Unknown

Dataset Information

0

A Three-Dimensional Scanning System for Digital Archiving and Quantitative Evaluation of Arabidopsis Plant Architectures.


ABSTRACT: A plant's architecture contributes to its ability to acquire resources and reduce mechanical load. Arabidopsis thaliana is the most common model plant in molecular biology, and there are several mutants and transgenic lines with modified plant architecture regulation, such as lazy1 mutants, which have reversed angles of lateral branches. Although some phenotyping methods have been used in larger agricultural plants, limited suitable methods are available for three-dimensional reconstruction of Arabidopsis, which is smaller and has more uniform surface textures and structures. An inexpensive, easily adopted three-dimensional reconstruction system that can be used for Arabidopsis is needed so that researchers can view and quantify morphological changes over time. We developed a three-dimensional reconstruction system for A. thaliana using the visual volume intersection method, which uses a fixed camera to capture plant images from multiple directions while the plant slowly rotates. We then developed a script to autogenerate stack images from the obtained input movie and visualized the plant architecture by rendering the output stack image using the general bioimage analysis software. We successfully three-dimensionally and time-sequentially scanned wild-type and lazy1 mutant A. thaliana plants and measured the angles of the lateral branches. This non-contact, non-destructive method requires no specialized equipment and is space efficient, inexpensive and easily adopted by Arabidopsis researchers. Consequently, this system will promote three- and four-dimensional phenotyping of this model plant, and it can be used in combination with molecular genetics to further elucidate the molecular mechanisms that regulate Arabidopsis architecture.

SUBMITTER: Kunita I 

PROVIDER: S-EPMC8711699 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC5945589 | biostudies-literature
| S-EPMC9919470 | biostudies-literature
| S-EPMC7978426 | biostudies-literature
| S-EPMC9418730 | biostudies-literature
| S-EPMC5897379 | biostudies-literature
| S-EPMC2917646 | biostudies-literature
| S-EPMC5539490 | biostudies-literature
| S-EPMC8105620 | biostudies-literature
| S-EPMC8647179 | biostudies-literature
| S-EPMC5689986 | biostudies-literature