Submit to Agronomy Review for Agronomy Propose a Special Issue

Journal Browser

Application of Sensors for Mechanical Weed Control

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Agricultural Biosystem and Biological Engineering".

Deadline for manuscript submissions: closed (15 August 2021) | Viewed by 16188

Share This Special Issue

Special Issue Editor

Prof. Dr. Roland Gerhards

E-Mail Website
Guest Editor

Department of Weed Science, University of Hohenheim, Otto‐Sander‐Str. 5, 70599 Stuttgart, Germany
Interests: integrated weed management; precision farming in weed management; weed biology; weed diversity; herbicide resistance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sensor technologies have been developed to automatically guide mechanical hoes in the center between two crop rows. More sophisticated algorithms of plant species identification were implemented in weeding robots to detect weeds within crop rows and selectively control them without damaging the crop. Lately, neural networks have been trained for the classification of weed and crop species. Those information technologies have improved efficacy and selectivity of mechanical weed control. However, there is a great potential for improving and automating mechanical weed control in arable, vegetable, and permanent cropping systems. Sensor technologies can be used to vary the intensity of harrowing, support decision rules for mechanical weed control, and collect information on crop development and quality.

Prof. Dr. Roland Gerhards
Guest Editor

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

Hoeing
Harrowing
Sensors
Weed identification
Decision support systems
Neural Network
Image analysis
Side-shift control
In-row weeding

Published Papers (4 papers)

Download All Papers

Research

Jump to: Review

15 pages, 4608 KiB

Open AccessArticle

Efficacy of Various Mechanical Weeding Methods—Single and in Combination—In Terms of Different Field Conditions and Weed Densities

by Georg-Peter Naruhn, Gerassimos G. Peteinatos, Andreas F. Butz, Kurt Möller and Roland Gerhards

Agronomy 2021, 11(10), 2084; https://doi.org/10.3390/agronomy11102084 - 19 Oct 2021

Cited by 7 | Viewed by 3065

Abstract

Public awareness and environmental policies have increased interest in applying non-herbicide weed control methods in conventional farming systems. Even though mechanical weed control has been used for centuries in agricultural practice, continuous developments—both in terms of implements and automation technologies—are continuously improving the potential outcomes. Current mechanical weed control methods were evaluated for their weed control efficacy and effects on yield potential against their equivalent herbicide methods. Furthermore, not much is known about the correlation between weed control efficacy (WCE) of different mechanical methods at varying weed density levels. A total of six experiments in winter wheat (2), peas (2), and soybean (2) were carried out in the years 2018, 2019, and 2020 in southwestern Germany. Harrowing and hoeing treatments at different speeds were carried out and compared to the herbicide treatments and untreated control plots. Regarding the average WCE, the combination of harrowing and hoeing was both the strongest (82%) and the most stable (74–100%) mechanical treatment in the different weed density levels. Whereas, in average, hoeing (72%) and harrowing (71%) were on the same WCE level, but harrowing (49–82%) was more stable than hoeing (40–99%). The grain yields in winter wheat varied between 4.1 Mg∙ha⁻¹ (control) and 6.3 Mg∙ha⁻¹ (harrow), in pea between 2.8 Mg∙ha⁻¹ (hoe slow) and 5.7 Mg∙ha⁻¹ (hoe fast) and in soybean between 1.7 Mg∙ha⁻¹ (control) and 4 Mg∙ha⁻¹ (herbicide). However, there were no significant differences in most cases. The results have shown that it is not possible to pinpoint a specific type of treatment as the most appropriate method for this cultivation, across all of the different circumstances. Different field and weather conditions can heavily affect and impact the expected outcome, giving, each time, an advantage for a specific type of treatment. Full article

(This article belongs to the Special Issue Application of Sensors for Mechanical Weed Control)

► Show Figures

Figure 1

13 pages, 2774 KiB

Open AccessArticle

Comparing Sensor-Based Adjustment of Weed Harrowing Intensity with Conventional Harrowing under Heterogeneous Field Conditions

by Michael Spaeth, Matthias Schumacher and Roland Gerhards

Agronomy 2021, 11(8), 1605; https://doi.org/10.3390/agronomy11081605 - 12 Aug 2021

