Computers and Electronics in Agriculture provides international coverage of advances in the development and application of computer hardware, software, electronic instrumentation, and control systems for solving problems in agriculture, including agronomy, horticulture (in both its food and amenity aspects), forestry, aquaculture, and animal/livestock farming. Its new companion journal, Smart Agricultural Technology provides continuity for smart application being applied in production agriculture.

The journal publishes original papers, reviews, and applications notes on topics pertaining to advances in the use of computers or electronics in plant or animal agricultural production, including agricultural soils, water, pests, controlled environments, structures, and wastes, as well as the plants and animals themselves. On-farm, post-harvest operations considered part of agriculture (such as drying, storage, logistics, production assessment, trimming and separation of plant and animal material) are also covered. Relevant areas of technology include artificial intelligence, sensors, machine vision, robotics, networking, and simulation modelling.

When determining the suitability of submitted manuscripts for publication, particular emphasis is placed on novelty and innovation, and the degree to which a manuscript advances the state of the art for computers/electronics in agriculture. Applying existing technology to a particular crop for the first time does not qualify as an innovation in computers/electronics for this journal. Research applying off-the-shelf hardware or software, without augmenting such technology with investigator-developed tools, innovations, or unique approaches, should be submitted to its companion journal, Smart Agricultural Technology, whose scope includes applied technology. Manuscripts that apply computers/electronics in an ancillary fashion or focus objectives and conclusions primarily on the application sciences (e.g., entomology, agronomy, engineering, economics, horticulture) should be submitted to one of those respective science journals.

The journal recognizes that the use of previously published data sets (either alpha-numeric, quantitative, or imagery) can be extremely beneficial as researchers develop and prototype new machine learning or machine vision algorithms with potential application to agriculture. However, the journal views this prototyping work as preliminary in nature, and prospective authors should, prior to submitting such work to this journal, generate a more scientifically rigorous data set, collected by the authors under controlled and reported experimental conditions.

Special Issue on Advanced technologies for precision nutrient management
Día de Entrega: 2024-12-30

Efficient nitrogen management is essential for both environmental sustainability and agricultural productivity. Current nitrogen management practices have limitations in evaluating soil nitrogen availability and plant nitrogen content as well as applying fertilizers at the right time and precise rates in specific field areas. However, recent advances in nitrogen sensing and application technologies provide farmers with accurate, real-time insights into crop growth and nutrient status, leading to higher yields, enhanced crop quality, and decreased environmental impact. This special issue aims to promote research on nitrogen management by bringing together scholars and researchers with new perspectives on nitrogen sensing and management technologies. Topics of interest include:

    Remote and proximity sensing technologies for nitrogen monitoring
    New technologies for laboratory-based soil and leaf tissue analysis for nitrogen measurement
    Variable rate application technology for nitrogen fertilizer application
    Soil sensors for nitrogen monitoring
    Modeling approaches for nitrogen management
    Integration of different nitrogen management technologies for improved efficiency and effectiveness
    Evaluation of the accuracy and effectiveness of nitrogen sensing and application technologies
    Cost-benefit analysis of precise nitrogen management technologies
    Development of decision support systems for nitrogen management
    Assessment of climate change impacts of nitrogen management practices
    Adoption and implementation of nitrogen sensing and application technologies by farmers
    Policy and regulatory frameworks for promoting sustainable nitrogen management in Agriculture
    Case studies and field trials demonstrating the effectiveness of precise nitrogen management practice
    Future directions and challenges in site-specific nitrogen management
    Nutrient measurement and precision application of manure

The issue encourages researchers from various fields to submit high-quality research to advance nitrogen management in agriculture.

