Tolerance and Suppression of Weeds Varies among Carrot Varieties

2017 ◽  
Vol 31 (6) ◽  
pp. 897-902 ◽  
Author(s):  
Jed B. Colquhoun ◽  
Richard A. Rittmeyer ◽  
Daniel J. Heider
Keyword(s):  
Weed Management ◽  
Yield Loss ◽  
Plant Density ◽  
Control Measures ◽  
Integrated Weed Management ◽  
Future Research ◽  
Canopy Development ◽  
Stand Establishment ◽  
Carrot Plant ◽  
Vegetative Canopy

Slow carrot emergence and canopy development render the crop a poor competitor with weeds. In this study, the ability to suppress weeds and maintain yield in the presence of weeds was compared among nine carrot varieties that included those selected by plant breeders for rapid vegetative canopy development compared to traditional varieties. Two weed management treatments were compared: handweeding for 21 d after carrot seeding versus handweeding for the entire carrot season. In years and locations with low to moderate weed pressure, such as in the 2014 study, differences among carrot varieties in weed competitiveness or tolerance were less apparent and therefore less relevant. Maximum carrot yield loss to weed competition among varieties was 28% in 2014. Yield loss in the presence of weeds was 15% or less with six of the nine carrot varieties. However, when weed pressure was intense in the 2015 study, both carrot plant density and carrot canopy development were inversely related to weed biomass. Carrot yield loss in the presence of weeds ranged from 38 to 87%. Despite correcting seeding populations for differences in germination among carrot varieties, carrot stand establishment varied greatly and would likely affect subsequent weed control measures such as timely cultivation or herbicide application. Future research efforts are warranted that consider carrot stand establishment factors and their relationship with integrated weed management programs.

scholarly journals Effect of Barley Sowing Density on the Integrated Weed Management of Lolium rigidum (Annual Ryegrass) in Mediterranean Dryland: A Modeling Approach

Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1565
Author(s):  
María Belén D’Amico ◽  
Guillermo R. Chantre ◽  
Guillermo L. Calandrini ◽  
José L. González-Andújar
Keyword(s):  
Weed Management ◽  
Life Cycles ◽  
Integrated Weed Management ◽  
Future Research ◽  
Seed Removal ◽  
Weed Infestation ◽  
High Control ◽  
Weed Dynamics ◽  
The Impact

Population models are particularly helpful for understanding long-term changes in the weed dynamics associated with integrated weed management (IWM) strategies. IWM practices for controlling L. rigidum are of high importance, mainly due to its widespread resistance that precludes chemical control as a single management method. The objective of this contribution is to simulate different IWM scenarios with special emphasis on the impact of different levels of barley sowing densities on L. rigidum control. To this effect, a weed–crop population model for both L. rigidum and barley life cycles was developed. Our results point out: (i) the necessity of achieving high control efficiencies (>99%), (ii) that the increase of twice the standard sowing density of barley resulted in a reduction of 23.7% of the weed density, (iii) non-herbicide-based individual methods, such as delayed sowing and weed seed removal at harvest, proved to be inefficient for reducing drastically weed population, (iv) the implementation of at least three control tactics (seed removal, delay sowing and herbicides) is required for weed infestation eradication independently of the sowing rate, and (v) the effect of an increase in the sowing density is diluted as a more demanding weed control is reached. Future research should aim to disentangle the effect of different weed resistance levels on L. rigidum population dynamics and the required efficiencies for more sustainable IWM programs.

scholarly journals Response of Barley Genotypes to Weed Interference in Australia

Agronomy ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 99 ◽  
Author(s):  
Gulshan Mahajan ◽  
Lee Hickey ◽  
Bhagirath Singh Chauhan
Keyword(s):  
Negative Correlation ◽  
Weed Management ◽  
Field Experiments ◽  
Yield Loss ◽  
Production Systems ◽  
Relative Yield ◽  
Organic Production ◽  
Integrated Weed Management ◽  
Weed Interference ◽  
Barley Genotypes

