Transforming smart farming for sustainability through agri-tech Innovations: Insights from the Australian agricultural landscape

Abstract

The rapid advancement of precision agriculture technologies and Agri-tech startups is transforming the global agricultural landscape, enhancing productivity, sustainability, and climate resilience. This study systematically reviewed 131 articles published between 2000 and 2024, selected using the PRISMA flow diagram from Scopus, ScienceDirect, Web of Science, Google Scholar, and grey literature sources. This study explores the role of precision agriculture technologies, including the Internet of Things (IoT), drones, and artificial intelligence (AI), in its adoption and effective use by farmers, for optimizing resource use, improving farm efficiency, and reducing environmental impacts in large size Australian farms. Despite their potential, widespread adoption faces challenges such as high implementation costs, technical constraints, and regulatory barriers. Additionally, Agri-tech startups play a crucial role in addressing climate change challenges by developing innovative solutions such as drought-resistant crops and climate-resilient farming methods. These advancements, when integrated with principles of agronomy and supported by strategic technology adoption, enhance the efficient use of resources. While the adoption of such technologies often involves an initial investment, their effective implementation can lead to more sustainable and resilient farming systems, ultimately promoting long-term productivity and environmental stewardship. However, inclusivity remains a critical issue, particularly in ensuring equitable access for small-scale farmers, women, and underrepresented groups in Agri-tech entrepreneurship. This study highlights the importance of supportive policies, financial investments, and training programs to facilitate broader adoption of emerging agricultural technologies. Based on the literature review and keyword co-occurrence analysis, this study developed nine hypotheses and subsequently proposed a conceptual model to examine the relationships among key variables in sustainable agriculture. Future research should focus on integrated approaches that assess agronomic, economic, and social aspects of precision agriculture and Agri-tech startups, fostering sustainable and inclusive agricultural development.