Guest editors:

Associate Professor Alireza Pourreza
UC Davis, Davis, CA, USA
apourreza@ucdavis.edu

Assistant Professor Ali Moghimi
UC Davis, Davis, CA, USA
amoghimi@ucdavis.edu

Senior Research Associate Terry Bates
Cornell CALS, Portland, NY, USA
trb7@cornell.edu

Professor Kang Yu
Technical University of Munich, Freising, Germany
kang.yu@tum.de

Manuscript submission information:

Submission deadline: 30 December 2024
To submit your manuscript please go to Computers and Electronics in Agriculture- COMPAG (at https://www.journals.elsevier.com/computers-and-electronics-in-agriculture) and follow the procedures for manuscript submission. When prompted for 'Enter Manuscript Information' you can select our Special Issue Article type as ‘VSI:Precision Nutrient Management” at https://www.editorialmanager.com/compag/default1.aspx.

Author Guidelines and Manuscript Submission can be found at: https://www.elsevier.com/journals/computers-and-electronics-in-agriculture/0168-1699/guide-for-authors.

Keywords:

1. Digital agriculture
2. Precision agriculture
3. Nitrogen sensing
4. Nitrogen retrieval
5. Variable rate application
6. Decision support systems
7. Sustainable nitrogen management
8. Climate change

Learn more about the benefits of publishing in a special issue: https://www.elsevier.com/authors/submit-your-paper/special-issues

Interested in becoming a guest editor? Discover the benefits of guest editing a special issue and the valuable contribution that you can make to your field: https://www.elsevier.com/editors/role-of-an-editor/guest-editors

Special Issue on Advanced Technologies in Sustainable Agriculture 4.0: Future Farming, Monitoring, Harvesting and Preservation
Día de Entrega: 2024-12-31

The global population is expected to be 9.2 billion in 2050, and the world will need to produce 70 percent more food. Meanwhile, agriculture’s share of global GDP has shrunk to just 3%, one-third its contribution just decades ago. The reality is that very few innovations have taken place in the industry of late, and they are far from enough. Farms and agricultural operations will run quite differently. Future agriculture will use integrated Agriculture 4.0 technologies such as robots, temperature and smart sensors, aerial images, and 3S technologies. These advanced devices, precision agriculture, and robotic systems will allow farms to be more profitable, efficient, safe, and environmentally friendly. The main aims of this focused section in collaborative journals are to present the current state of the art in advanced technologies in sustainable agriculture 4.0—future farming, harvesting and conservation—and to illustrate new results in several emerging research areas. Submissions can present theoretical and experimental aspects in these areas. 

This collection includes but not limited to: (1) Smart agricultural machinery; (2) 5G-based Internet of Things in Agriculture 4.0; (3) Smart Sensors in Agriculture 4.0; (4) 3S technologies in Agriculture 4.0: remote sensing, GIS, GPS; (5) High-throughput crop phenotyping; (6) Unmanned aerial vehicles in Agriculture 4.0. (7) Digital twins or AR/VR in agriculture simulation and experiment.

Guest editors:

Dr. Yunchao Tang
Zhongkai University of Agriculture and Engineering, Guangzhou, China
Ryan.twain@zhku.edu.cn

Dr. Spyros Fountas
Agricultural University of Athens, Athens, Greece
sfountas@aua.gr

Dr. Yiannis Ampatzidis
University of Florida, Department of Agricultural and Biological Engineering, Gainesville, Florida, United States of America
i.ampatzidis@ufl.edu

Dr. Lei Shu
Nanjing Agricultural University, China
lei.shu@njau.edu.cn

Manuscript submission information:

Submission deadline: 31 December 2024
Acceptance deadline: 30 April 2025

To submit your manuscript please go to Computers and Electronics in Agriculture- COMPAG (at https://www.journals.elsevier.com/computers-and-electronics-in-agriculture) and follow the procedures for manuscript submission. When prompted for 'Enter Manuscript Information' you can select our Special Issue Article type as ‘VSI:Sust. Agri. 4.0” at https://www.editorialmanager.com/compag/default1.aspx.

