With the agricultural sector facing mounting pressure to reduce their carbon footprint, greater emphasis has been placed on improving existing components and practices, such as soil health and biodiversity, which have since emerged as key components to achieving regenerative agriculture. Sensors provide the opportunity to measure crop and soil health at unparalleled scales and resolution. Key developments in sensor technology will help improve our current understanding and optimisation of the complex agricultural systems that make up our global ecosystem. Advances in sensor technology for sustainable crop production provides a comprehensive review of the wealth of research on key developments in sensor technology to improve monitoring and management of crop health, soil health, weeds and diseases. This collection also reviews advances in proximal and remote sensing techniques to monitor soil health, such as spectroscopy and radiometrics, as well as how sensor technology can be optimised for more targeted irrigation, site-specific nutrient and weed management.

This collection features four peer-reviewed reviews on proximal sensors in agriculture. The first chapter addresses the use of proximal sensors to evaluate crop health and performance throughout the growing season. The chapter reviews the evolution of crop sensors, as well as the issues and limitations facing further development, including the need to develop sensors equipped with the ability to detect stresses other than nitrogen. The second chapter reviews recent advances in using proximal sensors to detect crop health status in horticultural crops. The chapter considers the application of sensors to detect micro-environmental parameters linked to pathogen lifecycles which can then be utilised to predict disease risk. The third chapter reviews advances in using proximal spectroscopic sensors to assess soil health. It assesses principles and technologies, key properties measured, advantages and disadvantages together with applications in improving soil management. The final chapter discusses advances in the use of proximal sensor fusion and multi-sensor platforms for improved crop management. The chapter considers the combination of remote sensing from satellites and weather station data as the basis for crop growth models and explores the benefits of utilising a selection of tools to investigate yield prediction.