05) increase in Matricaria spp. infestation (57%) followed by Fresco (46% increase). Flame behaved similarly to Buster, whereas Maris Widgeon and Rialto were most suppressive, reducing the density of Matricaria spp. by 3% and 8% respectively (results not shown). Results concerning the effects of crop density on weed infestation were confirmed in both experiments such that increased crop density reduced significantly (P < 0.001) the number of individual species and total weed species recorded (Figs 2 and 3). In Expt 1, reductions of crop density from High (> 180) to Medium (< 50 > 100) or Low (< 50) plants m)2 increased total weed numbers significantly (P < 0.001) throughout the growing season by 17% and 44% respectively (Fig. 2). Similarly, in Expt 2 significant reductions (P < 0.001) were observed such that at a crop density of 270 plants m)2 weed infestation was reduced by 25% and at 380 plants m)2 by 40% (Fig. 3). Inclusion of time in the models conducted for individual weed species infestation revealed a

Fig. 1 Effects of cultivar · crop density on total weed dry weight in the Expt 2 240 DAS. Vertical bars represent SED (d.f. ¼ 34).

Fig. 2 Effects of crop density on weed infestation in Expt 1 (total number of plants across six cvs. and sampling occasions). Vertical bars represent SED (d.f. ¼ 46).

Modelling weed infestation



Fig. 3 Effects of crop density on weed infestation in Expt 2 (total number of plants across six cvs. and four sampling occasions). Vertical bars represent SED (d.f. ¼ 30).

contrasting pattern concerning their duration throughout the growing season in Expt 2 (Fig. 4). More specifically, S. media and Lamium spp. reached their maximum density at 70 and 190 DAS and a significant (P < 0.001) reduction thereafter, especially for S. media. Conversely, P. annua and Matricaria spp. increased between 70 and 190 DAS with non-significant differences in their numbers between 190 and 240 DAS (maximum density) and subsequent decline (Fig. 4). Total weed infestation attained a maximum density 190 DAS in Expt 2 with significant (P < 0.001) differences between sampling occasions. More specifically, weed infestation at 190 and 240 DAS was significantly different from that at 70 and 270 DAS (Fig. 4). In Expt 2, averaged across crop densities and subplot treatments, at final harvest, significant differences (P < 0.001) were observed in weed seedling density such that Fresco was the least suppressive with 64% increase relative to Buster, whereas comparison of Buster with the other cultivars revealed that Rialto and Maris Widgeon were the most competitive (60%

Fig. 4 Changes in weed infestation of individual and total weed species in Expt 2 (total number of plants across six cvs. and three crop densities). Vertical bars represent SED (d.f. ¼ 30).

Fig. 5 Effects of cultivars on total number of weed seedlings in Expt 2 at final harvest (total number of seedlings across three crop densities and weedy subplots. Vertical bars represent SED (d.f. ¼ 72).

and 57% reduction), whereas Flame and Riband reduced seedling density by 41% and 42% respectively (Fig. 5). Increasing crop density to 270 and 380 plant m)2 decreased total weed seedling density by 36% and 53%, respectively, relative to crop density of 125 plant m)2 (results not shown). Weed biological characteristics

Strong linear relationships were observed when weed dry weight per unit area for individual (Figs 6 and 7) and total weed species (Fig. 8) were regressed against reproductive structures indicating the dependence between these two parameters, particularly towards the end of the growing season.

Discussion Effects of cultivar

Winter wheat cultivar selection is one of the most important management decisions in obtaining optimum yield; however, consideration must also be given to the value of weed suppression by the crop (Wicks et al., 1986; 1994). In this study, differences in weed suppressive abilities of wheat cultivars (for individual weed species and totalities) were apparent. Maris Huntsman and Maris Widgeon showed appreciable weed suppression. As described by Jarman & Pickett (1998), both cultivars exhibit long to very long straw length and semierect to semi-recurved flag leaf attitude. Wicks et al. (1986), Lemerle et al. (1996) and Grundy & FroudWilliams (1997) agreed that height is a major characteristic contributing to cultivar competitiveness. This aspect is associated with light penetration within the crop canopy and shading ability (Blackshaw, 1994; Seavers & Wright, 1995). European Weed Research Society Weed Research 2002 42, 417–428


Fig. 6 Relationships between reproductive structures and dry weight per unit area at 210 and 240 DAS for Expts 1 and 2, respectively, in Poa annua.

Fig. 7 Relationships between reproductive structures and dry weight per unit area at 210 and 190 DAS for Expts 1 and 2, respectively, in Stellaria media.

Fig. 8 Relationships between total reproductive structures and total dry weight per unit area at 240 and 190 DAS for Expts 1 and 2 respectively.

