Recent Advances in Smart Polymer Composites for Plant Health Monitoring: A Strategic Integration of Sensing Mechanisms and Computational Intelligence

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Year : 2026 | Volume : 14 | 03 | Page :
    By

    Arvind Rehalia,

  • Kajal Kaul,

  • Surinder Kaur,

  • Ruchi Sharma,

  • Sanjeev Sanyal,

  1. Associate Professor, Department of Information Technology, Bharati Vidyapeeth’s College of Engineering, New Delhi, India
  2. Assistant Professor, Department of Information Technology, Bharati Vidyapeeth’s College of Engineering, New Delhi, India
  3. Associate Professor, Department of Information Technology, Bharati Vidyapeeth’s College of Engineering, New Delhi, India
  4. Associate Professor, Department of Information Technology, Bharati Vidyapeeth’s College of Engineering, New Delhi, India
  5. Assistant Professor, Department of Computer Science, IMS Engineering College, Ghaziabad, Uttar Pradesh, IndiaPolymer Composites, Plant Health, Sensing, Deep Learning, Quality Assessment

Abstract

Plant health assessment is crucial for agricultural production and food security, as plant diseases significantly affect crop yields and quality. This paper reviews the applications of polymers and composite materials in the evaluation of plant health, focusing on both natural and artificial polymers, carbon materials, and polymeric–nanoparticle composite materials. Various types of sensing principles, such as colorimetry, fluorimetry, surface plasmon resonance (SPR), surface enhanced Raman scattering (SERS), and interferometry, are examined, as well as optical, electrochemical, and volatile organic compounds (VOCs)-based methods combined with imaging tools. Traditional methods are also considered for comparison purposes. In addition, the research examines the approaches used to process the obtained data using polymer systems, paying particular attention to deep learning algorithms and pattern recognition, as well as image processing techniques. Some limitations, including environmental stability, selectivity, scale-up, user friendliness, and regulatory issues, are identified. Also, various Research Questions, Quality Assessment attributes, the mapping of RQs with QAs and Literature Review has been formulated to analyze the role of the approaches for Plant Health Assessment. These approaches pave the way forward for future innovation and research in this field. It is then followed by the Result and Conclusion sections, and later by the future scope.

Keywords: Polymer Composites, Plant Health, Sensing, Deep Learning, Quality Assessment

How to cite this article:
Arvind Rehalia, Kajal Kaul, Surinder Kaur, Ruchi Sharma, Sanjeev Sanyal. Recent Advances in Smart Polymer Composites for Plant Health Monitoring: A Strategic Integration of Sensing Mechanisms and Computational Intelligence. Journal of Polymer & Composites. 2026; 14(03):-.
How to cite this URL:
Arvind Rehalia, Kajal Kaul, Surinder Kaur, Ruchi Sharma, Sanjeev Sanyal. Recent Advances in Smart Polymer Composites for Plant Health Monitoring: A Strategic Integration of Sensing Mechanisms and Computational Intelligence. Journal of Polymer & Composites. 2026; 14(03):-. Available from: https://journals.stmjournals.com/jopc/article=2026/view=249463


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Ahead of Print Subscription Original Research
Volume 14
03
Received 15/04/2026
Accepted 06/07/2026
Published 11/07/2026
Publication Time 87 Days
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