Murdannia nudiflora (doveweed).

2021 ◽  
Author(s):  
Julissa Rojas-Sandoval
Keyword(s):  
South East Asia ◽  
Agricultural Crops ◽  
Soil Drainage ◽  
Weed Species ◽  
Invasive Weed ◽  
Land Preparation ◽  
Agricultural Areas ◽  
Murdannia Nudiflora ◽  
Near Future ◽  
Specialist Group

Abstract M. nudiflora is classified as one of the world's worst weeds by Holm et al. (1977), infesting no less than 16 crops in 23 countries. It is a major weed species in rice and other crops (Moody, 1989), and is a moderately invasive weed species both in agricultural crops and non-agricultural areas in South and South-east Asia (Waterhouse, 1993). Its special ability to root easily at the nodes, propagating clonally through cut stems and dispersal during tillage and land preparation make this weed difficult to control. This trait coupled with its ability to adapt and survive a wide ecological window of soil types, pH, moisture availability and soil drainage makes M. nudiflora a weed to watch for potential spread into new areas in near future, and a species under the 'alert list' by the Invasive Species Specialist Group. Oliveira Pellegrini et al. (2016) recognize M. nudiflora as one of two Murdannia species invasive in the Neotropics.

scholarly journals Effect of Herbicides on the Management of the Invasive Weed Solanum rostratum Dunal (Solanaceae)

Plants ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 284
Author(s):  
Jackline Abu-Nassar ◽  
Maor Matzrafi
Keyword(s):  
Growth Stage ◽  
Late Summer ◽  
Early Spring ◽  
Growth Stages ◽  
Weed Species ◽  
Invasive Weed ◽  
Solanum Rostratum ◽  
Stage 4 ◽  
Chemical Solutions ◽  
Late Growth

Solanum rostratum Dunal is an invasive weed species that invaded Israel in the 1950s. The weed appears in several germination flashes, from early spring until late summer. Recently, an increase in its distribution range was observed, alongside the identification of new populations in the northern part of Israel. This study aimed to investigate the efficacy of herbicide application for the control of S. rostratum using two field populations originated from the Golan Heights and the Jezreel Valley. While minor differences in herbicide efficacy were recorded between populations, plant growth stage had a significant effect on herbicide response. Carfentrazone-ethyl was found to be highly effective in controlling plants at both early and late growth stages. Metribuzin, oxadiazon, oxyfluorfen and tembutrione showed reduced efficacy when applied at later growth stage (8–9 cm height), as compared to the application at an early growth stage (4–5 cm height). Tank mixes of oxadiazon and oxyfluorfen with different concentrations of surfactant improved later growth stage plant control. Taken together, our study highlights several herbicides that can improve weed control and may be used as chemical solutions alongside diversified crop rotation options. Thus, they may aid in preventing the spread and further buildup of S. rostratum field populations.

scholarly journals The Effect of Different Soil Tillage Systems and Crop Residues on the Composition of Weed Communities

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1276
Author(s):  
Vaida Steponavičienė ◽  
Aušra Marcinkevičienė ◽  
Lina Marija Butkevičienė ◽  
Lina Skinulienė ◽  
Vaclovas Bogužas
Keyword(s):  
Soil Ph ◽  
Crop Residues ◽  
Soil Tillage ◽  
Reduced Tillage ◽  
Plant Residues ◽  
No Tillage ◽  
Agricultural Crops ◽  
Weed Species ◽  
Tillage Systems ◽  
Weed Communities

The composition of weed communities in agricultural crops is dependent on soil properties and the applied agronomic practices. The current study determined the effect of different tillage systems and crop residue on the soil weed community composition. The research programme encompassed 2013–2015 in a long-term field experiment located in the Experimental Station of Vytautas Magnus University in Lithuania. The soil type in the experimental field was qualified as Endocalcaric Stagnosol (Aric, Drainic, Ruptic, Amphisiltic). Weeds were categorised into communities according to soil pH, nitrogen and moisture indicators. The results of investigations were grouped using cluster analysis. Agricultural crops were dominated by different weed species depending on the soil pH and moisture. Weed species were relatively more frequent indicating nitrogen-rich and very nitrogen-rich soils. In the reduced tillage and no-tillage systems, an increase in the abundance of weed species indicating moderate acidity and low acidity, moderately wet and wet, nitrogen-rich and very nitrogen-rich soils was observed. The application of plant residues decreased the weed species abundance. In the reduced tillage and no-tillage systems, the quantitative distribution of weed was often uneven. By evaluating the association of weed communities with groups of different tillage systems with or without plant residues, their control can be optimised.

