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Three-Dimensional Volumetric Reconstruction of Native Chilean Pollen via Lens-Free Digital In-line Holographic Microscopy

J. Staforelli-Vivanco, V. Salamanca-Levi, R. Jofré-Cerda, M. Rondanelli-Reyes, I. Lamas

TL;DR

This work tackles the need for label-free, 3D pollen morphometrics to support melissopalynology and biodiversity assessment in Chile. It adopts lens-free Digital In-line Holographic Microscopy (DLHM) and the Kirchhoff-Helmholtz formalism to reconstruct a 3D refractive-index map from single holograms, yielding quantitative morphology such as volume $V$, surface area $S$, and Wadell's sphericity $\Psi$. The approach successfully characterizes native pollen species Gevuina avellana, Conium maculatum, and Anthemis cotula, achieving nanometric lateral resolution and demonstrating exine-driven shape differences, with potential for automated honey authentication and environmental monitoring. The study lays a foundation for scalable, automated pollen analysis and highlights future directions including multifocal stacks and real-time classification with deep learning frameworks.

Abstract

This study presents a robust methodology for the 3D volumetric reconstruction of native Chileanpollen grains, specifically Gevuina avellana (hazel),Conium maculatum (hemloc) and Anthemis cotula (chamomile). Using a lens-free Digital In-line Holographic Microscopy (DLHM) system, we capture complex interference patterns that are numerically reconstructed using the Kirchhoff-Helmholtz transform. Our results demonstrate that this label-free approach provides high-fidelity morphological characterization and nanometric precision in biophysical parameter extraction, offering a scalable alternative for automated melissopalynology and environmental monitoring.

Three-Dimensional Volumetric Reconstruction of Native Chilean Pollen via Lens-Free Digital In-line Holographic Microscopy

TL;DR

This work tackles the need for label-free, 3D pollen morphometrics to support melissopalynology and biodiversity assessment in Chile. It adopts lens-free Digital In-line Holographic Microscopy (DLHM) and the Kirchhoff-Helmholtz formalism to reconstruct a 3D refractive-index map from single holograms, yielding quantitative morphology such as volume , surface area , and Wadell's sphericity . The approach successfully characterizes native pollen species Gevuina avellana, Conium maculatum, and Anthemis cotula, achieving nanometric lateral resolution and demonstrating exine-driven shape differences, with potential for automated honey authentication and environmental monitoring. The study lays a foundation for scalable, automated pollen analysis and highlights future directions including multifocal stacks and real-time classification with deep learning frameworks.

Abstract

This study presents a robust methodology for the 3D volumetric reconstruction of native Chileanpollen grains, specifically Gevuina avellana (hazel),Conium maculatum (hemloc) and Anthemis cotula (chamomile). Using a lens-free Digital In-line Holographic Microscopy (DLHM) system, we capture complex interference patterns that are numerically reconstructed using the Kirchhoff-Helmholtz transform. Our results demonstrate that this label-free approach provides high-fidelity morphological characterization and nanometric precision in biophysical parameter extraction, offering a scalable alternative for automated melissopalynology and environmental monitoring.
Paper Structure (8 sections, 6 equations, 5 figures, 1 table)

This paper contains 8 sections, 6 equations, 5 figures, 1 table.

Table of Contents

  1. Introduction
  2. Mathematical Formalism
  3. Experimental Methodology
  4. Sample Selection
  5. Experimental Setup
  6. Morphological feature extraction
  7. Results and Discussion
  8. Conclusions

Figures (5)

  • Figure 1: Sample collection. In this stage, plants are collected and preserved for subsequent botanical identification. Along with this, the stamens are extracted from the flower buds, which contain the pollen grains used to create a reference pollen collection. This collection will help identify the pollens present in the honey and also allows for the study of individual pollen morphology. Due to seasonality, this process must be carried out during the period of greatest annual flowering, which spans the months of October 2024/25 to April 2025/26.
  • Figure 2: a. Samples are placed in microscopic chambers containing the pollen solution. These chambers are made with glass coverslips $\#1$ and $\#0$, sealed with epoxy film and plastic. b. concentrate was mounted using Hydromatrix mounting medium to perform a microscopic analysis to carry out pollen counting using an optical microscope (10X and 40X). c. Detail of the HM assembly in its version with lenses, with the sample microcamera and objective lenses confronted for simultaneous focusing and visualization of the laser (right) and the collection of light for the detection of the hologram interference pattern (left). d. Proof of principle of operation, calibration and imaging with test-target pollen samples of various species, including d.1 Gevuina avellana (hazel), d.2 Medicago Sativa (alfalfa), d.3-4 Anthemis cotula (chamomile), d.5-11 Colletia hystrix (yaqui), d.6 Convolvulus arvensis (Bindweed), d.7 Conium maculatum (hemlock), d.8 Trifolium pratense (Red clover), d.9 Mentha pulegium (pennyroyal), d.10 Quillaja saponaria (Soapbark) and d.12 Cissus striata (voqui)
  • Figure 3: The system illuminates the sample with a 532 nm laser, capturing a digital hologram of the pollen. A three-dimensional (3D) image of each pollen grain from the interference holograms is generated using Laty-mchevskaia and Fink algorithms for 2D objects reconstruction implemented in Matlab© and Python© with Numpy, scipy and matplotlib as special packages for 3D reconstrucction, and keras for image load. Additional guidelines were taken from Federico Capasso et al. Capasso2023.
  • Figure 4: "digital fingerprint" of pollen grains based on their inherent material properties.
  • Figure 5: Anthemis cotula (Sample a) exhibits a lower sphericity index due to its characteristic echinate (spiny) exine, which significantly increases the surface-to-volume ratio. In contrast, the triangular symmetry of Gevuina avellana (Sample b) and the prolate geometry of Conium maculatum (Sample c) are accurately captured in the volumetric reconstructions, consistent with traditional palynological descriptions.