A negative relationship between crop height and total weed dry weight m)2 was obtained when these two variables were regressed for individual cultivars (Fig. 9). The influence of height on weed biomass production is evident, especially for Rialto and Buster, for which the fitted lines appeared to be steeper compared with those European Weed Research Society Weed Research 2002 42, 417–428

of the other cultivars, particularly Maris Widgeon. Nevertheless, the accumulated analysis of variance for the examination of significance between the slopes of fitted lines did not indicate a significant difference of cultivar · cultivar height on weed dry weight. Based on the findings of this regression analysis, height appears to


Fig. 9 Relationship between cultivars, their height and total weed dry weight 190 DAS (Expt 2).

be a trait that confers competitiveness. Besides height, Blackshaw (1994) stated that other characters such as early growth rates, tillering ability and leaf area might also affect crop:weed interactions. Accordingly, the negative effects of tillering capacity on total weed dry matter production were evident for Maris Widgeon, Riband and Rialto (Fig. 10), which exhibited greatest tillering capacity (results not shown). The above observations may indicate that cultivar competitiveness is not an absolute characteristic, but resultant of different combinations of physiological traits (height or tillering ability). It is also indicative that increased tillering capacity of winter wheat cultivars could be a useful tool in weed management. Nevertheless, Balyan et al. (1991) found that height and dry matter accumulation per unit area during crop growth were better characters than tillering capacity for increased competitive ability. A very poor relationship was obtained when crop dry weight per unit area was regressed with total weed dry weight per unit area 190 DAS (results not shown). Seavers & Wright (1995) found that compared with Maris Huntsman, Fresco had

least ground cover in November. They stated that upright cultivars produced tillers more rapidly and hence more ground cover compared with those of prostrate growth habit. This is another possible reason for the least suppressive ability of Fresco (prostrate growth habit) compared with either Maris Huntsman or Maris Widgeon (intermediate growth habit) or Buster (semi-erect growth habit). No significant differences were observed in total weed numbers due to cultivar in either experiment. Nevertheless, considering individual species, Maris Widgeon caused a significant reduction of both P. annua and Matricaria spp., in agreement with Grundy & Froud-Williams (1993) who observed a significant reduction of Matricaria recutita L. in the presence of cv. Maris Huntsman at the end of the growing season. Significantly greater weed seedling emergence occurred early in August in the presence of Fresco, whereas Maris Widgeon was one of the most suppressive cultivars. Wicks et al. (1986) stated that the most competitive cultivars early in the growing season performed best against the post-harvest weed population. Based on the assumption that the majority of weed

Fig. 10 Relationship between cultivars, their tiller numbers and total weed dry weight 190 DAS (Expt 2). European Weed Research Society Weed Research 2002 42, 417–428


seeds originated from the current year’s weed population, Maris Widgeon showed the greater impact on reproductive structures per unit area either for individual weed species or total weed reproductive structures. This may partly explain its negative effect on weed germination at the end of the growing season. Effects of crop density

The strong effects of enhanced crop density were evident in both field experiments either for individual weed species or total weed infestation for all of the weed parameters assessed. Differences in weed total dry weight were evident 190 and 240 DAS between crop densities of 125 plants m)2 and the two higher densities of 270 and 380 plants m)2, albeit no reduction in weed dry weight between the two higher densities was observed. Low and high crop density implies high and low-light environments respectively (Solbrig et al., 1980). Tollenaar et al. (1994) and Ivashchenko (1999) showed that increases in crop density of Zea mays L. (maize), Secale cereale L. (winter rye) and Raphanus sativus oleiformis L. (oil radish), respectively, were associated with great reductions of weed biomass as a consequence of reduced light transmittance. The above was confirmed in both experiments where leaf area per unit ground area at high crop densities was significantly greater than that observed at low crop density (results not shown) as a consequence of increased light interception by crop canopy at higher crop densities. It has been shown that leaf area may also influence the transmitted radiation qualitatively by changing the red ⁄ far-red ratio (Ballare et al., 1990). So the possibilities of changes of this ratio under high crop density are apparent and may also influence the results of weed:crop competition. In contrast, Ball et al. (1997) found that by increasing seeding rate in small red-lentil (Lens culinaris L.), differences in water extraction between seed rates rather than differences in canopy light interception accounted for differences in weed suppression. Grundy & Froud-Williams (1997) reported greater reductions of weed dry matter accumulation at high wheat seed rates and proposed that crop architecture might have physically restricted the growth of weed species and hence dry matter production. Increases in crop density in both experiments resulted in reduced reproductive structures in agreement with observations reported by Wilson et al. (1988). This emphasises the importance of seed rates for controlling weed seed production and hence avoiding contamination of the harvestable product and future weed infestations. It was found that weed reproductive structures are linearly related to weed biomass. Therefore, it is reasonable to assume that reductions of weed European Weed Research Society Weed Research 2002 42, 417–428

