Dear Colleagues,

The abundance of information available currently, as well as the ease of generating new information at a reasonable cost, is crucial for current digitization processes. New satellite constellations (Sentinel), cloud computing, low-cost sensors, Internet of Things, big data, and "machine learning" and artificial intelligence are expected to be fundamental in various disciplines of plant pathology and the decision making that will drive integrated pest management in the coming years. A pathosystem is represented by the "disease triangle"; that is, disease requires the interaction of a susceptible host, a virulent pathogen, and a favorable environment. Under these conditions, an epidemic may occur, defined as an increase in the disease over time, generating a multitude of available data. In this context, "Precision plant pathology" is a set of techniques aimed at optimizing the management of diseases based on the quantification of their spatial and temporal variability. These techniques seek to reduce costs and improve production and sustainability by creating risk prediction algorithms and models for the main diseases and adapting them to specific conditions. The four following areas of research are proposed: (1) visualization and statistical analysis of disease data using R and Python; (2) disease modeling using machine learning techniques and fuzzy logic; (3) automatic plant disease diagnosis using deep learning; and (4) remote and proximal sensing for early plant disease detection.

Dr. Antonio Santos-Rufo
Prof. Dr. Francisco Javier López-Escudero
Dr. Fernando Pérez Porras
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• R
• Python
• cloud computing
• precision agriculture
• remote sensing
• smart sensors
• multispectral, hyperspectral and thermographic sensors
• vegetation index, NDVI
• artificial intelligence
• deep learning
• fuzzy logic
• prescription map
• UAV/drone
• big data