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Chemosensors
Special Issues
Application of Chemical Sensors in Smart Agriculture
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Application of Chemical Sensors in Smart Agriculture

A special issue of Chemosensors (ISSN 2227-9040). This special issue belongs to the section "Applied Chemical Sensors".

Deadline for manuscript submissions: 1 October 2026 | Viewed by 4659

Special Issue Editors

Prof. Dr. Yong Zhang

E-Mail Website
Guest Editor
School of Energy and Environment Science, Yunnan Normal University, Kunming 650500, China
Interests: low-dimensional optoelectronic functional nanomaterials and metal nanomaterials; electroanalysis and chemical sensing detection
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yingshu Guo

E-Mail Website
Guest Editor
School of Chemistry and Chemical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
Interests: biological and electrochemical sensing; environmental and energy chemistry; food analysis; cell imaging
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. He Li

E-Mail Website
Guest Editor
College of Optoelectronics Technology, Chengdu University of Information Technology, Chengdu 610225, China
Interests: biosensors; electroanalytical sensors; optoelectronic materials and devices; new energy materials and devices
Dr. Sixia Yang

E-Mail Website
Guest Editor
School of Energy and Environment Science, Yunnan Normal University, Kunming 650500, China
Interests: nanosensor and biosensor technologies; AI-integrated sensors in precise biological control; sensor array technologies

Special Issue Information

Dear Colleagues,

The rapid development of smart agriculture is inseparable from precise sensing technologies, among which chemical sensors have become a key driving force for agricultural modernization. With their high accuracy, stability, miniaturization, and cost-effectiveness, chemical sensors can effectively meet the diverse needs of smart agriculture, including soil nutrient detection, crop growth monitoring, pest and disease surveillance, and environmental sensing. This Special Issue focuses on the cutting-edge applications of chemical sensors in smart agriculture, gathering the latest global research achievements and highlighting their important roles in agricultural IoT.

This Special Issue will provide a high-profile platform for the application of chemical sensors in smart agriculture, promoting academic exchange and technology dissemination and facilitating the deep integration of chemical sensor technology with smart agriculture. We look forward to your active participation, as well as to working together to explore the future of smart agriculture and contribute to the sustainable development of global agriculture.

Prof. Dr. Yong Zhang
Prof. Dr. Yingshu Guo
Prof. Dr. He Li
Dr. Sixia Yang
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. Chemosensors 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 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.

Keywords

  • agricultural environmental monitoring sensors
  • crop growth monitoring sensors
  • pest and disease early warning sensors
  • functional materials-based sensors
  • AI-integrated sensors
  • miniaturized sensor technology

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Published Papers (2 papers)

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22 pages, 12718 KB  
Article
Machine Learning-Assisted Dual-pH Electrochemical Sensor for Rapid Detection of Quercetin, Rutin and Glucose in Litchi Fruit
by Lihua Jiang, Miaoyang Chen, Jun Zhu, Gang Chen, Shaohua Huang and Haitao Xu
Chemosensors 2026, 14(6), 122; https://doi.org/10.3390/chemosensors14060122 - 22 May 2026
Viewed by 124
Abstract
Electrochemical sensing provides an alternative approach for the trace detection of bioactive substances in fruits. However, the complex matrix in fruit tissues, the coexistence of multiple active components, and the varied pH environments limit the sensing performance and accurate quantitative detection of conventional [...] Read more.
Electrochemical sensing provides an alternative approach for the trace detection of bioactive substances in fruits. However, the complex matrix in fruit tissues, the coexistence of multiple active components, and the varied pH environments limit the sensing performance and accurate quantitative detection of conventional electrochemical sensors. Herein, a dual-mode electrochemical sensor based on a Co3O4@N-MWCNTs modified glassy carbon electrode was developed for the sequential detection of quercetin, rutin, and glucose in fruits under acidic and alkaline conditions. The as-prepared electrode exhibited improved charge transfer efficiency and favorable electrocatalytic activity toward the three target analytes. Under optimal conditions, the sensor displayed wide linear ranges of 0.5~70 μM for quercetin and 0.5~5 μM for rutin in acidic environment, with low detection limits of 0.124 μM and 0.045 μM, respectively. In alkaline environment, the detection limit for glucose was determined to be 8.86 μM. Moreover, four combined machine learning models with feature selection algorithms were established, among which the CARS-RFE+RFR model achieved the best prediction accuracy and robustness for multicomponent quantification. Furthermore, the proposed sensing system was applied to the rapid determination of quercetin, rutin, and glucose in real litchi samples, with recoveries ranging from 98.4% to 105.4%. This study provides a feasible electrochemical strategy for multicomponent detection in complex plant matrices, showing good applicability for rapid on-site analysis in agricultural and food-related applications. Full article
(This article belongs to the Special Issue Application of Chemical Sensors in Smart Agriculture)
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Review

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32 pages, 3930 KB  
Review
Recent Advances in Agricultural Sensors: Towards Precision and Sustainable Farming
by Jiaqi Lin and Shuping Wu
Chemosensors 2025, 13(11), 399; https://doi.org/10.3390/chemosensors13110399 - 14 Nov 2025
Cited by 3 | Viewed by 3739
Abstract
Global population growth, intensifying climate change, and escalating food security demands are mounting. In response, modern agriculture must transcend the limitations of traditional experience-based cultivation models to address issues such as low resource utilization, poor environmental adaptability, and significant yield fluctuations. As the [...] Read more.
Global population growth, intensifying climate change, and escalating food security demands are mounting. In response, modern agriculture must transcend the limitations of traditional experience-based cultivation models to address issues such as low resource utilization, poor environmental adaptability, and significant yield fluctuations. As the core technical support of smart agriculture, agricultural sensors have become the key to transformation. This review systematically introduces the classification and working principles of current mainstream agricultural sensors: according to the monitoring parameters, they can be divided into humidity sensors, light sensors, gas sensors, pressure sensors, nutrient sensors, etc. At the same time, breakthroughs in emerging technologies such as microneedle sensing, nanosensing, and wireless sensor networks are being explored, which are breaking the application limitations of traditional sensors in complex agricultural environments. Combined with specific cases, the practical value of sensor technology is improving in agricultural drought monitoring, soil detection, and agricultural product quality assessment. Looking ahead, if agricultural sensors can overcome existing limitations through breakthroughs in material innovation, multi-sensor unit integration, and artificial intelligence algorithm fusion, this will provide stronger technological support for the further advancement of smart agriculture. Full article
(This article belongs to the Special Issue Application of Chemical Sensors in Smart Agriculture)
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