Smart Cultivation Technologies for Enhancing Crop Physiology and Yield
A special issue of AgriEngineering (ISSN 2624-7402).
Deadline for manuscript submissions: 31 August 2027 | Viewed by 97
Editors
Interests: abiotic stresses; saline stress; irrigation management; water resources; soilless cultivation; plant nutrition
Interests: biosaline agriculture; reuse of water; hydroponic cultivation; salt stress
Special Issues, Collections and Topics in MDPI journals
Interests: plant physiology; abiotic stress; salt stress; drought stress; phytohormones; vegetables; postharvest of fruits and vegetables; edible flowers
Special Issues, Collections and Topics in MDPI journals
Interests: plant production; plant physiology; abiotic stress; plant hormones; plant ecophysiology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Faced with the challenges of climate change, seeking intelligent solutions to guarantee food production for the growing global population is an urgent issue. Water scarcity, soil salinization, and unsustainable agricultural practices further exacerbate pressures on crop productivity. Additionally, production inputs such as fertilizers (price increases due to geopolitical conflicts), as well as scarce labor, further impact agricultural production. With technological advancements, it has become possible to automate crop management practices, such as the application of water and nutrients, intelligently. These solutions involve measurements ranging from climate and root zone to physiological measurements within the plant itself. Therefore, intelligent systems are implemented to accurately estimate crop water needs, using these measurements individually or in combination. These systems allow for more precise application control, consequently optimizing resource use and, in turn, reducing field labor. In that regard, this Special Issue will focus on research that addresses smart cultivation technologies for enhancing crop physiology and yield, including the following topics:
- IoT-based irrigation and nutrient management for real-time decision support;
- Machine learning for predicting crop water status and physiological responses;
- Remote sensing for monitoring crop physiological responses and managing water stress;
- Plant-based methodologies and approaches for estimating plant water status.
Dr. Mairton Gomes da Silva
Prof. Dr. Hans Raj Gheyi
Prof. Dr. Toshik Iarley da Silva
Prof. Dr. João Everthon Da Silva Ribeiro
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AgriEngineering 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 1800 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
- agricultural automation
- internet of things
- machine learning
- plants physiology
- plants abiotic stress
- plant measurements
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