Periods of weed plant interference in canola

Abstract Background Fungal stem end rot disease of pitaya caused by Alternaria alternata is one of the most destructive diseases in Binh Thuan province, Vietnam. This study aimed to assess the antagonistic effects of some endophytic bacteria isolated from the weed plant (Echinochloa colonum) against A. alternata. Results A total of 19 endophytic bacteria were isolated and 5 of them presented in vitro antagonistic activity against A. alternata. Of five, strain EC80 significantly inhibited the pathogenic growth with a mean inhibition diameter of 11.88 ± 0.08 mm, while the other four (C79, EC83, EC90, and EC97) showed a weak inhibition. Interestingly, the combination of EC79 and EC80 reduced more biomass of pathogenic fungi than the single one did. EC79 showed positive results for amylase, indole acetic acid (IAA), and biofilm production, whereas EC80 presented positive capabilities for IAA and biofilm production and a negative one for amylase production. In addition, the combined filtrate of EC79 and EC80 presented non-antifungal activity on biocontrol tests in vitro, indicating that bacteria cells played a role in defending against the pathogen. Moreover, both isolates EC79 and EC80 significantly increased seedling biomass than the control. Conclusions The results suggest that those two strains in combination had the potential to be used as a biocontrol agent against A. alternata. More studies should be done in the future to evaluate their efficiency under the field conditions.

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Development of an elementary quantitative competing species model: potential guidelines for exotic/weed plant species control and ecosystem restoration programs

Ecological Engineering ◽

10.1016/j.ecoleng.2004.02.004 ◽

2004 ◽

Vol 22 (2) ◽

pp. 67-75 ◽

Cited By ~ 2

Author(s):

Lawrence J. De Chant ◽

Chris J. De Chant

Keyword(s):

Plant Species ◽

Ecosystem Restoration ◽

Model Potential ◽

Competing Species ◽

Weed Plant

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Competition of Bearded Sprangletop (Leptochloa fascicularis) with Rice (Oryza sativa)

Weed Science ◽

10.1017/s0043174500068661 ◽

1983 ◽

Vol 31 (1) ◽

pp. 120-123 ◽

Cited By ~ 31

Author(s):

Roy J. Smith

Keyword(s):

Oryza Sativa ◽

Grain Yield ◽

Paddy Rice ◽

Rice Grain ◽

Rice Seed ◽

Weed Density ◽

Weed Plant ◽

Linear Decrease ◽

Head Rice ◽

Rice Yields

Yields of drill-seeded paddy rice (Oryza sativaL. ‘Lebonnet’) at optimum stands of 215 to 270 plants/m2at Stuttgart, Arkansas, were reduced 9, 18, 20, and 36% by bearded sprangletop [Leptochloa fascicularis(Lam.) Gray] densities of 11, 22, 54, and 108 plants/m2, respectively. There was a linear decrease in rice grain yield of 21 kg/ha for each bearded sprangletop plant per square meter. Weed densities of 54 and 108 plants/m2reduced head-rice yields (whole milled kernels) and a density of 108 plants/m2reduced germination of rice seed. The number of bearded sprangletop panicles produced per weed plant decreased as the weed density increased.

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Insecticidal, biological and biochemical response of Musca domestica (Diptera: Muscidae) to some indigenous weed plant extracts

Saudi Journal of Biological Sciences ◽

10.1016/j.sjbs.2019.05.009 ◽

2020 ◽

Vol 27 (1) ◽

pp. 106-116 ◽

Cited By ~ 1

Author(s):

Attaullah ◽

Muhammad Kashif Zahoor ◽

Muhammad Asif Zahoor ◽

Muhammad Samee Mubarik ◽

Hina Rizvi ◽

...

Keyword(s):

Musca Domestica ◽

Plant Extracts ◽

Biochemical Response ◽

Weed Plant

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A Statistical Analysis for Area-of-Influence Experiments

Weed Technology ◽

10.1017/s0890037x00031444 ◽

1989 ◽

Vol 3 (1) ◽

pp. 114-121 ◽

Cited By ~ 7

Author(s):

Nicholas Jordan

Keyword(s):

Statistical Technique ◽

Crop Growth ◽

Control Measures ◽

Statistical Dependence ◽

Weed Species ◽

Competitive Effects ◽

Weed Plant ◽

Sources Of Variation ◽

Plant Effects ◽

Area Of Influence

Area-of-influence (AOI3) experiments measure the effect of a single weed on crop growth at intervals away from the weed plant. Effects of treatment variables, e.g., weed species or control measures, on the AOI of a single weed can be estimated. AOI experiments can be analyzed by regression of crop growth on distance from the weed plant, but this analysis violates an important regression assumption: independece of observations. Statistical dependence can occur among successive observations along the row because uncontrolled sources of variation are likely to act in similar ways on adjacent individuals. Multivariate analysis of variance (MANOVA) is a statistical technique that accounts for dependencies among crop growth measurements along the row. The technique tests three hypotheses: first, that different treatments cause weed AOI to differ in spatial distribution of competitive effects; second, that different treatments cause weed AOI to differ in size; and third, that the weed has an effect, i.e., crop growth near the weed differs from growth away from weed. MANOVA can be applied to most common experimental designs, e.g., randomized blocks or split plots, and can be implemented on various mainframe and microcomputer statistical packages.

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