reproductive structures follow reductions of weed dry weight, although it has been shown that weeds under stressed conditions exhibit a remarkable plasticity (Watkinson, 1981). No interactions were observed in Expt 1 between cultivar and crop density concerning any of the weed parameters measured, which suggests that under these specific experimental conditions, the influence of crop density in weed:crop interference is more important. In contrast, some interactions were recorded in Expt 2 for weed dry weight m)2. Cultivars Fresco, Flame and Rialto appeared to show a greater competitive ability when their densities increased from 125 to 270 or 380 plants m)2. However, manipulation of crop density did not significantly affect the competitive ability of cultivars Maris Widgeon, Buster or Riband. This suggests that attention must be paid to cultivar selection and manipulation of seed rates for weed suppression in situations where water availability is limited, as crop density affects its availability to the crop. Samuel & Guest (1990) observed great reductions in weed dry weight of infestations dominated by P. annua, Trifolium pratense L., S. media and Lamium spp. as a result of increased seed rates in organically grown wheat, but did not observe any effects on weed population. In both experiments reported here, increases in crop density reduced weed infestation of individual species as well as total weed numbers. Greater seedling emergence at low than at high crop densities was observed at the end of the growing season. Weed biology

The production and fate of weed seeds produced by surviving plants determines changes in weed populations from year to year. The potential for population increase is conditioned largely by the number of viable seeds produced, which has been shown to be influenced by crop competition, especially for annual grass weeds (Cussans & Wilson, 1975; Moss, 1985). A positive relationship was found between weed dry weight m)2 and reproductive structures m)2 for each individual and total species in agreement with Wilson et al. (1988) and Wright (1993). Although weed biomass differed between years, the reproductive component:biomass relationship was more stable. This observation gives confidence that the reproductive component:biomass relationship would be suitable for use in population dynamics models and that dry weight itself may offer a reliable indicator of reproductive structures. Furthermore, for species with a prolonged flowering period such as S. media, the decision of when to assess seed production is a major problem (Van Acker et al., 1997); as indicated in Figs 6 and 7 with regard to later


sampling occasions for P. annua and S. media. Nevertheless, Peters & Wilson (1983) stated that later emerged weeds would produce fewer seeds in comparison with those emerging with the crop. A similarity between the magnitude of the response (growth characteristics) and the degree of weed infestation throughout the growing season was observed in Expt 2 190 DAS. This indicated parallel progress between a weed population and its biological growth characteristics. If the maximum of weed population and characteristics of reproduction were known (the maximum values in this project were achieved early in April for Expt 2) then this information could be used to guide producers’ options in integrated management systems. For example, mechanical weed control such as hoeing or intra- and interrow harrowing around this time or earlier is one cultural practice that producers can use to reduce future soil weed seedbanks (Anderson, 1993). Counts of S. media and Lamium spp. in Expt 2 peaked early in the season (70 DAS) but the plants senesced early, resulting in little weed biomass by harvest. In contrast, P. annua and Matricaria spp. achieved their maximum densities later. Wilson & Wright (1990) observed a similar pattern concerning S. media and Lamium purpureum L. and suggested that weeds in winter wheat may be categorized as early and late senescent relative to the crop. In addition, they proposed that it may be possible to identify weed groups which affect yield loss most, although Wilson (1986) observed that L. purpureum, Veronica persica Poiret and Veronica hederifolia L. did not affect winter wheat yield, and so could be given a reduced priority for control.

Conclusions Choice of cultivar has a significant role in the determination of competitive ability. Tall cultivars were more competitive to weeds than semi-dwarf or dwarf cultivars as found in the cases of Maris Huntsman, Maris Widgeon and Fresco. Nevertheless, Buster in Expt 2 showed a potential for appreciable competitiveness. It seems that cultivars with erect growth habit have an advantage compared with cultivars that exhibit a prostrate growth habit. However increases in tillering capacity or plant height are potential characteristics for enhanced crop competitiveness. Of course it is difficult for plant breeders to breed for taller plants (greater lodging than the semi-dwarf and dwarf cultivars and low harvest index). Crop competitiveness is an attribute that combines many characteristics as it is influenced by environmental conditions as well as cultural practices including seed rate (Fresco, Flame and Rialto). Crop density is a more

reliable agronomic factor compared with cultivar selection for enhanced crop competitiveness as has been shown by the two field experiments, although not always the better for achieving higher yield. Densities between 125 and 270 plants m)2 were found to be adequate for satisfactory suppression of mixed broad-leaved weed infestations. Furthermore, a combination of an appropriate seed rate with a suitable choice of cultivar of increased tillering capacity may suppress weed infestation adequately. Modelling weed population dynamics requires selection of data over a long period and a knowledge of weed biology in space and time. Incorporation of environmental factors and weed biological characteristics under specific cultural practices in combination with economic estimations of the consequences of weed control will provide adequate information about sustainable agricultural systems. Finally, if the combination of cultivar selection and crop density can suppress weed infestations and weed growth, then a significant step towards integrated weed management can be achieved.

Acknowledgements The authors would like to thank Greek State Scholarship (IKY) for sponsoring this study, the two anonymous referees and Drs J A Ivany and H M Lawson who contributed greatly to the improvement of the manuscript.

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