Robots addressing agricultural labour shortages and environmental issues

Purpose The rapid advancement of Generative Artificial Intelligence (Gen-AI) offers transformative opportunities for enhancing digital competence and management quality in small and medium-sized enterprises (SMEs). Given the challenges of a Volatile, Uncertain, Complex and Ambiguous (VUCA) business environment, SMEs face risks of losing competitive advantages to larger corporations. This study aims to explore Gen-AI trends and identify strategies that can support SMEs in building digital resilience and operational efficiency. Design/methodology/approach Through text analysis of patent data and using Gen-AI technology, this research examines potential AI applications to address SME challenges, such as labor shortages, productivity declines and operational inefficiencies. The study uses topic modeling and an OS-matrix framework to analyze trends in Gen-AI patents, aligning technological developments with SME-specific needs. Findings The study finds that Gen-AI technologies, such as automated content creation and predictive analytics, provide targeted solutions for key SME challenges. The OS-matrix framework reveals that specific Gen-AI applications can enhance SMEs’ adaptability and competitive positioning in dynamic markets. Research limitations/implications While this research underscores the potential of Gen-AI for SME digital transformation, limitations include a reliance on patent data and a lack of consideration of various industrial features of SMEs. Future research should expand data sources and apply findings across diverse SME sectors. Originality/value This study contributes insights by mapping Gen-AI advancements to SME needs under VUCA conditions. Therefore, integrating topic modeling with OS-matrix for aligning Gen-AI technologies to SME operational challenges, offers a strategic framework for digital adoption.

The COVID-19 pandemic has garnered public attention to Canada’s food security. Access to a safe, stable, and high quality food supply is often taken for granted by Canadians but it is one of the key roles that our agricultural industry serves and underlines why it is designated an essential service. Despite the federal government’s assurance that our nation’s food supply remains stable, concerns have been mounting from both consumers and the agricultural industry that disruptions in the food supply chain will cause food insecurity and severe economic distress. As a whole, Canada’s agri-food industry is well-positioned to adapt to the present crisis and continue supplying domestic and export markets. However, this does not mean that our food system is impermeable to disruption. In fact, challenges caused by COVID-19 have highlighted vulnerabilities in the food supply chain. Labour shortages, major shifts in consumer demand, and the slowdowns/closures at processing plants have already exacerbated food insecurity among Canadians and increased financial pressure on primary producers. As the foundation of the food supply chain, Canadian farmers are key to its stability. As many farms were experiencing severe economic hardship prior to the pandemic, the challenges of market uncertainty and increased production costs put these operations at greater financial risk. Policy action will be key to ensure the short and long-term viability of our primary industry and maintain the capacity to meet domestic and export market demands. Canada is still in the early stages of crisis management but government support of Canadian agriculture has been largely inadequate in alleviating the financial impact on farmers. The Canadian government must take immediate steps to alleviate the financial burden on primary producers, ensure export markets remain open and free from trade barriers, and commit to establishing a long-term agri-food strategy and action plan.

Climate change poses a significant challenge to food security. Several traditional approaches are available to prevent food insecurity in climate change scenarios, such as modifications in crop practices, altering field management systems, and climate-smart farming measures. Recently, precision agriculture practices are becoming a more popular way of farming that might help to overcome climate risk and reduce food insecurity. Precision agriculture is a tool for monitoring the food supply chain and managing both the amount and quality of agricultural products. Thus, this work seeks to synthesize and discuss the research related to the importance of a precision agriculture system in preventing food insecurity in the context of a developing countries such as Pakistan. The study is based on the narrative literature review.

