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

TL;DR

This paper introduces a novel lens-free holographic microscopy method for 3D reconstruction and morphological analysis of native Chilean pollen, enabling high-resolution, label-free biophysical characterization.

Contribution

It presents a new scalable, high-resolution 3D imaging technique for native pollen using lens-free digital in-line holography, advancing automated pollen analysis.

Findings

Achieved ~69 nm lateral resolution in 3D pollen imaging.

Quantified biophysical parameters with nanometric precision.

Differentiated pollen species based on morphological features.

Abstract

This study presents a robust methodology for the three-dimensional (3D) volumetric reconstruction and morphological characterization of native Chilean pollen grains using a lens-free Digital In-line Holographic Microscopy (DLHM) system. Utilizing a 532 nm laser point-source configuration and a 3.45 $\mu$m pixel pitch CMOS sensor , we achieved a geometric magnification of 50x, resulting in an effective lateral resolution of approximately 69 nm at the object plane. The complex wavefronts of \textit{Anthemis cotula} (chamomile), \textit{Gevuina avellana} (hazel), and \textit{Conium maculatum} (hemlock) were numerically reconstructed via the Kirchhoff-Helmholtz transform to generate high-fidelity 3D refractive index maps. Biophysical parameters were extracted with nanometric precision, with volumes ranging from $3780.2 \pm 18$ $\mu$m$^3$ to $4320.5 \pm 15$ $\mu$m$^3$. Morphological quantification identified \textit{A. cotula} as the least spherical species ($\Psi = 0.76 \pm 0.03$) due to its characteristic echinate (spiny) exine, while \textit{G. avellana} exhibited the highest sphericity index of $0.89 \pm 0.02$. These results demonstrate that the label-free retrieval of "digital fingerprints" provides a scalable alternative for automated melissopalynology and viability assessment, filling critical geographic data gaps in South American biodiversity hotspots.