Special Issue "Energy Balancing/Optimization in General, with Special Emphasis on Crop Production"
Deadline for manuscript submissions: 8 November 2021.
Interests: materials informatics; nanomechanics and nanotribology; coatings; cladding; additive manufacturing; materials/alloy design; CALPHAD; physical metallurgy; process metallurgy: blast furnace iron making; LD steel making; artificial intelligence algorithms; data-driven modeling; multi-objective optimization
Special Issues, Collections and Topics in MDPI journals
Crop production is an energy-intensive process. Consumption of energy depends on several factors, including but not limited to soil nutrients, soil moisture, and weather pattern. Nutrient content in soil, specifically amount of N, K, etc., plays a vital role in determining the amount of fertilizer to be used, while soil moisture and weather pattern determine irrigation. Other factors such as crop rotation and type of crops produced in a farm too affect the quality of soil. Energy is also consumed in the cultivation of land, transportation of various products and irrigation, and harvesting. There are ways to recover a portion of energy through effective utilization of farm waste through biomass. Minimizing energy losses can also be helpful in energy balancing/optimization. Exergy analysis can help to understand energy losses and their minimization from principles of thermodynamics.
One of the major challenges faced by farm owners is a lack of understanding of soil quality. This results in inefficient utilization of resources such as manure/fertilizer and irrigation. Choosing a fertilizer is a complicated process, and one needs to understand the change in soil over several years. Additionally, soil and weather conditions in one place differ from soil and weather conditions in another. Farming practices in developing and developed countries differ a lot, too. Thus, a methodology developed for energy optimization for one farm may not work on another farm.
To address a complicated problem like this, artificial intelligence (AI)-based algorithms can be helpful. AI-based algorithms can provide vital information on correlations among various factors affecting crop production. These factors include soil nutrient/moisture, energy consumption from various sources, fertilizer and its content, irrigation, weather patterns, number of crops, types of crops, etc.
This issue focuses on energy optimization in general with special emphasis on crop production. Articles focusing on energy optimization and exergy analysis in industries will also be considered for publication in this Special Issue.
Dr. Rajesh Jha
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 papers will be 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. Energies 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 2000 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.
- Soil nutrients and moisture
- Weather pattern
- Crop rotation
- Artificial intelligence
- Multi-objective optimization
- Mathematical modeling