Field Phenotyping for Precise Crop Management
A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Artificial Intelligence and Digital Agriculture".
Deadline for manuscript submissions: 15 February 2026 | Viewed by 458
Special Issue Editors
Interests: plant phenotyping; remote sensing; UAV; cereal; wheat; drought; RGB; thermal imaging; multispectral sensors
Special Issues, Collections and Topics in MDPI journals
Interests: image-based plant phenotyping; image analysis; abiotic stress; low-cost phenotyping platform; crop monitoring; 3D modeling and reconstruction
Special Issue Information
Dear Colleagues,
High-throughput field phenotyping has become essential not only in plant breeding but also in agricultural monitoring and decision-making. In recent decades, significant technological advances have enabled the evaluation of crop traits across various spatial, temporal, and organizational scales. The literature reports a wide range of phenotyped traits, measured either directly or indirectly, using diverse platforms, sensors, indices, and data-processing tools. For instance, the normalized difference vegetation index (NDVI) is one of the most widely used indices, commonly employed as an indirect indicator of biomass and canopy vigor, although its specific purpose can vary depending on experimental objectives. Applications span from variety selection in breeding programs to agronomic decision-making, particularly in evaluating management strategies aimed at optimizing crop productivity and enhancing sustainability.
Beyond the development of new sensing and imaging technologies, there is a growing need to streamline the entire data pipeline, from field-level acquisition to downstream processing, analysis, and interpretation. This involves efficient transfer, storage, and integration into analytical software environments. The ability to automate dataflow, standardize processing routines, and scale up analyses is becoming critical in the usability of field phenotyping outputs.
This Special Issue aims to address the main challenges and opportunities of the diverse range of applications in field phenotyping. We are particularly interested in contributions that explore whether phenotyping remains a bottleneck in agricultural research, how phenotypic traits relate to genotypic adaptation under different management conditions, and how data integration across time and scale can be achieved. Additionally, we welcome studies focused on managing large volumes of high-resolution data, developing scalable analytical frameworks, and presenting novel data extraction protocols or custom software solutions that enhance the interoperability and reproducibility of phenotyping workflows.
Dr. Adrian Gracia-Romero
Guest Editor
Dr. Riccardo Rossi
Guest Editor Assistant
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 semimonthly 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.
Keywords
- high-throughput phenotyping
- crop monitoring
- sensor technology
- trait analysis
- genotype-environment interaction
- UAV
- image analysis
- precision agriculture
- IoT
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