Serial section videography (SSV): A low‐cost protocol for generating 3D reconstructions of internal plant structure

Abstract

Premise Analyzing structural changes along the length of an organ provides insight into its development. However, traditional histological methods are limited by intensive procedures and size restrictions. Micro-computed tomography (microCT) enables non-destructive internal imaging along the length of an organ, but high cost, technical complexity, and limited accessibility hinder widespread application. Here, we describe serial section videography (SSV), a new low-cost technique for generating three-dimensional (3D) reconstructions of internal plant anatomy using serial sectioning and open-source software. Methods and results SSV was applied to four fern rhizomes with varied gross morphology and diverse vascular architectures. Specimens were sectioned using a sliding microtome or a handheld blade, and imaged using either a digital camera or smartphone setup. Images were aligned using Fiji and segmented using 3D Slicer. The SSV method enabled continuous visualization of internal stem anatomy over several centimeters and is adaptable to both laboratory and field settings. Conclusions This protocol offers an alternative to microCT for generating 3D anatomical reconstructions, enabling researchers to examine development and structural variation across organs with minimal equipment and software. This accessible protocol reduces technical and financial barriers and is particularly well-suited for comparative studies of vascular tissues, advancing the study of plant anatomy and development.

Plant phenotyping relevance

植物器官内部構造を連続撮像・画像処理して3D形態を再構成する低コスト手法の開発と適用が中心であり、植物形態・解剖状態の取得法として収載対象。

Code and data availability

The paper describes the SSV protocol applied to four fern rhizomes, with four aligned developmental videos and 3D reconstructions as paper-specific outputs. However, the data availability statement says only 'All data are provided in the manuscript' with no public deposit, repository, or author URL for the image stacks

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