In this chapter is presented part of the results of a project of the Greek Ministry of Rural Development and Foods (MRDF). This project aimed at the investigation of the freshwater quality (surface and groundwater) in River Water Basins EL07 and ELO4 located in Sterea Hellas, central Greece. This includes the identification of pollution sources as well as the proposal of measures for protection and restoration of water quality, according to the provisions of Community Directive 2000/60 and national regulations. The water properties discussed in this chapter are pH, electrical conductivity, and the inorganic nitrogen ions nitrite, nitrate, and ammonium. The entire area was divided into 11 catchments from which, for two consecutive years (2017–2018), water samples were taken at specified intervals from rivers, lakes, canals, and wells. These samples were analyzed in situ and in the laboratory, evaluated as to their suitability for drinking and irrigation, according to European Union and national regulations. The values of the parameters studied ranged widely among rivers, lakes, groundwater, and drainage canals, reflecting the various prevailing conditions in the different water sources and the special characteristics of the sampling positions. The median values of all the properties studied are lying within the normal and acceptable levels. However, in some places, extreme values, unacceptable for any use were recorded. The pH was higher in lake water, followed by rivers, canals, and groundwaters; electrical conductivity was found to be higher in river and canal waters, followed by canals and groundwaters; nitrite was higher in groundwaters followed by canals, rivers, and lake waters, while nitrate was higher in groundwaters followed by all other categories, and ammonium was higher in canals, followed by lakes, rivers, and groundwaters. The sources of contamination on a case-by-case basis appear to be anthropogenic, such as poor agricultural practices and, in particular, unsound management of inputs (fertilizers and pesticides), the dumping into drainage canals of untreated municipal or/and industrial waste, livestock farming (as it was found in the catchments, Sperceios – C1, Kifisos – C5, and Asopos – C6). And there are natural sources, such as seawater intrusion and the chemical composition of the rocks of the study area (especially in the catchments: Sperceios – C1, Amfissa – C4, Messapios-Lilantas – C8, Nireas-Kireas-Voudoros-Kimasi – C9, Kallas – C10). The most significant suggested measurement of water contamination are the tracing of contamination sources to identify their origin (agricultural, livestock, urban, industrial), the implementation of good agricultural practices (especially in applying appropriate irrigation methods that reduce nutrient leaching into the aquifer), and the estimation of the nutrient needs by soil and plant analysis or by using precision agriculture practices, both of which permit the differentiation of the amount of nitrogen fertilizers needs by taking into account the significant variability of the soil properties. Furthermore, suggestions include the continuous monitoring of surface and groundwater through certain environmental indicators (for example nitrate content), and taking protection measures of water drilling and application of their protection zones following the River Basin Management Plans, which propose detailed measures based on the article 4 of the Water Framework Directive 2000/60.

Agriculture is essential to the continued existence of human life as they directly depend on it for the production of food. The exponential rise in population calls for a rapid increase in food with the application of technology to reduce the laborious work and maximize production. Precision Agriculture is thought to be solution required to achieve the production rate required. There has been a significant improvement in the area of image processing and data processing which has being a major challenge previously in the practice of precision Agriculture. A database of images is collected through remote sensing, analyzed and a model is developed to determine the right treatment plans for different crop types and different regions. Features of images from vegetation's need to be extracted, classified, segmented and finally fed into the model. Different techniques have been applied to the processes from the use of the neural network, support vector machine, fuzzy logic approach and recently, the most effective approach generating fast and excellent results using the deep learning approach of convolution neural network for image classifications. Deep Convolution neural network is used in plant images recognition and classification to optimize production on a maize plantation. The experimental results on the developed model yielded results with an average accuracy of 99.58%.

Natural agricultural production is an open system, both energy and matters are exchanged freely in this system involving interactions of geosphere (especially pedosphere), biosphere, and atmosphere. Agriculture provides crops for food and industry, fiber, fuel, auto-fuel and drugs. On one hand it faces ever escalating food prices and farmer’s suicides, and on the other hand input use efficiency is low. Present agricultural practices have made harvests toxic, mother’s milk a poison, and breathing-air venom. In this background, nanotechnology brings new hope. Nanotechnology is an interdisciplinary venture-field that converge science, engineering, and agriculture and food systems into one. The Environmental Protection Agency of the US has defined nanotechnology as the understanding and control of matter at dimensions of roughly 1-100 nm, where unique physical properties make novel applications possible. The triple problems of agriculture – over-dependence on supplementary irrigation, vulnerability to climate, and poor input and energy conversion to products – can be solved by using nanotechnology, provided agricultural scientists seek a chance to try and cooperate with scientists of kindred disciplines. Nanotechnology is new to agriculture; a ventured field of less than a decade old. But, already success has been achieved for manufacturing nano-pesticides and nano-fertilizer, in disease elimination in poultry, in food packaging, use of agricultural waste, nanosensors, precision agricultural practices, and in livestock and fisheries. Nanotechnology holds the potential to revolutionize agriculture and food systems in the areas of nano-fertilizers, pesticide career, microfluidics, BioMEMS, nucleic acid bioengineering, smart treatment delivery systems, nanobioprocessing, bioanalytical nanosensors, nanomaterials, bioselective surfaces, environmental processing, pathogen detection, plant/animal production, biosecurity, molecular and cellular biology, protection of the environment through the reduction and conversion of agricultural materials into valuable products, design and development of new nanocatalysts to convert vegetable oils into biobased fuels and biodegradable industrial solvents, and in controlled ecological life support system, to name a few.

