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 Wearable Sensors for Animal and Plant Information Acquisition
提出日: 2026-08-01

The world is undergoing a revolution in agriculture. AI, Internet of Things (IoT), cloud computing and other innovative technologies are accelerating the development of modern smart agriculture. Information acquisition and processing, which rely on sensors and chips, are key to this revolution towards smart agriculture. This special issue aims to foster innovation and drive progress in modern agriculture by bringing together scholars and researchers with new perspectives on smart wearable sensors and chips in agriculture.

Guest editors:

Dr. Jianfeng Ping
Zhejiang University, Hangzhou, China
jfping@zju.edu.cn

Dr. Yibin Ying
Zhejiang University, Hangzhou, China
ybying@zju.edu.cn

Dr. Jiandong Hu
Henan Agricultural University, Zhengzhou, China
jdhu@henau.edu.cn

Dr. Mazhar Sher
South Dakota State University, Brookings, SD, USA
mazhar.sher@sdstate.edu

Special issue information:

Global food systems are facing unprecedented challenges due to population growth, climate change, and the reduction of arable land. Traditional agriculture, which relies on manual sampling and periodic monitoring, can no longer meet the urgent demand for real-time and precise data acquisition in modern farming. Against this backdrop, emerging intelligent sensing technologies, represented by wearable sensors, have become a critical support to break through information bottlenecks, and drive digital and smart agricultural transformation. Serving as the “perception interface” connecting plants and animals to the digital world, wearable sensors characterized by their flexibility, biocompatibility, and low power consumption can non-invasively or minimally invasively attach to the surfaces or interiors of plants and animals, enabling continuous monitoring and high-resolution data acquisition of their physiological states and behavioral traits. These technologies effectively overcome the limitations of traditional monitoring methods and provide more comprehensive and dynamic information support for the health status of organisms and their environmental responses. With the widespread integration of artificial intelligence and the Internet of Things, the large-scale and multidimensional data generated by wearable sensors can be rapidly mined, modeled, and intelligently analyzed. Leveraging deep learning algorithms and data-driven predictive modeling, these systems enable critical applications including early detection of plant stress, timely pest and disease forecasting, and real-time monitoring of abnormal livestock behavior, shifting agricultural management from reactive responses to proactive perception and active regulation within a closed-loop intelligent control system, thereby promoting the development of an efficient, precise, and sustainable smart agricultural ecosystem.

Manuscript submission information:

Submission Deadline: 01 August 2026

To submit your manuscript, please go to https://www.editorialmanager.com/compag/default1.aspx and follow the procedures for manuscript submission by selecting our Special Issue Article type as "VSI: Wearable Sensors”.

Author Guidelines and Manuscript Submission can be found at: https://www.sciencedirect.com/journal/computers-and-electronics-in-agriculture/publish/guide-for-authors

Keywords:

Smart agriculture; Agricultural information; Animal information; Plant information; Intellisense; Wearable sensors; Flexible sensors; Implantable sensors; Sensing chips; Artificial intelligence; Information acquisition; Optical sensors; Nanosensors