Weed-competitive genotypes could be an important tool in integrated weed management (IWM) practices. However, weed competitiveness is often not considered a priority for breeding high-yielding cultivars. Weed-competitive ability is often evaluated based on weed-suppressive ability (WSA) and weed-tolerance ability (WTA) parameters; however, there is little information on these aspects for barley genotypes in Australia. In this study, the effects of weed interference on eight barley genotypes were assessed. Two years of field experiments were performed in a split-plot design with three replications. Yield loss due to weed interference ranged from 43% to 78%. The weed yield amongst genotypes varied from 0.5 to 1.7 Mg ha−1. Relative yield loss due to weed interference was negatively correlated with WTA and WSA. A negative correlation was also found between WSA and weed seed production (r = −0.72). Similarly, a negative correlation was found between WTA and barley yield in the weedy environment (r = −0.91). The results suggest that a high tillering ability and plant height are desirable attributes for weed competitiveness in the barley genotypes. These results also demonstrated that among the eight barley genotypes, Commander exhibited superior WSA and WTA parameters and therefore, could be used in both low- and high-production systems for weed management. Westminster had a superior WSA parameter. Therefore, it could be used for weed management in organic production systems. These results also implied that genotypic ranking on the basis of WSA and WTA could be used as an important tool in strengthening IWM programs for barley.

A Reintroduction to Integrated Weed Management

Weed Science ◽  
1996 ◽  
Vol 44 (2) ◽  
pp. 409-412 ◽  
Author(s):  
Clyde L. Elmore
Keyword(s):  
Pest Management ◽  
Weed Management ◽  
Management Practices ◽  
Farming System ◽  
Control Measures ◽  
Integrated Weed Management ◽  
Integrated Crop Management ◽  
Long Time ◽  
Management Hierarchy ◽  
Crop Management Systems

Integrated Weed Management (IWM), a long time practice by farmers has become more commonly discussed as a total weed management system. Whether an off shoot of Integrated Pest Management (IPM) or a further recognition of integrating weed control measures within the cropping and farming system, it has become more widespread. IWM is being practiced using many of the same components, from croplands to forests and rangeland. A weed management hierarchy has been developed by degree of diversity of management practices. IWM researchers and educators should invite other pest management specialists to join us in striving for Integrated Crop Management systems.

Influence of Weed Management Practices and Crop Rotation on Glyphosate-Resistant Horseweed Population Dynamics and Crop Yield

Weed Science ◽  
2007 ◽  
Vol 55 (5) ◽  
pp. 508-516 ◽  
Author(s):  
Vince M. Davis ◽  
Kevin D. Gibson ◽  
Thomas T. Bauman ◽  
Stephen C. Weller ◽  
William G. Johnson
Keyword(s):  
Population Dynamics ◽  
Crop Rotation ◽  
Crop Yield ◽  
Cover Crops ◽  
Weed Management ◽  
Management Practices ◽  
Plant Density ◽  
Management Systems ◽  
Integrated Weed Management ◽  
Rapid Decline

Horseweed is an increasingly problematic weed in soybean because of the frequent occurrence of glyphosate-resistant (GR) biotypes. The objective of this study was to determine the influence of crop rotation, winter wheat cover crops (WWCC), residual nonglyphosate herbicides, and preplant herbicide application timing on the population dynamics of GR horseweed and crop yield. A field study was conducted at a site with a moderate infestation of GR horseweed (approximately 1 plant m−2) with crop rotation (soybean–corn or soybean–soybean) as main plots and management systems as subplots. Management systems were evaluated by quantifying horseweed plant density, seedbank density, and crop yield. Crop rotation did not influence in-field horseweed or seedbank densities at any data census timing. Preplant herbicides applied in the spring were more effective at reducing horseweed plant densities than when applied in the previous fall. Spring-applied, residual herbicide systems were the most effective at reducing season long horseweed densities and protecting crop yield because horseweed in this region behaves primarily as a summer annual weed. Horseweed seedbank densities declined rapidly in the soil by an average of 76% for all systems over the first 10 mo before new seed rain. Despite rapid decline in total seedbank density, seed for GR biotypes remained in the seedbank for at least 2 yr. Therefore, to reduce the presence of GR horseweed biotypes in a local no-till weed flora, integrated weed management (IWM) systems should be developed to reduce total horseweed populations based on the knowledge that seed for GR biotypes are as persistent in the seed bank as glyphosate-sensitive (GS) biotypes.