scholarly journals Competitive analysis of soybean and sudangrass using replacement series design

Revista CERES ◽  
2016 ◽  
Vol 63 (5) ◽  
pp. 668-675
Author(s):  
Mauro Antônio Rizzardi ◽  
Alana Cristina Dorneles Wandscheer ◽  
Andrea Ferreira Hoffmann
Keyword(s):  
Competitive Analysis ◽  
Dry Matter ◽  
Rio Grande ◽  
Agricultural Crops ◽  
Rio Grande Do Sul ◽  
Replacement Series ◽  
Series Design ◽  
Randomized Design ◽  
Completely Randomized Design ◽  
Agricultural Areas

ABSTRACT Competition is the best known form of direct interference of weeds on agricultural crops. However, there is relatively little information on the competition of the weed sudangrass on soybean, which has been common in agricultural areas in the southern of Rio Grande do Sul. The objective of this study was to evaluate the competition between sudangrass and soybeans using replacement series experiments. The experiment was carried out in a greenhouse in a completely randomized design with four replications. The treatments consisted of soybean and sudangrass associations. The experimental units were 8-L plastic pots, in the proportions 0: 8, 2: 6, 4: 4, 6: 2, 8: 0, corresponding to 0, 25, 50, 75 and 100% of the crop and weed respectively. Shoot, root and total dry matter and plant height were analyzed through diagrams applied to replacement series and competitive indices. Soybean showed competitive superiority in coexistence with sudangrass in relation to shoot, root and total dry matter. The intraspecific competition was more significant for the crop and inter-specific competition was more important for the weed.

scholarly journals Weed Management Potentials of Identified Invasive Weed Species

2015 ◽  
Vol 22 (1) ◽  
Author(s):  
Annabella T. Carcusia ◽  
Pet Roey L. Pascual ◽  
James Francienne J. Rosit
Keyword(s):  
Weed Management ◽  
Germination Rate ◽  
Cyperus Rotundus ◽  
Conyza Canadensis ◽  
Mimosa Pudica ◽  
Chromolaena Odorata ◽  
Weed Species ◽  
Invasive Weed ◽  
Percent Germination ◽  
Percent Mortality

Synthetic herbicide, the most popular weed control, causes environmental hazards. The use of allelopathy in controlling weeds is a possible alternative for sustainable weed management. The study was conducted to determine the allelopathic potentials of identified invasive weed species in terms of percent and rate of germination, plant height, length of leaves and roots and percent mortality of grasses, sedges, and broadleaves. The treatments were: T0-Pre/Post-emergence Herbicide, T1Tap Water, T2-Mimosa pudica extract,T3-Lantana camara extract,T4-Chromolaena odorata extract. These were compared according to their effects on Cenchrus spinifex, Conyza canadensis, Impatiens wallerana and Cyperus rotundus. Data were analyzed using Analysis of Variance (ANOVA) for Completely Randomized Design. A further test was done using Duncans Multiple Range Test (DMRT). For germination, Lantana camara is effective in reducing the percent germination and prolonging germination rate of most common weed species. On the other hand, Chromolaena odorata is effective in reducing the percent germination and prolonging the germination rate of Impatiens wallerana, while Mimosa pudica was effective against Cenchrus spinifex and Cyperus rotundus. For growth and development, Mimosa pudica was found to be the most effective in all common weed species, except for Cyperus rotundus where Chromolaena odorata was most effective on reducing the length of leaves and roots, and above ground fresh weight. Furthermore, Chromolaena odorata was found effective against both Cyperus rotundus and Conyza canadensis while Mimosa pudica was effective against Cenchrus spinifex in terms of percent mortality. Thus, such potential of invasive weed species for weed management should be utilized. 