Author Guidelines and Manuscript Submission can be found at: https://www.elsevier.com/journals/computers-and-electronics-in-agriculture/0168-1699/guide-for-authors.

Keywords:

    Unmanned mechatronics systems
    Agricultural robotics
    Cooperative mechatronics
    Smart sensors
    Crop phenotyping & estimation
    Data-driven sustainability
    Precision farming
    Life cycle health monitoring of crops
    Digital Twins / AR / VR
    Internet of Things

Learn more about the benefits of publishing in a special issue: https://www.elsevier.com/authors/submit-your-paper/special-issues

Interested in becoming a guest editor? Discover the benefits of guest editing a special issue and the valuable contribution that you can make to your field: https://www.elsevier.com/editors/role-of-an-editor/guest-editors

Special Issue on Quantitative Remote Sensing Modelling for Smart Farming
Día de Entrega: 2024-12-31

Remote sensing plays an increasingly important role in smart farming, especially for field crop and orchard production. It provides essential information, such as crop growth, yield and quality, for planters or agricultural vehicles on making optimized decision on precision fertilization, irrigation and pesticide application. It will trigger green, sustainable and intelligent crop production paradigm by less chemical inputs, more yield and better quality, remove information connectivity barriers among sectors of tillage, sowing, management, harvesting and storage, and lay a solid foundation for the development of smart farming in the future.

With the increasing temporal, spatial, and spectral resolution of satellites, particularly commercial small satellites in recent years, there is an explosive growth in remote sensing data. However, current agricultural remote sensing models are still based on empirical statistics, lacking agronomy and remote sensing mechanism, which is difficult to be widely applied in highly complex field environment. In addition, these models are dispersed and with different maturity, resulting in many shortcomings in the whole chain of smart crop production, such as "lack of core and soul", which greatly restricts the development of smart agriculture. Therefore, there is urgent need for constructing quantitative remote sensing models through integrating the agronomy knowledge with the spatial-temporal-spectral remote sensing data to tackle these growing challenges. Thereby it will realize the efficient information perception of crop-soil-environment system, accelerate the transition from traditional empirical analytics to quantitative era.

This Special Issue aims to bring together researches with new, recently developed perspectives in remote sensing models for smart agriculture applications. The objective of the Special Issue is to increase awareness of the implications of using remote sensing solutions, including but not limited to:

    Geometric and radiometric correction model
    Spectral transformation and radiation enhancement model
    Sensor calibration model
    Sensor measurement model
    Fusion model of spatial-temporal-spectral remote sensing data
    Spectral classification and AI recognition model
    Vegetation parameters inversion model
    Active and passive detection model for soil parameters
    Early warning model for crop diseases and pests monitoring
    Crop fertilizer and irrigation decision model
    Crop yield estimation model
    Crop quality prediction model
    Data assimilation of remote sensing and crop model
    Cultivated land quality assessment model
    Crop evapotranspiration model
    Crop phenotyping monitoring model…

Guest editors:

Professor Guijun Yang
Chang’an University, College of Geological Engineering and Geomatics
yanggj@nercita.org.cn

Professor Igor SAVIN
RUDN University, agroengineering department
savin_iyu@esoil.ru

Professor Haiyan Cen
Zhejiang University, College of Biosystems Engineering and Food Science
hycen@zju.edu.cn

Professor Zhengwei Yang
United States Department of Agriculture, National Agricultural Statistics Service, Research and Development Division, Spatial Analysis Research Section
Zhengwei.Yang@usda.gov

Professor Jihua Meng
Chinese Academy of Sciences, Key Lab of Digital Earth, Institute of Remote Sensing and Digital Earth
mengjh@irsa.ac.cn

Professor Stefano Pignatti
C.N.R.-IMAA, Consiglio Nazionale delle Ricerche-Institute of Methodologies for Environmental Analysis
pignatti@imaa.cnr.it

Professor Tiecheng Bai
Tarim University, Southern Xinjiang Research Center for Information Technology in Agriculture
baitiecheng1983@163.com

Manuscript submission information:

Submission deadline: 31 December 2024
Acceptance deadline: 31 March 2025

To submit your manuscript please go to Computers and Electronics in Agriculture- COMPAG (at https://www.journals.elsevier.com/computers-and-electronics-in-agriculture) and follow the procedures for manuscript submission. When prompted for 'Enter Manuscript Information' you can select our Special Issue Article type as ‘VSI:QRSM” at https://www.editorialmanager.com/compag/default1.aspx.