scholarly journals Yield loss prediction for integrated weed management in direct‐seeded rice

1993 ◽  
Vol 39 (2) ◽  
pp. 175-180 ◽  
Author(s):  
A. J. Fischer ◽  
J. Lozano ◽  
A. Ramirez ◽  
L. R. Sanint
Keyword(s):  
Weed Management ◽  
Yield Loss ◽  
Integrated Weed Management ◽  
Loss Prediction ◽  
Direct Seeded

scholarly journals Drone and sensor technology for sustainable weed management: a review

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Marco Esposito ◽  
Mariano Crimaldi ◽  
Valerio Cirillo ◽  
Fabrizio Sarghini ◽  
Albino Maggio
Keyword(s):  
Weed Management ◽  
Yield Loss ◽  
Abiotic Factors ◽  
Machine Learning Techniques ◽  
Sensor Technology ◽  
Integrated Weed Management ◽  
Weed Population Dynamics ◽  
Learning Techniques ◽  
Robot Systems ◽  
Available Technology

AbstractWeeds are amongst the most impacting abiotic factors in agriculture, causing important yield loss worldwide. Integrated Weed Management coupled with the use of Unmanned Aerial Vehicles (drones), allows for Site-Specific Weed Management, which is a highly efficient methodology as well as beneficial to the environment. The identification of weed patches in a cultivated field can be achieved by combining image acquisition by drones and further processing by machine learning techniques. Specific algorithms can be trained to manage weeds removal by Autonomous Weeding Robot systems via herbicide spray or mechanical procedures. However, scientific and technical understanding of the specific goals and available technology is necessary to rapidly advance in this field. In this review, we provide an overview of precision weed control with a focus on the potential and practical use of the most advanced sensors available in the market. Much effort is needed to fully understand weed population dynamics and their competition with crops so as to implement this approach in real agricultural contexts.

Competitive ability of hybrid and open-pollinated canola (Brassica napus) with wild oat (Avena fatua)

2002 ◽  
Vol 82 (2) ◽  
pp. 473-480 ◽  
Author(s):  
E. Zand ◽  
H. J. Beckie
Keyword(s):  
Brassica Napus ◽  
Weed Management ◽  
Plant Density ◽  
Management Program ◽  
Avena Fatua ◽  
Integrated Weed Management ◽  
Wild Oat ◽  
Replacement Series ◽  
Weed Interference ◽  
High Plant Density

The competitiveness of three hybrid and three open-pollinated canola cultivars against two wild oat populations was determined under controlled environment conditions at two plant densities and five canola:wild oat ratios (100:0, 75:25, 50:50, 25:75, 0:100). Analysis of replacement series and derivation of relative crowding coefficients (RCC), based on shoot dry weight or leaf area, indicated that hybrid canola cultivars were twice as competitive than open-pollinated cultivars when weed interference was relatively high (i.e., high plant density and vigorous wild oat growth). Little difference in competitiveness among cultivar types was apparent when weed interference was lower. The results of this study suggest that hybrid canola cultivars may be best suited for use in an integrated weed management program, particularly for farmers of organic or low input cropping systems. Key words: Hybrid canola, Brassica napus, Avena fatua, replacement series, competition

Prediction of corn (Zea mays) yield loss from early observations of the relative leaf area and the relative leaf cover of weeds

Weed Science ◽  
1999 ◽  
Vol 47 (3) ◽  
pp. 297-304 ◽  
Author(s):  
Mathieu Ngouajio ◽  
Claudel Lemieux ◽  
Gilles D. Leroux
Keyword(s):  
Decision Making ◽  
Leaf Area ◽  
Weed Management ◽  
Yield Loss ◽  
Maximum Yield ◽  
Integrated Weed Management ◽  
Corn Yield ◽  
Image Analysis System ◽  
Vertical Projection ◽  
Common Lambsquarters

