Agronomic, Technological and Ecological Advances in Integrated Weed Management

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Weed Science and Weed Management".

Deadline for manuscript submissions: closed (20 February 2023) | Viewed by 13420

Special Issue Editors


E-Mail Website
Guest Editor
1. Amrita School of Agricultural Sciences, Amrita Vishwa Vidyapeetham, Coimbatore 641112, India
2. UWA School of Agriculture and Environment, The University of Western Australia, M082, Locked Bag 5005, Perth, WA 6001, Australia
Interests: greenhouse gas emission; herbicide resistance evolution; weed ecology; agronomy; artificial intelligence and image processing
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Agriculture Crop Production and Rural Environment, University of Thessaly, Fytokou St., 38446 Volos, Greece
Interests: weed biology and ecology; weed control in field crops, vegetables, and medicinal crops; cultural practices for weed management; herbicides; herbicide resistance; weeds as source of nutraceutical products
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Weeds are a major challenge and impediment to sustainable crop productivity and a hindrance to human efforts to feed the burgeoning population. Many agronomic, technological and ecological advancements in the area of weed management are happening extensively, and these efforts need to be integrated to evolve a sustainable weed management program. We would like to invite you to share the recent advances and success stories from your research for this Special Issue. Submissions on the following topics (but not limited to) are invited: (1) agronomic advancements in weed management; (2) technological advancements including image processing, sensors and artificial intelligence in weed management; (3) decision support tools, remote sensing and modeling in the field of weed management; (4) ecological advancements in weed management; (5) integrated approaches in weed management.

Dr. Sudheesh Manalil
Dr. Anestis Karkanis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • weed management
  • conservation agriculture
  • seed catching
  • harvest weed seed control
  • weed ecology
  • integrated weed management
  • decision support tools
  • crop model

Published Papers (6 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

28 pages, 6197 KiB  
Article
Management Effect on the Weed Control Efficiency in Double Cropping Systems
by Fruzsina Schmidt, Herwart Böhm, Rüdiger Graß, Michael Wachendorf and Hans-Peter Piepho
Agronomy 2023, 13(2), 467; https://doi.org/10.3390/agronomy13020467 - 4 Feb 2023
Cited by 1 | Viewed by 1453
Abstract
There are often negative side-effects associated with the traditional (silage) maize cropping system related to the unprotected soil surface. Reducing soil disturbance could enhance system sustainability. Yet, increased weed pressure and decreased nitrogen availability, particularly in organic agriculture, may limit the implementation of [...] Read more.
There are often negative side-effects associated with the traditional (silage) maize cropping system related to the unprotected soil surface. Reducing soil disturbance could enhance system sustainability. Yet, increased weed pressure and decreased nitrogen availability, particularly in organic agriculture, may limit the implementation of alternative management methods. Therefore, a field experiment was conducted at two distinct locations to evaluate the weed control efficiency of 18 organically managed silage maize cropping systems. Examined parameters were relative weed groundcover (GCweed) and its correlation with maize dry matter yield (DMY), relative proportion of dominant weed species (DWS) and their groups by life form (DWSgroup). Treatment factors comprised first crop (FC—winter pea, hairy vetch, and their mixtures with rye, control (sole silage maize cropping system—SCS)), management—incorporating FC use and tillage (double cropping system no-till (DCS NT), double cropping system reduced till (DCS RT), double cropped, mulched system (DCMS Roll) and SCS control), fertilization, mechanical weed control and row width (75 cm and 50 cm). The variation among environments was high, but similar patterns occurred across locations: Generally low GCweed occurred (below 28%) and, therefore, typically no correlation to maize DMY was observed. The number of crops (system), system:management and occasionally management:FC (group) influenced GCweed and DWS(group). Row width had inconsistent and/or marginal effects. Results suggest differences related to the successful inclusion of DCS and DCMS into the rotation, and to the altered soil conditions, additional physical destruction by shallow tillage operations, especially in the early season, which possibly acts through soil thermal and chemical properties, as well as light conditions. DCS RT could successfully reduce GCweed below 5%, whereas DCS NT and particularly DCMS (Mix) suffered from inadequate FC management. Improvements in DCMS may comprise the use of earlier maturing legumes, especially hairy vetch varieties, further reduction/omission of the cereal companion in the mixture and/or more destructive termination of the FC. Full article
Show Figures

