This book features five peer-reviewed reviews on machine vision applications in agriculture.

The first chapter examines recent advances in machine vision technologies for the measurement of soil texture, structure and topography. The chapter also provides an overview of the basic principles of machine vision technologies, focussing on areas such as 3D surface modelling.

The second chapter considers the use of machine learning methods to classify multiple diseases across several different crop types. The chapter also explains how deep learning for image analysis and classification works.

The third chapter presents an overview of the use of machine learning for agri-robotics, including the main trends of the last decade. It also discusses the use of machine learning for data analysis and decision-making for perception and navigation.

The fourth chapter addresses the prospects of machine vision application in plant factories with artificial lighting. The chapter also summarises recent research utilising this technology, including plant growth monitoring, robot operation assistance and fruit grading.

The final chapter reviews advances in computer vision-based technologies for precision livestock farming. The chapter also reviews how automation in image analysis can promote smart management of livestock to improve health and welfare.