Disease diagnostic tools—past, present, and future—a preface

Disease diagnostics in aquaculture have evolved substantially in association with the developments in aquaculture and the discipline of aquatic veterinary medicine. In the past, fish disease diagnosis was primarily based on visual observations such as changes in behavior, physical appearance, and mortality rate. Typically, these methods are not specific enough, due to the lack of specificity, delayed and inaccurate diagnosis, leading to severe economic and ecological impacts. In the mid-20 th century, significant progress was made in microbiology, histopathology, and molecular biology, leading to more precise identification of pathogens. Recently, the adoption of molecular diagnostic tools such as polymerase chain reaction (PCR) and next-generation sequencing (NGS) have considerably transformed the detection of fish pathogens, with high sensitivity and specificity. Additionally, advances in imaging technologies and the use of biomarkers allow for greater rapidity of assessment and monitoring of fish health. In the future, diagnostic tools are expected to integrate artificial intelligence (AI), and big data analytics, enabling real-time disease surveillance and more accurate predictions of disease outbreaks. The chapter reviews conventional disease diagnosis methods, such as clinical diagnosis, microscopic examination, microbial identification, and histopathologic studies in aquatic health management. This section also details immunological methods, omics-based molecular detection, different PCR diagnosis techniques, DNA microarray, etc. Overall, this preface contains an overview of the background, current status, and future perspectives of disease diagnostic tools, highlighting the continuous innovation that drives improvements in fish health management.