Author Guidelines and Manuscript Submission can be found at: https://www.elsevier.com/journals/computers-and-electronics-in-agriculture/0168-1699/guide-for-authors.

Learn more about the benefits of publishing in a special issue.

Interested in becoming a guest editor? Discover the benefits of guest editing a special issue and the valuable contribution that you can make to your field.

Special Issue on Agricultural Cybernetics: A New Methodology of Analysis and Development for Modern Agricultural Production Systems
Día de Entrega: 2025-01-31

In the digital age, agriculture has evolved into modern precision farming characterized by what we call smart that utilizes recent innovations in data science, artificial intelligence, Internet of Things, and high-performance cloud computing. For further advancement of modern agriculture, agricultural cybernetics has been established as a new methodology of agricultural information science for analysis and development of advanced modern agricultural production systems. Agricultural cybernetics, as a new science, deals with the issues of control and communications in information, biological and mechanical systems for operation, optimization, and control of precision/smart agricultural production systems. To promote further research on agricultural cybernetics, this special issue welcomes manuscripts from but not limited to:

    Agriculture information science and agricultural cybernetics in relation to precision and smart agriculture
    Modern agricultural information management and decision support, especially data-driven system design and development, and knowledge production
    Agricultural system modeling and optimization methods, especially machine/deep learning methods and related issues to ensure computational and system performance
    Agricultural system sensing and control methods, including robot design, intelligent agents, and deep learning
    Agricultural automated system design and testing, including robot development and system implementation.

Guest editors:

Dr. Yanbo Huang
Genetics and Sustainable Agriculture Research Unit, USDA-ARS, Mississippi State, MS, USA
yanbo.huang@usda.gov

Dr. Lie Tang
Agricultural and Biosystems Engineering, Iowa State University, Ames, IA, USA
lietang@iastate.edu

Dr. Lirong Xiang
Biological and Agricultural Engineering, North Carolina State University, Raleigh, NC, USA
lxiang3@ncsu.edu

Jiajia Li
Electrical and Computer Engineering, Michigan State University, East Lansing, MI, USA
lijiajia@msu.edu

Manuscript submission information:

Submission deadline: 31 Jan 2025
Acceptance deadline: 30 May 2025

To submit your manuscript please go to Computers and Electronics in Agriculture- COMPAG (at https://www.journals.elsevier.com/computers-and-electronics-in-agriculture) and follow the procedures for manuscript submission. When prompted for 'Enter Manuscript Information' you can select our Special Issue Article type as ‘VSI: Agricultural Cybernetics” at https://www.editorialmanager.com/compag/default1.aspx.

Author Guidelines and Manuscript Submission can be found at: https://www.elsevier.com/journals/computers-and-electronics-in-agriculture/0168-1699/guide-for-authors.

Keywords:

Agricultural cybernetics,
Modeling of agricultural systems
System of agricultural systems,
Control of agricultural systems,
Operational control of agricultural production,
Data-driven decision support in agriculture,
Digitalization of farming knowledge
AI and deep learning in agriculture, 
Agricultural robotics.

Learn more about the benefits of publishing in a special issue: https://www.elsevier.com/authors/submit-your-paper/special-issues

Interested in becoming a guest editor? Discover the benefits of guest editing a special issue and the valuable contribution that you can make to your field: https://www.elsevier.com/editors/role-of-an-editor/guest-editors