Natural agricultural production is an open system, both energy and matters are exchanged freely in this system involving interactions of geosphere (especially pedosphere), biosphere, and atmosphere. Agriculture provides crops for food and industry, fiber, fuel, auto-fuel and drugs. On one hand it faces ever escalating food prices and farmer’s suicides, and on the other hand input use efficiency is low. Present agricultural practices have made harvests toxic, mother’s milk a poison, and breathing-air venom. In this background, nanotechnology brings new hope. Nanotechnology is an interdisciplinary venture-field that converge science, engineering, and agriculture and food systems into one. The Environmental Protection Agency of the US has defined nanotechnology as the understanding and control of matter at dimensions of roughly 1-100 nm, where unique physical properties make novel applications possible. The triple problems of agriculture – over-dependence on supplementary irrigation, vulnerability to climate, and poor input and energy conversion to products – can be solved by using nanotechnology, provided agricultural scientists seek a chance to try and cooperate with scientists of kindred disciplines. Nanotechnology is new to agriculture; a ventured field of less than a decade old. But, already success has been achieved for manufacturing nano-pesticides and nano-fertilizer, in disease elimination in poultry, in food packaging, use of agricultural waste, nanosensors, precision agricultural practices, and in livestock and fisheries. Nanotechnology holds the potential to revolutionize agriculture and food systems in the areas of nano-fertilizers, pesticide career, microfluidics, BioMEMS, nucleic acid bioengineering, smart treatment delivery systems, nanobioprocessing, bioanalytical nanosensors, nanomaterials, bioselective surfaces, environmental processing, pathogen detection, plant/animal production, biosecurity, molecular and cellular biology, protection of the environment through the reduction and conversion of agricultural materials into valuable products, design and development of new nanocatalysts to convert vegetable oils into biobased fuels and biodegradable industrial solvents, and in controlled ecological life support system, to name a few.

An empirical analysis on adoption of precision agricultural techniques among farmers of Punjab for efficient land administration

As various technologies are integrated and implemented into the food and agricultural industry, it is increasingly important for stakeholders throughout the sector to identify and reduce cybersecurity vulnerabilities and risks associated with these technologies. However, numerous industry and government reports suggest that many farmers and agricultural equipment manufacturers do not fully understand the cyber threats posed by modern agricultural technologies, including CAN bus-driven farming equipment. This paper addresses this knowledge gap by attempting to quantify the cybersecurity risks associated with cyberattacks on farming equipment that utilize CAN bus technology. The contribution of this paper is twofold. First, it presents a hypothetical case study, using real-world data, to illustrate the specific and wider impacts of a cyberattack on a CAN bus-driven fertilizer applicator employed in row-crop farming. Second, it establishes a foundation for future research on quantifying cybersecurity risks related to agricultural machinery.

During the last years, a plethora of technological advances have appeared, with a strong impact on people’s lives and works. In response to this dynamic, people getting involved with agricultural practices, like scientists, students and farmers, should become familiar with and able to exploit systems of cutting-edge characteristics. In this regard, this work reports on recent university laboratory efforts to design, implement, upgrade and test prototype do-it-yourself (DIY) agricultural robotic ground vehicles of convincing size, in a cost-effective manner, vehicles that will be capable for “real-world” missions. These efforts also aim to bridge the gap between native educational approaches and working commercial solutions and to lower the cost barriers. Two basic robotic variants, of diverse nature, are presented, one mainly for performing all-terrain soil-specific measurements and another for spraying over the crops. Both vehicles can be seen as “vanilla” platforms, customizable to support a rich set of light-duty agricultural field operations. The “core” of these robots consists of popular microcontrollers assisted by selected electronic components, like smart navigation and/or camera units. The “logic” of these robots has been developed using both visual and textual programming environments. The efficiency of the proposed robots has been evaluated via remote interaction scenarios carried out through Wi-Fi and LoRa radio interfaces, while the provision for solar panel assistance and for energy consumption measuring has also increased their functionality.

