Plant pathology and diseases from a novel bibliometric method

The study of plant pathology is of vital importance to plant health and agriculture. These diseases impact ecosystems and agriculture and therefore need to be studied in depth. This paper introduces a novel bibliometric analysis method, offering a comprehensive view of the current research landscape, distinct from traditional tools like VOSviewer. The analysis identifies key research directions such as disease resistance, pathogen detection, and treatment strategies while also uncovering future opportunities, especially in integrating big data and machine learning. These technologies promise to revolutionize plant disease management by providing predictive capabilities, personalized treatments, and proactive solutions. By processing vast datasets and continuously learning from new inputs, machine learning models can enhance early detection and intervention, leading to more sustainable and effective management of plant diseases in the future.