Figure 1

12 pages, 2241 KiB  
Article
Dose–Response Curves of Pelargonic Acid against Summer and Winter Weeds in Central Italy
by Euro Pannacci, Daniele Ottavini, Andrea Onofri and Francesco Tei
Agronomy 2022, 12(12), 3229; https://doi.org/10.3390/agronomy12123229 - 19 Dec 2022
Cited by 4 | Viewed by 1579
Abstract
Pelargonic acid is a non-selective post-emergence contact bio-herbicide which is registered both for cropping and non-cropping uses in several countries. Dose–response curves on the efficacy of pelargonic acid against common weeds in Mediterranean areas are not available. Dose–response curves of pelargonic acid efficacy [...] Read more.
Pelargonic acid is a non-selective post-emergence contact bio-herbicide which is registered both for cropping and non-cropping uses in several countries. Dose–response curves on the efficacy of pelargonic acid against common weeds in Mediterranean areas are not available. Dose–response curves of pelargonic acid efficacy against summer and winter annual weeds were evaluated in two field experiments (winter exp. in 2019 and summer exp. in 2020) in central Italy. Pelargonic acid was applied at five doses (1.4, 2.7, 5.4, 10.9 and 21.8 kg a.i. ha−1). Data on weed density, weed dry weight, and weed ground cover were used to calculate the efficacy of pelargonic acid against winter and summer weeds. Data were subjected to a non-linear regression analysis using the logistic dose–response model. Dose of pelargonic acid required to obtain 50%, 70%, 90% and 95% weed control against each weed species (ED50, ED70, ED90 and ED95) were estimated. ED values allowed us to classify winter and summer weeds with respect to their susceptibility to pelargonic acid (ED50 values in kg ha−1 are reported in parenthesis): Kickxia spuria (2.6) (more susceptible) > Heliotropium europaeum (3.0) > Echinochloa crus-galli (3.4) > Solanum nigrum (3.6) > Stachys annua (5.3) > Papaver rhoeas (6.5) > Veronica hederifolia (10.3) > Amaranthus retroflexus (11.4) > Matricaria chamomilla (11.6) > Portulaca oleracea (18.7) > Lolium multiflorum (>21.8) (less susceptible). These findings will allow for the optimization of weed control by pelargonic acid and its use in weed management strategies, both in organic and sustainable cropping systems, under different environmental conditions. Full article
Show Figures

Figure 1

13 pages, 2570 KiB  
Article
Using Post-Emergence Herbicides in Combination with the Sowing Date to Suppress Sinapis arvensis and Silybum marianum in Durum Wheat
by Anestis Karkanis, Athanasios Angou, Despoina Athanasiadou, Kyriakos D. Giannoulis, Rodanthi Askianaki, Niki Kousi, Avgerinos Sarridis, Spyridon Souipas and Christos Karamoutis
Agronomy 2022, 12(10), 2583; https://doi.org/10.3390/agronomy12102583 - 20 Oct 2022
Cited by 6 | Viewed by 1804
Abstract
Wild mustard (Sinapis arvensis L.) and milk thistle (Silybum marianum (L.) Gaertn.) are two competitive broad-leaved weeds commonly found in cereals in Europe, while several weed species have developed resistance to the main herbicides that are applied on these crops. Thus, [...] Read more.
Wild mustard (Sinapis arvensis L.) and milk thistle (Silybum marianum (L.) Gaertn.) are two competitive broad-leaved weeds commonly found in cereals in Europe, while several weed species have developed resistance to the main herbicides that are applied on these crops. Thus, the implementation of integrated weed management (IWM) programs is of great importance. Field experiments were conducted based on a split-plot design with two factors (sowing date and herbicides). Our results showed that the density of wild mustard and milk thistle was higher in the early sowing compared to the late sowing, while the total weed density was up to 75% higher in early sowing. Moreover, the herbicides florasulam + 2.4-D and bromoxynil + 2.4-D exhibited high efficacy (>98%) against milk thistle and wild mustard, while tribenuron-methyl and florasulam + clopyralid provided greater efficacy in the late sowing compared to the early sowing. Among the four herbicides, the lowest dry biomass and grain yield of wheat were observed in tribenuron-methyl and florasulam + clopyralid, while in the weed-infested treatment, the highest values of both parameters were recorded in late sowing. Finally, the results showed that the sowing date is a cultural weed control method that should be implemented in IWM programs, since it can affect both weed density and herbicide efficacy. Full article
Show Figures

