Virtual Reality System Software and Tools: Software for virtual reality systems consists of various tools and applications used for creating, developing, and managing virtual environments, as well as the databases that store the associated information. These tools can be categorized into modeling tools and development tools.
VR Modeling Tools: There are many modeling tools available for VR designing; the most common are 3ds Max, Maya and Creator. Engineering-specific applications may utilize software like CATIA, Pro/E, Solidworks, UG, etc.
VR Development Tools: VR is a multifaceted and integrated technology that draws from various other technologies, including real-time 3D graphics, tracking systems, audio processing, and haptic feedback, which necessitate flexibility in software development and real-time interaction. Beginning the development of a VR system from foundational code in languages like C/C++, Java, OpenGL, etc., demands considerable effort, and the reliability of such systems is typically low; hence, VR development tools are utilized.
Careful thought is required in selecting VR development tools because of the variation in flexibility offered by various software packages concerning model input available, interface compatibility, file format, ease of animation, collision detection, supported I/O devices and support community accessible to the users.
The equipment for developing VR content includes virtual world authoring tools, VR toolkits/software development kits (SDKs), and application programming interfaces (APIs). It is also not unusual to encounter APIs that function as toolkits, such as the OpenGL optimizer and the Java 3D API (Dani & Rajit, 1998).
Utilizing VR Simulation for Agricultural Training
Development of Virtual Crops: Virtual reality can give users a powerful feeling of reality and authentic experience and occupy a new concept-immersed interactive environment. Using this technology, years of crop growth data can be simulated in just a few minutes. This allows for quick operation, observation, testing, and collection of crop data (Su et al., 2005).
Virtual crops technology uses virtual reality to replicate crops' structure, growth processes and environment in a three-dimensional space. It uses a data collecting system to monitor environmental factors changes and crop growth trends, and to study regular patterns of crops and the environment. The virtual crops system is highly valuable for investigating optimal crop models, enhancing growth strategies, shaping crops, designing gardens, and providing educational opportunities (Sun, 2000; Song et al., 2000; Holt & Sonka, 2003).

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Figure 4: General Architecture of a Virtual Crop System (Li, 2008)
Precision Agriculture: Simulation systems have become indispensable tools in modern research and virtual laboratory experiments, providing an advanced platform for in-depth analysis and replication of intricate processes. A prime example of innovation in the agri-food sector is the SIMAGRI platform, a high-fidelity driving simulator designed explicitly for tractors and agricultural machinery. Developed to support precision agriculture (PA) research, SIMAGRI employs advanced algorithms and real-time data processing to mimic the dynamic conditions of modern farming practices (Cutini et al., 2023). Beyond enabling rigorous scientific exploration of innovative PA techniques, this cutting-edge system is a critical training resource for professional farm operators. By allowing drivers to refine their skills in a controlled, risk-free virtual environment, SIMAGRI bridges the gap between theoretical knowledge and practical implementation, ultimately fostering the advancement of sustainable and efficient agricultural practices. Through its virtual environment, researchers can evaluate PA operational strategies' effects and adjustments by replicating real-world scenarios or designing new ones in diverse contexts and configurations. The simulator currently includes an agricultural tractor capable of towing or transporting various farming equipment, such as sprayers, seeders, and fertilizer spreaders. It is integrated with embedded sensors and human-machine interfaces, including joysticks, consoles, or touchscreens, all connected to four virtual environment displays.

Figure 5: SIMAGRI workflow (version 2 linked with SCF) (Sosa et al., 2017)
Livestock Management: Climate change effects on farm productivity are more severe now, leading to increased food insecurity. It is essential to adopt more sophisticated practices like smart farming instead of conventional methods for increasing production. As a result, livestock farming is quickly transitioning to innovative farming systems, driven by rapid technological advancements such as cloud computing, the Internet of Things, big data, machine learning, augmented reality and robotics. A Digital Twin (DT), an element of state-of-the-art digital agricultural technology, serves as a virtual representation or model of any physical entity (physical twin) connected through real-time data sharing. A digital twin (DT) continuously mirrors the state of its physical counterpart in real time and can also influence it in return. The application of DTs in the livestock sector is currently nascent, reflecting a knowledge gap in their holistic application within livestock systems. The application of DTs in livestock has vast potential to promote animal health, welfare, and productivity (Arulmozhi et al., 2024). The digital transformation landscape in the livestock sector includes monitoring animals, managing the environment, implementing precision agriculture techniques, and optimizing the supply chain. It emphasizes the significance of collecting quality data, maintaining robust data privacy measures, and having seamless data source integration to ensure effective and accurate implementation.