The relative leaf area of weeds is a good predictor of the outcome of weed-crop competition. However, this variable has not been used in decision-making tools for integrated weed management because leaf area cannot be measured quickly. A powerful image analysis system for measuring leaf cover (the vertical projection of plant canopy on the ground) has been developed and validated. This research was conducted to compare the efficiency of weed relative leaf area and relative leaf cover in predicting corn yield loss. Field studies were conducted in 1996 and 1997 using varying densities of common lambsquarters, barnyardgrass, common lambsquarters plus barnyardgrass, and a natural weed community. Corn grain yield and biomass loss varied with weed infestation type and year. Values of the relative damage coefficient of weeds (q) were smaller in 1997 compared with 1996. For both years, the relative leaf area of weeds was an adequate predictor of corn yield loss (r2varied from 0.61 to 0.92). The precision of the predictions was not influenced by the leaf area sampling period (four- or eight-leaf stage of corn). In general, smaller values ofqandm(predicted maximum yield loss) were obtained as a consequence of using the relative leaf cover of weeds in model fitting. However, percentages of variation explained by the model (from 0.67 to 0.90) were similar to values obtained with the relative leaf area. On the basis of the residual mean squares, neither of the variables could be declared superior to the other in yield loss prediction. The development of weed control decision-making tools using the relative leaf cover of weeds may require improvements prior to being used in weed management systems. Such improvements would include use of appropriate sampling and image-processing techniques, development and validation of empirical models specific to individual situations, and proper identification of the crop growth stage at which leaf cover must be assessed.

scholarly journals Herbicide Resistance: Another Hot Agronomic Trait for Plant Genome Editing

Plants ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 621
Author(s):  
Amjad Hussain ◽  
Xiao Ding ◽  
Muna Alariqi ◽  
Hakim Manghwar ◽  
Fengjiao Hui ◽  
...  
Keyword(s):  
Genome Editing ◽  
Weed Control ◽  
Herbicide Resistance ◽  
Weed Management ◽  
Crop Productivity ◽  
Control Measures ◽  
Plant Genome ◽  
Integrated Weed Management ◽  
Leading Role ◽  
The Impact

Weeds have continually interrupted crop plants since their domestication, leading to a greater yield loss compared to diseases and pests that necessitated the practice of weed control measures. The control of weeds is crucial to ensuring the availability of sufficient food for a rapidly increasing human population. Chemical weed control (herbicides) along with integrated weed management (IWM) practices can be the most effective and reliable method of weed management programs. The application of herbicides for weed control practices calls for the urgency to develop herbicide-resistant (HR) crops. Recently, genome editing tools, especially CRISPR-Cas9, have brought innovation in genome editing technology that opens up new possibilities to provide sustainable farming in modern agricultural industry. To date, several non-genetically modified (GM) HR crops have been developed through genome editing that can present a leading role to combat weed problems along with increasing crop productivity to meet increasing food demand around the world. Here, we present the chemical method of weed control, approaches for herbicide resistance development, and possible advantages and limitations of genome editing in herbicide resistance. We also discuss how genome editing would be effective in combating intensive weed problems and what would be the impact of genome-edited HR crops in agriculture.

scholarly journals Critical Period of Weed Control in Aerobic Rice

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
M. P. Anwar ◽  
A. S. Juraimi ◽  
B. Samedani ◽  
A. Puteh ◽  
A. Man
Keyword(s):  
Weed Control ◽  
Weed Management ◽  
Critical Period ◽  
Yield Loss ◽  
Field Trials ◽  
Integrated Weed Management ◽  
Aerobic Rice ◽  
View Point ◽  
Weed Interference ◽  
Economic View

Critical period of weed control is the foundation of integrated weed management and, hence, can be considered the first step to design weed control strategy. To determine critical period of weed control of aerobic rice, field trials were conducted during 2010/2011 at Universiti Putra Malaysia. A quantitative series of treatments comprising two components, (a) increasing duration of weed interference and (b) increasing length of weed-free period, were imposed. Critical period was determined through Logistic and Gompertz equations. Critical period varied between seasons; in main season, it started earlier and lasted longer, as compared to off-season. The onset of the critical period was found relatively stable between seasons, while the end was more variable. Critical period was determined as 7–49 days after seeding in off-season and 7–53 days in main season to achieve 95% of weed-free yield, and 23–40 days in off-season and 21–43 days in main season to achieve 90% of weed-free yield. Since 5% yield loss level is not practical from economic view point, a 10% yield loss may be considered excellent from economic view point. Therefore, aerobic rice should be kept weed-free during 21–43 days for better yield and higher economic return.

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