Unlabelled: This paper investigates the Maximum Acquisition Values (MAVs) of weeding robots and their determinants in both organic and conventional sugar beet farming in Germany. The MAV is defined in this paper as the price of the weeding robot that renders the same net profit as the current weeding methods. For our analysis, a Monte Carlo simulation approach is used, combined with empirical data and data collected from weeding robot companies. The results show that the MAVs of mechanical weeding robots for organic farming are substantially higher than that of spot spraying robots for conventional farming. Technology attributes are more influential than labour cost in determining the MAVs of weeding robots: in organic farming, technology attributes such as area capacity and weeding efficiency impact the MAVs of mechanical weeding robots the most; in conventional farming, supervision intensity and the robot's ability to save herbicides are the most influential factors. The wage rate of unskilled labour, relevant for manual weeding, plays a more important role in determining the MAVs than that of skilled labour, relevant for supervision of the robot. This implies that a shortage of seasonal workers and hence increases in the wage of low-skilled labour could be important drivers of the adoption of mechanical weeding robots. Plot characteristics such as plot size and mechanisation level only have limited impacts on the MAVs.
Supplementary Information: The online version contains supplementary material available at 10.1007/s11119-023-10015-x.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10075499 | PMC |
http://dx.doi.org/10.1007/s11119-023-10015-x | DOI Listing |
Front Plant Sci
October 2024
College of Engineering, China Agricultural University, Beijing, China.
Introduction: The competition between intra-row weeds and cultivated vegetables for nutrients is a major contributor for crop yield reduction. Compared with manual weeding, intelligent robots can improve the efficiency of weeding operations.
Methods: This study proposed a novel mechanical-laser collaborative intra-row weeding device structure.
Front Robot AI
October 2024
Machine Automation and Agricultural Robotics Laboratory, Department of Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, NE, United States.
Effective weed management is a significant challenge in agronomic crops which necessitates innovative solutions to reduce negative environmental impacts and minimize crop damage. Traditional methods often rely on indiscriminate herbicide application, which lacks precision and sustainability. To address this critical need, this study demonstrated an AI-enabled robotic system, Weeding robot, designed for targeted weed management.
View Article and Find Full Text PDFSensors (Basel)
October 2024
Department of Agriculture Technology, Faculty of Agriculture, University Putra Malaysia, Serdang 43400, Selangor, Malaysia.
The challenges and drawbacks of manual weeding and herbicide usage, such as inefficiency, high costs, time-consuming tasks, and environmental pollution, have led to a shift in the agricultural industry toward digital agriculture. The utilization of advanced robotic technologies in the process of weeding serves as prominent and symbolic proof of innovations under the umbrella of digital agriculture. Typically, robotic weeding consists of three primary phases: sensing, thinking, and acting.
View Article and Find Full Text PDFJ Environ Manage
November 2024
Department of Agricultural Economics and Rural Development, University of Göttingen, Platz der Göttinger Sieben 5, 37073, Göttingen, Germany. Electronic address:
Robotic weed control is not yet widely adopted, despite its technological availability and proven economics and sustainability in crop cultivation by replacing seasonal labor and synthetic pesticides. This impedes technologically enabled changes toward more sustainable agricultural systems. Given that adopting robotics for the weeding process requires changing existing systems, farmers' appraisals for the new and the current weeding technology may constitute barriers.
View Article and Find Full Text PDFIEEE Trans Pattern Anal Mach Intell
December 2024
The production of food, feed, fiber, and fuel is a key task of agriculture, which has to cope with many challenges in the upcoming decades, e.g., a higher demand, climate change, lack of workers, and the availability of arable land.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!