Figure 6: Potential application of digital twins in overall livestock management (Arulmozhi et al., 2024)
Rationale for Adopting Digital Twins in the Livestock Industry: Despite a recent breakthrough in DT technology, its use in the livestock industry is in the nascent phase of development. However, some industries like aero manufacturing (Ibrion et al., 2019), oil field services (Mayani et al., 2018), software (Brenner & Hummel, 2017), fast-moving consumer goods (Erol, Mendi, & Doğan, 2020), and tire manufacturing (Erol, Mendi, & Doğan, 2020) are already utilizing the benefits of DTs. From the authors’ viewpoint, the analysis of prior studies and reviews suggests that DTs offer numerous benefits for improving livestock production. This includes the following:
● Precision Livestock Farming: Health and nutrition are enhanced by technology that utilizes real-time data and monitoring for each animal, optimizing productivity on a case-by-case basis. Such growth not only increases animal welfare but also optimizes profitability for livestock farms. This allows farmers the chance to select alternative breeding based on parameters that give optimal productivity, which may include superior growth rates, fertility, or resistance to diseases. Another strategy involves enhancing genetic progress within herds. Digital twins (DTs) can detect early changes in disease-related physiological indicators, behavior, and environmental factors. Predictive models provide farmers with early alerts to help minimize mortality and treatment expenses for emerging health problems. By continuously monitoring the animals' physical condition and their immediate environment, it becomes easier to identify signs of discomfort or stress. This approach enhances overall animal welfare, resulting in healthier and more productive livestock.
● Sustainability and Environmental Impact: DTs can greatly minimize waste and lessen environmental impact by enhancing the efficiency of feed and water consumption, along with other resources. This results in more sustainable farming practices that align with the increasing global demand for eco-friendly livestock production methods.
● Labour Efficiency: Using DTs in automation minimizes the requirement for additional human oversight. With a virtual system for monitoring and management, farmers can strategically organize multiple schedules for the feeding and care of their animals, thereby enhancing efficiency and reducing the likelihood of human mistakes.
● Compliance with Regulations: Digital twins (DTs) offer comprehensive records of animal health, farm management practices, and environmental impacts, while ensuring adherence to both local and international standards for animal welfare and sustainability. This improves traceability across the supply chain.
● Remote Management: Digital twin technology enables farmers to manage livestock operations remotely using cloud-based systems. This capability is essential for multi-site farms or large-scale operations, allowing for improved management without physical presence.
● Operational Cost Efficiency: While costlier to establish overall, in the long run, the DTs improve resource efficiency, minimize waste feed, and save on healthcare expenditures through early treatment of animal diseases.
● Training and Education: The simulated replicas of the livestock system can train employees in innovative management techniques without affecting the real animals, thereby improving the skills and knowledge of farm workers.
Combating Misinformation on Climate Change: Misinformation, whether accidental or deliberate, pertains to incorrect or deceptive information (Lewandowsky, Ecker, & Cook, 2020) and can have serious adverse effects on individuals and society. Misinformation about climate change, especially the denial of its human-induced aspects, can lead to confusion and doubt, undermining efforts to tackle the problem (van der Linden, 2023). It reduces public backing for mitigation strategies, impeding investments in renewable energy, sustainable development, and practices that enhance climate resilience (Winter et al., 2022). Additionally, political divisions and social tensions may emerge from climate change misinformation, creating a split between those who accept the scientific consensus and those who reject or question it (Hart et al., 2015). Combating misinformation, advancing accurate scientific knowledge, and encouraging informed public discussions about climate change are essential for fostering a sustainable future.
