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Introduction
Successful and effective farming has always been concerned with collecting data on the processes involved to ensure that the resources are used in the most efficient way possible. Today, it has become commonplace to use technological tools to determine whether the relevant processes are taking place smoothly. For instance, drones that have the capacity to communicate with satellites can fly through the fields and collect data, while wifi-enable moisture sensors can enable farmers to preserve more water resources only through watering the parts of the fields that need it. Thus, there are many challenges of farming that technologies can potentially solve. Ranging from the aging farming workforce to climate change, there are new technologies that can potentially help farmers reduce costs while also boosting efficiency, and agricultural robots are one of the leading solutions. They offer the needed level of flexibility and quality improvement that is not often available through human labor. Moreover, robotic technologies are continuously changing and improving, thus offering farmers the most advanced versions that could be integrated into farming operations. Therefore, the production and use of robotic technologies should be allowed and celebrated in farming.
Background on Robotics Use in Agriculture
Today, robotic technologies have advanced significantly, with a range of new devices being introduced to the market. For example, robotic fruit pickers are no longer clumsy and bulky and can be used to pick delicate vegetables or fruit, such as strawberries. When there are not enough workers to continue picking every berry that a plant produces throughout the growing seasons, new nimble robots can solve that problem. The picker robot Rubion produced by Octinion is of the latest technologies in this area, with the possibility to pluck berries continuously without the need for increased physical labor (Lallensack). Apart from robot fruit pickers, weed pullers have also become available due to the overarching need for farmers to tackle the persistent issue of weeds. New weed pulling robots have become so advanced that they are capable of not disturbing the soil through tillage, especially the herbicide use has caused weeds to be more resistant to chemicals and are harder to handle. FarmWises weeding robots combine the latest developments in machine learning and mechanical engineering to enable farmers to cover all of their weeding needs.
In addition to robot-pickers and weed pullers, small rover-like bots have got to fields, and, through light detecting and ranging technology, it has become possible to collect relevant data from fields hard-to-reach understory (Lallensack). For example, TerraSentia, developed by the University of Illinois, has been designed for collecting data on the health of plants, their physiology, as well as a stress response. In addition, the robots creators are working on programming the bot to measure the health of young plants, corn ear height, plant biomass, as well as the capability of detecting and identifying diseases and abiotic stresses. Drones have also been widely used in agriculture for offering immediate insights to diagnose and correct agronomic, disease, and pest concerns (Lallensack). The appeal of using drones in agriculture is concerned with the capacity to get precise data about field sections and even plans individually. Besides, in the future, drones can be used for analyzing soil, planting, spraying crops, irrigation, and further relevant information.
Another significant improvement that robotics offer to agriculture pertains to the availability of farming exoskeletons. Their emergence has been attributed to the fact that the population of farmers is getting older, with an average farmer being between 50 and 58 years old (Lallensack). The aging workforce is a significant issue in the long term, especially in medium or small-sized farms, in which the lack of a generational labor stream reduced the number of the available workforce (Lallensack). However, scientists have developed wearable exoskeletons or supersuits that ease the pressure on farmers backs and knees, such as the inventions at Virginia Tech. Also, a research team at the university is working on a robotic glove to help farmers with arthritis so they can engage in workless painfully before retiring (Lallensack). The goal of such inventions is to allow farmers not to work longer but rather enable them to continue doing what they love doing while also staying healthy.
Increased Farming Efficiency
Considering the wide availability of robotics solutions that can be used in the fields, it becomes clear that the technologies offer a range of benefits to agriculture. With the global demand for increased food resources, the speed and consistency with which robots can perform will allow farmers to deliver products quickly and efficiently (Saiz-Rubio and Rovira- Más 3). An example of the improvement in this area is the University of Cambridge vegetable-picking robot that uses machine learning for harnessing iceberg lettuce, with the technology potentially being used for tackling labor shortages and reducing food waste (Birrel et al. 230). The robot can identify the target crop within its vision field, determine whether a particular plant is healthy and can be picked, and only then cuts the lettuce from the rest of the plant without crushing it. It is possible to reduce waste with the help of such harvesting technologies because of the benefits of machine learning (Birrel et al. 225). Specifically, because machine learning facilitates the robots recognition when a specific plant is ready to be harvested, it targets only ripe vegetables. In turn, this results in lesser quantities of vegetables or fruits being discarded because they are not ready to be sold or consumed.