Figure 1

13 pages, 2265 KiB  
Article
Detection of Weeds Growing in Alfalfa Using Convolutional Neural Networks
by Jie Yang, Yundi Wang, Yong Chen and Jialin Yu
Agronomy 2022, 12(6), 1459; https://doi.org/10.3390/agronomy12061459 - 17 Jun 2022
Cited by 14 | Viewed by 2177
Abstract
Alfalfa (Medicago sativa L.) is used as a high-nutrient feed for animals. Weeds are a significant challenge that affects alfalfa production. Although weeds are unevenly distributed, herbicides are broadcast-applied in alfalfa fields. In this research, object detection convolutional neural networks, including Faster [...] Read more.
Alfalfa (Medicago sativa L.) is used as a high-nutrient feed for animals. Weeds are a significant challenge that affects alfalfa production. Although weeds are unevenly distributed, herbicides are broadcast-applied in alfalfa fields. In this research, object detection convolutional neural networks, including Faster R-CNN, VarifocalNet (VFNet), and You Only Look Once Version 3 (YOLOv3), were used to indiscriminately detect all weed species (1-class) and discriminately detect between broadleaves and grasses (2-class). YOLOv3 outperformed other object detection networks in detecting grass weeds. The performances of using image classification networks (GoogLeNet and VGGNet) and object detection networks (Faster R-CNN and YOLOv3) for detecting broadleaves and grasses were compared. GoogLeNet and VGGNet (F1 scores ≥ 0.98) outperformed Faster R-CNN and YOLOv3 (F1 scores ≤ 0.92). Classifying and training various broadleaf and grass weeds did not improve the performance of the neural networks for weed detection. VGGNet was the most effective neural network (F1 scores ≥ 0.99) tested to detect broadleaf and grass weeds growing in alfalfa. Future research will integrate the VGGNet into the machine vision subsystem of smart sprayers for site-specific herbicide applications. Full article
Show Figures

Figure 1

18 pages, 4637 KiB  
Article
An Alternative Tool for Intra-Row Weed Control in a High-Density Olive Orchard
by Alberto Assirelli, Corrado Ciaccia, Veronica Giorgi, Matteo Zucchini, Davide Neri and Enrico Maria Lodolini
Agronomy 2022, 12(3), 605; https://doi.org/10.3390/agronomy12030605 - 28 Feb 2022
Cited by 7 | Viewed by 2401
Abstract
In high-density olive orchards, weed control along the row is pivotal to avoid the competition between the young trees and the weeds to promote a strong vegetative growth of the olives during the first years after planting. Two different mechanical weeders were compared [...] Read more.
In high-density olive orchards, weed control along the row is pivotal to avoid the competition between the young trees and the weeds to promote a strong vegetative growth of the olives during the first years after planting. Two different mechanical weeders were compared in a high-density olive orchard (1250 trees ha−1) planted in 2019. An intra-row hoeing machine (Control) and an alternative system with a high-pressure water blast (Grass Killer) were compared. The treatments were carried out in summer and autumn. The effects of the two control systems were assessed through the weed soil coverage and indirectly through the growth of olive trees. The effect on weeds in summer was marked without showing significant differences between the applied treatments, even if the Grass Killer did not eradicate totally the weeds. In autumn, the hoeing machine showed a higher weeding capacity, even though the presence of weeds along the row treated with the high-pressure water weeder can contribute to reduce the soil moisture in wintertime. No differences were seen for the young olive tree growth. Results showed a good weeding capacity of the alternative machine, and its use can be managed in combination with other mechanical systems. Full article
Show Figures

Figure 1

12 pages, 3110 KiB  
Article
Effects of Post-Emergence Herbicides and Period of Johnsongrass (Sorghum halepense (L.) Pers.) Control on Growth and Yield of Sunflower Crops
by Anestis Karkanis, Dimitrios Nakopoulos, Charikleia Palamioti, Kyriakos D. Giannoulis, Thomas Palamiotis, Georgios Igoumenos, Spyridon Souipas, Vasiliki Liava and Nicholaos G. Danalatos
Agronomy 2022, 12(3), 581; https://doi.org/10.3390/agronomy12030581 - 26 Feb 2022
Cited by 2 | Viewed by 2599
Abstract
Sunflower is an important industrial crop since it is grown all over the world for oil production, while Johnsongrass (Sorghum halepense (L.) Pers.) is characterized by great competitiveness and can severely impair plant growth and crop productivity. Thus, a two-year field experiment [...] Read more.
Sunflower is an important industrial crop since it is grown all over the world for oil production, while Johnsongrass (Sorghum halepense (L.) Pers.) is characterized by great competitiveness and can severely impair plant growth and crop productivity. Thus, a two-year field experiment was conducted to evaluate the impact of Johnsongrass control practices on plant growth, seed yield, and oil content of sunflower crop. The results indicated that Johnsongrass competition negatively affected sunflower growth and productivity as the lowest values of height, dry biomass, seed, and oil yields were recorded at the weed-infested treatment, followed by the weed infested for 30 days after sowing. All the other treatments had a positive effect on vegetative and yield parameters. Moreover, fluazifop-p-butyl, quizalofop-p-ethyl, and the combination of fluazifop-p-butyl and imazamox effectively controlled Johnsongrass. Specifically, in 2020, the lowest dry weight of Johnsongrass was observed in the plots where fluazifop-p-butyl + imazamox were applied. Thus, the results of this study clearly showed that the use of the above-mentioned herbicides can improve the seed and oil yield of a sunflower crop by managing Johnsongrass, while the competition of this rapidly growing weed for a short period of 30 days can significantly reduce crop yield. Full article
Show Figures

Figure 1

Back to TopTop