To comprehensively grasp the psychology and context behind misinformation, it is crucial to explore the impact of contemporary technology (Ecker et al., 2022). Studies suggest that tackling the complexities of the post-truth era demands technological solutions informed by psychological principles (Lewandowsky et al., 2017). Virtual reality (VR) has emerged as a promising tool, offering immersive environments that allow users to engage deeply with simulated experiences, thereby providing a unique platform for developing and implementing effective corrective measures (Slater & Sanchez-Vives, 2016). By immersing users in realistic, interactive scenarios, VR can challenge and correct false beliefs and assumptions, making it a powerful tool against misinformation (Slater et al., 2020). Additionally, VR can create engaging and memorable experiences that foster critical thinking, learning, and fact-checking (Queiroz et al., 2023). This technology can boost media literacy and deepen understanding of intricate issues by allowing users to witness the consequences of misinformation in a controlled setting (Jones et al., 2022). Moreover, VR can be combined with data visualization and interactive storytelling to present factual information captivating and impactfully (Krokos et al., 2019; Slater & Sanchez-Vives, 2016).
The advantages that make VR effective for delivering persuasive messages can also render it a powerful means of spreading misinformation (Ahn, 2021; Brown et al., 2023). Although creating high-quality VR content is challenging and there are currently low levels of familiarity with VR devices, the significant investment in this technology suggests that VR platforms will likely gain popularity in the future (Trauthig & Woolley, 2023). Therefore, it is increasingly essential to comprehend how VR can be used in harmful ways, such as for disinformation campaigns and to develop strategies for countering these activities within the VR environment.
Supply Chain Management: Supply chains are becoming increasingly important, with competition shifting from individual companies to entire supply chains (Farahani et al., 2014). The swift development of supply chain management (SCM) as an essential area within operations management is propelled by technological advancements such as digital twin (DT) technology, which is a part of Industry 4.0 progress. Digital twin (DT) technology, initiallycreated by NASA in the 1960s, generates a virtual representation of physical assets and processes, continuously updated through sensor information and analytics. Supported by IoT, cloud computing, AI, robotics, and 3D printing (Verboven et al., 2020), digital supply chains derive actionable insights from real-time data, improving efficiency, adaptability, and value generation. Initial findings indicate that DT technology enhances performance throughout operations and supply chains.
Contemporary supply chain management (SCM) software encompasses a variety of solutions, including advanced planning and scheduling (APS) systems, warehouse management systems (WMS), and transportation management systems (TMS). Over the last decade, these technologies have streamlined many supply chain operations, significantly improving collaboration and communication between suppliers, buyers, and logistics providers.
Digital twins can complement existing SCM solutions by acting as an innovative layer that enhances the technology stack. In this way, digital twins can refine data inputs for SCM tools, producing predictive analytics to tackle and respond to numerous situations. For example, a multinational OEM created a digital twin to optimize the strategies integrated into its transportation management system (TMS) for managing outbound logistics. Consequently, the OEM achieved an 8 percent reduction in freight and damage costs.

Figure 7: Supply chain digital twin system based on a unique product model (Xia et al., 2022)
Digital twins enhance supply chain management (SCM) tools in several ways: Digital twins enable comprehensive integration across supply chain management (SCM) software, providing a unified view of performance and the broader impact of decisions across upstream and downstream operations, thereby eliminating fragmented, isolated systems and fostering collaboration—for instance, a retailer used digital twins to connect planning, inventory, and transportation systems. In volatile markets, especially post-COVID-19, supply chain leaders must adapt to shifting demand and disruptions like port delays or material shortages; digital twins paired with SCM tools offer real-time insights, predictive analytics, and actionable recommendations to mitigate risks, as demonstrated by an OEM that reduced last-mile delivery costs by 5% through monitoring carrier performance and surcharges. Additionally, digital twins help balance competing priorities and complex constraints, enabling rapid responses to market changes, such as an automotive manufacturer dynamically aligning demand with supply and operational challenges to optimize sales and production goals. Furthermore, SCM systems enhanced with digital twins can simulate diverse scenarios by analyzing variables like lead times, demand patterns, and supplier reliability, predicting outcomes to strengthen resilience—for example, a consumer goods company reduced distribution costs by 15% by evaluating fluctuating demand and labor levels in its distribution network.