Increased Health and Safety of Production Operators and the Public
Agriculture has been continuously challenged by the use of pesticides, which have been shown to threaten farmers safety (European Parliament Directorate-General for External Policies). According to the study by Gonzalez-de-Santos et al., robots such as multi-robot systems can be widely used to perform pest control tasks, while individual robots can also be used (590). Canopy sprayers can be independently used in agricultural works autonomously as they integrate perception and decision, and action to improve the system of pest administration and reduce farmers exposure to harmful chemicals (Gonzalez-de-Santos et al. 599). For instance, the smart sprayer developed with the integration of the Central Direct-Injection Pesticide System has shown to achieve variable rate application (VRA) through spraying the carrier at a pre-identified continuous flow while the concentration of pesticide is varied as needed (Gonzalez-de-Santos et al. 598). The benefit of such technologies is that the implementation of the pest administration processes can help monitor the applied concentration of the chemicals and the possibility to generate maps of pesticide use for improving data analysis.
The Precision of Weed Control
Another benefit of robots use in agriculture, as illustrated in the example of FarmWises weeding robots, is the use of independent weeding systems that have shown great potential to alleviate the current dependency on agrochemicals such as herbicides and pesticides, thus reducing environmental pollution and improving sustainability (Wu et al. 2). Besides, such robots can help introduce weed control systems that can detect, track, and treat weeds in real-time. The devices have intra- and inter-camera tracking for weed identification and increasing the accuracy and robustness of weed estimates. Because the robots allow for the collecting of a wide variety of data, it becomes easier to facilitate predictive control regarding the use of the weeding tools based on the collected data. Even though robotic weeding machines have been criticized for their limitations in differentiating crops from weeds, current research is advancing in the area of machine learning (Steward et al. 6). The advancements enable robots to learn the specific features of plants to be effective in distinguishing crop plants from weeds and reduce errors in the remote weeding process (Steward et al. 9). Overall, enabling robots to make decisions in the context of uncertain field environments is an open area of research, which is expected to widen the application of robots in agriculture.
Reduction of Greenhouse Gases
When it comes to the use of robotic technologies in agriculture, considering its influence on reducing farmings carbon footprint (Association for Advancing Automation). According to Darby, with the help of the latest technologies such as drones, it has become possible to reduce the amount of herbicide for spraying plants by 99.9% as the machines can apply microdots on plants directly. In addition, 5W lasers can zap unwanted plants, thus later reducing the need for weeding. Another way in which robots positively impact greenhouse gas emissions in farming is that they are electricity-powered, while tractors use diesel fuel, which is a significant source of carbon emissions (Darby). Thus, using robots reduces the energy used in cultivation by around 90% (Brown). The reorganization of land use through the application of flexible and efficient drones and robots to attend to small areas is another benefit to sustainability. Such an approach allows to arrange appropriate land use in certain landscapes to reduce the pressure associated with pests and diseases, thus helping to cut the use of energy and, as a result, reducing carbon emissions (Brown). Overall, advances in technologies have reinforced drones and robots with a wide range of data from satellites, which can be used for continuous data analysis and the quality improvement of procedures. Low-cost and on-demand advice for troubleshooting the quality of crops and the recognition of issues that impact their growth can be accessed quickly, thus facilitating the increased efficiency of farming and reduced use of energy.
Conclusion
To conclude, robotic technologies have wide potential to be used in the agricultural sector due to the multi-dimensional nature of their applications as well as the possibilities for ongoing improvement. Ranging from autonomous weeding robots to exoskeletons, the latest advancements in robotics increase the capacity of the efficiency in agriculture while also considering the long-term impact of farming on the environment as well as the health and safety of both farmers and populations they aim to supply with fresh and high-quality produce. Furthermore, the capacity for research and development presents open opportunities for advancement based on emerging trends and changing needs of the industry.
References
Association for Advancing Automation. Cultivating Robotics and AI for Sustainable Agriculture. Automate, 2019. Web.
Birrell, Simon, et al. A Field-Tested Robotic Harvesting System for Iceberg Lettuce. Journal of Field Robotics, vol. 37, no. 2, 2020, pp. 225-245.
Brown, Mike. Climate Change: Robots on Farms Could Fight Emissions and Grow More Food. Inverse, 2019. Web.
Darby, Megan. Can Robots Cut Farmings Carbon Footprint? Climate Change News, 2016. Web.
European Parliament Directorate-General for External Policies. The use of Pesticides in Developing Countries and their Impact on Health and the Right to Food. Europarl, 2021. Web.
Gonzalez-de-Santos, Pablo, et al. Fleets of Robots for Environmentally-Safe Pest Control in Agriculture. Precision Agriculture, vol. 18, 2016, pp. 574-614.
Lallensack, Rachael. Five Roles Robots Will Play in the Future of Farming. Smithsonianmag, 2019. Web.
Saiz-Rubio, Verónica, and Francisco Rovira- Más. From Smart Farming towards Agriculture 5.0: A Review on Crop Data Management. Agronomy, vol. 10, 2020, 1-21. Web.
Steward, Brian, et al. The Use of Agricultural Robots in Weed Management and Control. Agricultural and Biosystems Engineering Publications, 2019. Web.
Wu, Xiaolong, et al. Robotic Weed Control Using Automated Weed and Crop Classification. HAL Archives, 2020. Web.
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