Cutting-Edge Technologies in Grain Drying: Innovations for Efficiency, Quality, and Sustainability
A special issue of AgriEngineering (ISSN 2624-7402). This special issue belongs to the section "Pre and Post-Harvest Engineering in Agriculture".
Deadline for manuscript submissions: 22 July 2026 | Viewed by 1427
Special Issue Editors
Interests: postharvest engineering; applied crop storage research; sustainable energy; computer-aided grain drying modeling; numerical modeling; grain handling automation and controls; high-temperature drying
Special Issues, Collections and Topics in MDPI journals
Interests: postharvest crop drying, handling, and storage; postharvest crop waste/byproduct utilization; postharvest integrated pest management; human safety on farms and at processing plants
Interests: food processing; postharvest systems engineering; grain drying; grain chilling; grain aeration; computerized mathematical modeling
Special Issue Information
Dear Colleagues,
Grain drying is a critical postharvest operation that directly influences grain quality, storage stability, energy consumption, and overall supply chain efficiency. This Special Issue aims to showcase emerging technologies and innovative approaches that are reshaping traditional grain drying systems into more efficient, intelligent, and sustainable processes. The focus includes advanced drying methods, energy optimization, modeling and simulation, hybrid and solar-assisted systems, sensor-based monitoring, and the integration of digital technologies such as artificial intelligence (AI), machine learning, machine vision, Internet of Things (IoT), and automation.
The scope of this Special Issue spans experimental research, computational studies, technology validation, and practical applications across diverse climatic conditions and grain types. Contributions from academic researchers, industry experts, and interdisciplinary collaborations are encouraged.
The purpose of this Special Issue is to highlight transformative engineering solutions that address key challenges in grain drying such as non-uniform drying, high energy use, and quality degradation while supporting global goals for climate-resilient and resource-efficient food systems.
This collection will complement the existing literature by offering new insights into underexplored areas like AI-driven process control, sensor fusion, and renewable-energy-integrated drying. It will serve as a valuable resource for engineers, researchers, and practitioners seeking state-of-the-art solutions in postharvest grain handling.
Dr. Shubham Subrot Panigrahi
Dr. Kaushik Luthra
Dr. Griffiths Gregory Atungulu
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-blind 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
- grain drying
- postharvest engineering
- energy efficiency
- artificial intelligence
- machine vision
- solar drying
- hybrid systems
- IoT
- drying optimization
- automation
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