L-DONAX, a growth model of the invasive weed species, Arundo donax L.

2007 ◽  
Vol 87 (4) ◽  
pp. 275-284 ◽  
Author(s):  
David Thornby ◽  
David Spencer ◽  
Jim Hanan ◽  
Anna Sher
Keyword(s):  
Growth Model ◽  
Arundo Donax ◽  
Weed Species ◽  
Invasive Weed ◽  
Arundo Donax L

Detection of grassy weeds in bermudagrass with deep convolutional neural networks

Weed Science ◽  
2020 ◽  
Vol 68 (5) ◽  
pp. 545-552
Author(s):  
Jialin Yu ◽  
Arnold W. Schumann ◽  
Shaun M. Sharpe ◽  
Xuehan Li ◽  
Nathan S. Boyd
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Cynodon Dactylon ◽  
Plant Morphology ◽  
Weed Species ◽  
Deep Convolutional Neural Networks ◽  
Control Cost ◽  
Weed Density ◽  
Murdannia Nudiflora ◽  
Vision Detection

AbstractSpot spraying POST herbicides is an effective approach to reduce herbicide input and weed control cost. Machine vision detection of grass or grass-like weeds in turfgrass systems is a challenging task due to the similarity in plant morphology. In this work, we explored the feasibility of using image classification with deep convolutional neural networks (DCNN), including AlexNet, GoogLeNet, and VGGNet, for detection of crabgrass species (Digitaria spp.), doveweed [Murdannia nudiflora (L.) Brenan], dallisgrass (Paspalum dilatatum Poir.), and tropical signalgrass [Urochloa distachya (L.) T.Q. Nguyen] in bermudagrass [Cynodon dactylon (L.) Pers.]. VGGNet generally outperformed AlexNet and GoogLeNet in detecting selected grassy weeds. For detection of P. dilatatum, VGGNet achieved high F1 scores (≥0.97) and recall values (≥0.99). A single VGGNet model exhibited high F1 scores (≥0.93) and recall values (1.00) that reliably detected Digitaria spp., M. nudiflora, P. dilatatum, and U. distachya. Low weed density reduced the recall values of AlexNet at detecting all weed species and GoogLeNet at detecting Digitaria spp. In comparison, VGGNet achieved excellent performances (overall accuracy = 1.00) at detecting all weed species in both high and low weed-density scenarios. These results demonstrate the feasibility of using DCNN for detection of grass or grass-like weeds in turfgrass systems.

scholarly journals Supporting Urban Weed Biosecurity Programs with Remote Sensing

2020 ◽  
Vol 12 (12) ◽  
pp. 2007
Author(s):  
Kathryn Sheffield ◽  
Tony Dugdale
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Data Availability ◽  
Surveillance Program ◽  
Urban Landscapes ◽  
Weed Species ◽  
Species Introduction ◽  
Weed Detection ◽  
Invasive Weed ◽  
Detection Rates

Weeds can impact many ecosystems, including natural, urban and agricultural environments. This paper discusses core weed biosecurity program concepts and considerations for urban and peri-urban areas from a remote sensing perspective and reviews the contribution of remote sensing to weed detection and management in these environments. Urban and peri-urban landscapes are typically heterogenous ecosystems with a variety of vectors for invasive weed species introduction and dispersal. This diversity requires agile systems to support landscape-scale detection and monitoring, while accommodating more site-specific management and eradication goals. The integration of remote sensing technologies within biosecurity programs presents an opportunity to improve weed detection rates, the timeliness of surveillance, distribution and monitoring data availability, and the cost-effectiveness of surveillance and eradication efforts. A framework (the Weed Aerial Surveillance Program) is presented to support a structured approach to integrating multiple remote sensing technologies into urban and peri-urban weed biosecurity and invasive species management efforts. It is designed to support the translation of remote sensing science into operational management outcomes and promote more effective use of remote sensing technologies within biosecurity programs.

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