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Agronomy
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Robotic Weeding
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Robotic Weeding

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Precision and Digital Agriculture".

Deadline for manuscript submissions: closed (20 June 2022) | Viewed by 13872

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,

Robotic weeding is a new approach of site-specific weed management. It is mostly targeted at single weeds instead of larger patches of weeds. Similar to site-specific weed control, it uses modern sensor and information technologies to assess and classify crops and weed species in agricultural fields. Those sensors can be cameras, spectrometers, very precise positioning systems, and other innovative tools to determine the position of weeds. Robotic weeding includes offline and online applications for weed control. Data processing is often performed using Artificial Intelligence. Mostly physical and chemical control methods of weed control are applied with robotic weeding. Robots usually have a higher degree of automation than previous applications of site-specific weed control. However, robots do not only imply completely autonomous systems. They can also be implemented on vehicles that are driven by humans.

We invite authors to submit manuscripts on the technical development and practical performance (weed control, selectivity, etc.) of robotic weeding. However, manuscripts on the environmental and socioeconomic impact of robotic weeding systems on farming will also be appreciated. If results of greenhouse and field studies are presented in the manuscript, we expect that those experiments are repeated over time and/or in different locations. Since a lot of progress has been made in robotic weeding over the last five years and several commercial systems of robotic weeding have been introduced, reviews summarizing the progress and comparing the benefits and limitations of those systems are also welcome in the Special Issue.

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

  • Artificial Intelligence
  • weed classification
  • spot spraying
  • sensor-controlled hoeing and harrowing
  • physical weed control
  • sensor technologies

Published Papers (4 papers)

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Research

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12 pages, 2585 KiB  
Article
Effects of Tertill® Weeding Robot on Weed Abundance and Diversity
by Kristine M. Averill, Anna S. Westbrook, Laura Pineda-Bermudez, Ryan P. O’Briant, Antonio DiTommaso and Matthew R. Ryan
Agronomy 2022, 12(8), 1754; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12081754 - 26 Jul 2022
Cited by 6 | Viewed by 2763
Abstract
Robotic weed control may reduce labor requirements, soil disturbance, and amount of herbicide applied relative to non-robotic methods. Tertill® is among the first weeding robots to become commercially available. This solar-powered robot moves in a random walk, avoiding obstacles using capacitive sensors, [...] Read more.
Robotic weed control may reduce labor requirements, soil disturbance, and amount of herbicide applied relative to non-robotic methods. Tertill® is among the first weeding robots to become commercially available. This solar-powered robot moves in a random walk, avoiding obstacles using capacitive sensors, and cuts weeds with a string trimmer. We tested the effects of Tertill (two hours per week) with and without the string trimmer and hand weeding (from 3 to 5.6 min per week with a stirrup hoe) on weed communities at two field sites in Ithaca, NY. Tertill with trimmer and hand weeding provided similar levels of weed control (visual estimates averaging 2–9% ground cover at the end of the experiment, compared to 14–48% in the unweeded control). Without the string trimmer, Tertill was ineffective. Tertill did not significantly reduce monocot weed density but did reduce dicot weed density. At one site, Tertill reduced species richness and increased evenness based on density. Overall, these results suggest that Tertill can effectively remove newly emerged weed seedlings. Future research should investigate Tertill performance against more established weeds and the long-term effects of Tertill on weed community composition (e.g., possible selection for monocots and other species with low growing points). Full article
(This article belongs to the Special Issue Robotic Weeding)
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12 pages, 4397 KiB  
Article
Evaluating Sensor-Based Mechanical Weeding Combined with Pre- and Post-Emergence Herbicides for Integrated Weed Management in Cereals
by Marcus Saile, Michael Spaeth and Roland Gerhards
Agronomy 2022, 12(6), 1465; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12061465 - 18 Jun 2022
Cited by 8 | Viewed by 1905
Abstract
Due to the increasing number of herbicide-resistant weed populations and the resulting yield losses, weed control must be given high priority to ensure food security. Integrated weed management (IWM) strategies, including reduced herbicide application, sensor-guided mechanical weed control and combinations thereof are indispensable [...] Read more.
Due to the increasing number of herbicide-resistant weed populations and the resulting yield losses, weed control must be given high priority to ensure food security. Integrated weed management (IWM) strategies, including reduced herbicide application, sensor-guided mechanical weed control and combinations thereof are indispensable to achieve this goal. Therefore, this study examined combinations of pre- and post-emergence herbicide applications with sensor-based harrowing and hoeing in cereals by conducting five field experiments at two locations in Southwestern Germany from 2019 to 2021. Each experiment contained an untreated control and a single post-emergence herbicide treatment as a comparison to these IWM treatments. The effects of the different IWM approaches on weed control efficacy (WCE), crop density, and grain yield were recorded. All experiments were set up in a randomized complete block design with four repetitions. Pre-emergence herbicide application combined with one-time harrowing and subsequent hoeing (Pre-Herb + Harr + Hoe) achieved the highest WCE (100%), followed by an approach of WCE (95%) for two-times hoeing. In contrast, a single pre-emergence herbicide application achieved the worst result with an average WCE of 25%. Grain yield was equal between all treatments in between 6 t ha−1 and 10 t ha−1, except for a single pre-emergence herbicide application, which achieved a 2.5 t ha−1 higher grain yield in winter wheat in 2021 that averaged 11 t ha−1, compared to the combination of Pre-Herb + Harr + Hoe that averaged 8.5 t ha−1. The results showed that it is possible to reduce and replace herbicides while achieving equivalent yield and WCE. Full article
(This article belongs to the Special Issue Robotic Weeding)
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Review

