Journal of Entomological Research
SCOPUSWeb of Science
  • Year: 2025
  • Volume: 49
  • Issue: 1

Advances in digital imaging techniques for insect morphological studies

  • Author:
  • Ved Vrat Verma*, Kollathur Sudheer1, Shitij Goyal2, Jaspreet Sidhu3, Manish Nagpal4
  • Total Page Count: 7
  • Page Number: 185 to 191

1Centre for Multidisciplinary Research, Anurag University, Hyderabad - 500 088, Telangana, India; Orcid Id : 0009-0001-2178-9878

2Quantum University Research Center, Quantum University, Roorkee - 247 667, Uttarakhand, India; Orcid Id : 0009-0002-5558-8238

3Centre of Research Impact and Outcome, Chitkara University, Rajpura - 140 417, Punjab, India; Orcid Id : https://orcid.org/0009-0002-5658-5629

4Chitkara Centre for Research and Development, Chitkara University, Solan - 174 103, Himachal Pradesh, India; Orcid Id : https://orcid.org/0009-0000-9823-5251

Department of Biotechnology, Noida International University, Greater Noida, Gautam Budh Nagar - 201 310, Uttar Pradesh, India

*Corresponding authors’ E-mail : ved.verma@niu.edu.in, Orcid Id : 0000-0002-2596-2578

Online Published on 13 May, 2025.

Abstract

The field of entomology has witnessed significant advancements in digital imaging techniques that facilitate detailed morphological studies of insects. This chapter explores recent advancements in digital imaging techniques that have revolutionized the study of insect morphology. By integrating high-resolution imaging, 3D reconstruction, and machine learning algorithms, researchers can now analyze insect structures with unprecedented precision and efficiency. Insect morphology provides critical insights into evolutionary biology, ecology, and taxonomy. Traditional imaging methods, such as light microscopy, often fall short in capturing fine details and complex structures. Recent advancements in digital imaging technologies have emerged as game-changers, enabling detailed morphological studies that were previously unattainable.

Keywords

3D reconstruction, Analysis, Automation, Digital imaging, Entomology, Evolution, Fluorescence, High-resolution, High-throughput, Insects, Machine learning, Morphology, Structural analysis, Taxonomy, Techniques