Cited by 5 | Viewed by 1689

Abstract

Setting the right intensity is crucial for the success of post-emergence weed harrowing in cereals. The percentage of crop soil cover (CSC) correlates with the selectivity of weed harrowing. Therefore, real-time camera-based measurements of CSC offer a novel approach to automatically adjust the intensity of harrowing. The intensity of harrowing is varied by hydraulic steering of the tine angle. Five field experiments in cereals were conducted at three locations in southwestern Germany in 2019 and 2020 to measure the effect of camera-based harrowing (2020) and conventional harrowing on weed control efficacy (WCE), crop density, and grain yield. For this purpose, pair-wise comparisons of three fixed harrowing intensities (10°, 40°, and 70° tine angle) and three predefined CSC thresholds (CSC of 10%, 20%, and 60%) were realized in randomized complete block designs. Camera-based intensity adjustment resulted in more homogeneous CSC across the whole plot (6–16% less standard deviation variation) compared to conventional fixed settings of the tine angle. Crop density, WCE, crop biomass, and grain yield were significantly higher for camera-based harrowing than for conventional harrowing. WCE and yields of all automatic adjusted harrowing treatments were equal to the herbicide control plots. Camera-based harrowing provides a robust technology for effective weed management with a lower risk of crop damage than conventional harrowing. Full article

(This article belongs to the Special Issue Application of Sensors for Mechanical Weed Control)

► Show Figures

Graphical abstract

17 pages, 27321 KiB

Open AccessEditor’s ChoiceArticle

Sensor-Based Intrarow Mechanical Weed Control in Sugar Beets with Motorized Finger Weeders

by Jannis Machleb, Gerassimos G. Peteinatos, Markus Sökefeld and Roland Gerhards

Agronomy 2021, 11(8), 1517; https://doi.org/10.3390/agronomy11081517 - 29 Jul 2021

Cited by 23 | Viewed by 3206

Abstract

The need for herbicide usage reduction and the increased interest in mechanical weed control has prompted greater attention to the development of agricultural robots for autonomous weeding in the past years. This also requires the development of suitable mechanical weeding tools. Therefore, we devised a new weeding tool for agricultural robots to perform intrarow mechanical weed control in sugar beets. A conventional finger weeder was modified and equipped with an electric motor. This allowed the rotational movement of the finger weeders independent of the forward travel speed of the tool carrier. The new tool was tested in combination with a bi-spectral camera in a two-year field trial. The camera was used to identify crop plants in the intrarow area. A controller regulated the speed of the motorized finger weeders, realizing two different setups. At the location of a sugar beet plant, the rotational speed was equal to the driving speed of the tractor. Between two sugar beet plants, the rotational speed was either increased by 40% or decreased by 40%. The intrarow weed control efficacy of this new system ranged from 87 to 91% in 2017 and from 91 to 94% in 2018. The sugar beet yields were not adversely affected by the mechanical treatments compared to the conventional herbicide application. The motorized finger weeders present an effective system for selective intrarow mechanical weeding. Certainly, mechanical weeding involves the risk of high weed infestations if the treatments are not applied properly and in a timely manner regardless of whether sensor technology is used or not. However, due to the increasing herbicide resistances and the continuing bans on herbicides, mechanical weeding strategies must be investigated further. The mechanical weeding system of the present study can contribute to the reduction of herbicide use in sugar beets and other wide row crops. Full article

(This article belongs to the Special Issue Application of Sensors for Mechanical Weed Control)

► Show Figures

Figure 1

Review

Jump to: Research

16 pages, 5904 KiB

Open AccessEditor’s ChoiceReview

Using Remote Sensing and an Unmanned Aerial System for Weed Management in Agricultural Crops: A Review

by Muhammad Huzaifah Mohd Roslim, Abdul Shukor Juraimi, Nik Norasma Che’Ya, Nursyazyla Sulaiman, Muhammad Noor Hazwan Abd Manaf, Zaid Ramli and Mst. Motmainna

Agronomy 2021, 11(9), 1809; https://doi.org/10.3390/agronomy11091809 - 08 Sep 2021

Cited by 40 | Viewed by 7563

Abstract

Weeds are unwanted plants that can reduce crop yields by competing for water, nutrients, light, space, and carbon dioxide, which need to be controlled to meet future food production requirements. The integration of drones, artificial intelligence, and various sensors, which include hyperspectral, multi-spectral, and RGB (red-green-blue), ensure the possibility of a better outcome in managing weed problems. Most of the major or minor challenges caused by weed infestation can be faced by implementing remote sensing systems in various agricultural tasks. It is a multi-disciplinary science that includes spectroscopy, optics, computer, photography, satellite launching, electronics, communication, and several other fields. Future challenges, including food security, sustainability, supply and demand, climate change, and herbicide resistance, can also be overcome by those technologies based on machine learning approaches. This review provides an overview of the potential and practical use of unmanned aerial vehicle and remote sensing techniques in weed management practices and discusses how they overcome future challenges. Full article

(This article belongs to the Special Issue Application of Sensors for Mechanical Weed Control)

► Show Figures