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21 pages, 4967 KiB  
Review
Precision Chemical Weed Management Strategies: A Review and a Design of a New CNN-Based Modular Spot Sprayer
by Alicia Allmendinger, Michael Spaeth, Marcus Saile, Gerassimos G. Peteinatos and Roland Gerhards
Agronomy 2022, 12(7), 1620; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071620 - 05 Jul 2022
Cited by 26 | Viewed by 4960
Abstract
Site-specific weed control offers a great potential for herbicide savings in agricultural crops without causing yield losses and additional weed management costs in the following years. Therefore, precision weed management is an efficient tool to meet the EU targets for pesticide reduction. This [...] Read more.
Site-specific weed control offers a great potential for herbicide savings in agricultural crops without causing yield losses and additional weed management costs in the following years. Therefore, precision weed management is an efficient tool to meet the EU targets for pesticide reduction. This review summarizes different commercial technologies and prototypes for precision patch spraying and spot spraying. All the presented technologies have in common that they consist of three essential parts. (1) Sensors and classifiers for weed/crop detection, (2) Decision algorithms to decide whether weed control is needed and to determine a suitable type and rate of herbicide. Usually, decision algorithms are installed on a controller and (3) a precise sprayer with boom section control or single nozzle control. One point that differs between some of the techniques is the way the decision algorithms classify. They are based on different approaches. Green vegetation can be differentiated from soil and crop residues based on spectral information in the visible and near-infrared wavebands (“Green on Brown”). Those sensors can be applied for real-time on/off control of single nozzles to control weeds before sowing after conservation tillage and in the inter-row area of crops. More sophisticated imaging algorithms are used to classify weeds in crops (“Green on Green”). This paper will focus on Convolutional Neural Networks (CNN) for plant species identification. Alternatively, the position of each crop can be recorded during sowing/planting and afterward herbicides can be targeted to single weeds or larger patches of weeds if the economic weed threshold is exceeded. With a standardized protocol of data communication between sensor, controller and sprayer, the user can combine different sensors with different sprayers. In this review, an ISOBUS communication protocol is presented for a spot sprayer. Precision chemical weed control can be realized with tractor-mounted sprayers and autonomous robots. Commercial systems for both classes will be introduced and their economic and environmental benefits and limitations will be highlighted. Farmers ask for robust systems with less need for maintenance and flexible application in different crops. Full article
(This article belongs to the Special Issue Robotic Weeding)
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10 pages, 1932 KiB  
Review
Weed Management in Ridge Tillage Systems—A Review
by Oyebanji Alagbo, Michael Spaeth, Marcus Saile, Matthias Schumacher and Roland Gerhards
Agronomy 2022, 12(4), 910; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12040910 - 10 Apr 2022
Cited by 4 | Viewed by 3455
Abstract
Although different modifications of ridge tillage (RT) systems exist in different regions around the world, the positive impacts of RT on crop yields and weed management are quite similar. This review gives a comprehensive summary of different forms of RT and highlights the [...] Read more.
Although different modifications of ridge tillage (RT) systems exist in different regions around the world, the positive impacts of RT on crop yields and weed management are quite similar. This review gives a comprehensive summary of different forms of RT and highlights the benefits of RT for crop growth, mainly due to better access to soil moisture, nutrients and light. In temperate areas, RT can accelerate crop emergence because soil temperature is usually higher on the ridge. These stimulating effects increase crop competitiveness against weeds especially in the early period of crop development until canopy closure. RT with crops placed on the top of ridges can also be used for automatically guiding inter-row hoes and intra-row band sprayers. The ridges can replace automatic vision control systems for hoeing and band spraying, which are needed for precise weeding in conventional flat seedbeds. Therefore, RT can be considered a possible platform for smart/robotic weeding. This paper introduces a new RT system using real-time kinematic (RTK) global satellite navigation systems (GNSS) for the ridging and seeding of maize and soybean on top of recompacted ridges. Straight ridges with precise positioning data were used to guide mechanical weeding elements precisely along the crop rows. Simultaneously, weeds in the valleys were suppressed by living mulches. Field experiments with this new technology in maize showed 85.5% weed dry biomass suppression compared to an untreated control and a slightly higher weed control efficacy than mechanical weeding in flat seedbeds. Full article
(This article belongs to the Special Issue Robotic Weeding)
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