Robotics has emerged as a transformative force in modern agriculture, addressing key challenges such as labor shortages, environmental sustainability, and resource optimization. This review presents an overview of current advancements in agricultural robotics, encompassing ground-based robots, unmanned aerial vehicles (UAVs), and autonomous tractors. Empirical evidence highlights significant gains, including herbicide reduction of up to 85%, weeding efficiencies exceeding 90%, and harvesting success rates of 75-90% for various crops. UAVs have improved early disease detection by 40%, while artificial intelligence (AI)-based weed identification achieved an F-score of 0.9843. Despite these promising results, most systems remain in prototype or field-testing stages, constrained by high costs ranging from US$50,000-US$120,000 and technical limitations in perception, navigation, and integration. This review systematically synthesizes existing literature to assess applications, technological capabilities, performance outcomes, and barriers to adoption, providing key insights into the future of robotics in agriculture.

The increasing world population, growing need for agricultural products, and labour shortages have driven the growth of robotics in agriculture. Tasks such as fruit harvesting require extensive hours of work during harvest periods and can be physically exhausting. Autonomous robots bring more efficiency to agricultural tasks with the possibility of working continuously. This paper proposes a stackable 3 DoF SCARA manipulator for tomato harvesting. The manipulator uses a custom electronic circuit to control DC motors with an endless gear at each joint and uses a camera and a Tensor Processing Unit (TPU) for fruit detection. Cascaded PID controllers are used to control the joints with magnetic encoders for rotational feedback, and a time-of-flight sensor for prismatic movement feedback. Tomatoes are detected using an algorithm that finds regions of interest with the red colour present and sends these regions of interest to an image classifier that evaluates whether or not a tomato is present. With this, the system calculates the position of the tomato using stereo vision obtained from a monocular camera combined with the prismatic movement of the manipulator. As a result, the manipulator was able to position itself very close to the target in less than 3 seconds, where an end-effector could adjust its position for the picking.

Design and development of a robot for spraying fertilizers and pesticides for agriculture

The article under scrutiny investigates the conceptual and applied foundations of managing the sustainable development of agricultural enterprises in the Carpathian region of Ukraine with consideration of European integration processes and regional specifics. The research emphasises the importance of harmonising environmental and economic interests through the introduction of green public procurement, technological innovations, and institutional transformations in the agricultural sector. The methodological framework is based on a systemic approach that combines statistical analysis, SWOT analysis, structural-functional methods and the comparative generalisation of EU experience. The study identifies the key strengths, weaknesses, opportunities and threats to sustainable agricultural development in the Carpathian region, which is characterised by challenging natural conditions, significant soil erosion and limited investment capacity. The implementation of integrated technological solutions, including precision agriculture, contour-melioration systems and organic production practices, has been shown to be crucial for reducing environmental degradation and enhancing soil fertility. Furthermore, adapting EU Common Agricultural Policy instruments, such as ecological subsidies, digital monitoring platforms and circular economy principles, creates opportunities to align Ukrainian agricultural practices with European standards. The novelty of the study lies in its proposed organisational and economic mechanism, which integrates green procurement, financial incentives, technological modernisation and institutional support in order to ensure the ecological competitiveness and resilience of the agrarian sector. The practical significance of the research lies in developing regional models of sustainable agricultural management, particularly green procurement pilot projects, which could be replicated in other Ukrainian regions. The findings show that making Ukrainian agricultural products more environmentally responsible, increasing their digitalisation and fostering public-private partnerships can significantly boost their competitiveness in domestic and international markets.

Ours is an age of unprecedented levels of environmental alteration and biodiversity loss. Beyond the exposure to environmental hazards, conditions such as environmental degradation, biotic impoverishment, climate change, and the loss of ecosystem services create important health threats by changing the ecology of many pathogens and increasing the incidence and/or severity of certain noncommunicable conditions. They also threaten health in the future by weakening the Earth's life support systems.Although physicians remain one of the most often accessed and most trusted sources of information about the environment, there is currently little emphasis on educating medical professionals about these environmental issues. This lack of training reduces the ability of most physicians to be efficient science-public interfaces and makes them ineffective at contributing to address the fundamental causes of environmental problems or participate in substantive environmental policy discussions. This is an important challenge facing medical education today.To turn medical students into effective physician-citizens, an already-overwhelmed medical school curriculum must make way for a thoughtful exploration of environmental stressors and their impacts on human health. The overarching question before medical educators is how to develop the competencies, standards, and curricula for this educational endeavor. To this end, the authors highlight some of the critical linkages between health and the environment and suggest a subset of key practical issues that need to be addressed in order to create environmental education standards for the physician of the future.