Studying flowers in 3D using photogrammetry

And growth on form? How tissue expansion generates novel shapes, colours and enhance biological functions of Turing colour patterns of Eukaryotes

Evidenced in zebrafishes skin and Mimulus petal, Turing-like mechanisms are probably responsible for many periodic color patterns of Eukaryotes. They are characterized by the mathematical relationships linking their cellular or molecular actors, the periodicity and the geometrical range of the patterns they produce: spots, stripes or mazes. Nevertheless, some periodic patterns such as leopard iconic rosettes required additional ingredients to explain their formation. Growth being the main candidate, we extensively explore its multiple facets, at the Eukaryotes scale. We show that far beyond the particular feline coat pattern, putative-growth Turing color patterns are present in many diverse lineages of plants and animals and seem absent in Fungi and unicellular lineages. Using models, we show the many ways growth can induce new shapes and colors, and that putative-growth pattern locations correlates with tissue hot spots of growth, suggesting the latter as the underlying mechanism. By reverse reasoning, we show that growth effects could reveal crucial information about pattern formation. We show how putative growth patterns can contribute to influence organisms visibility, thereby improving camouflage or aposematism. Our results demonstrate the range of morphogenetic roles that tissue expansion can take, by interacting with a scale-sensitive mechanism, here Turing-like patterning. Considering this extensive overview of its biological importance, both qualitatively and quantitatively, links between growth and form might more than ever needed to be explored.

Petal segmentation in CT images based on divide-and-conquer strategy

Manual segmentation of the petals of flower computed tomography (CT) images is time-consuming and labor-intensive because the flower has many petals. In this study, we aim to obtain a three-dimensional (3D) structure of Camellia japonica flowers and propose a petal segmentation method using computer vision techniques. Petal segmentation on the slice images fails by simply applying the segmentation methods because the shape of the petals in CT images differs from that of the objects targeted by the latest instance segmentation methods. To overcome these challenges, we crop two-dimensional (2D) long rectangles from each slice image and apply the segmentation method to segment the petals on the images. Thanks to cropping, it is easier to segment the shape of the petals in the cropped images using the segmentation methods. We can also use the latest segmentation method for the task because the number of images used for training is augmented by cropping. Subsequently, the results are integrated into 3D to obtain 3D segmentation volume data. The experimental results show that the proposed method can segment petals on slice images with higher accuracy than the method without cropping. The 3D segmentation results were also obtained and visualized successfully.

3D documentation and classification of incense tree Aquilaria sinensis (Lour.) Spreng. wounds by photogrammetry and its potential conservation applications

In recent years, illegal felling of and damage to the incense tree Aquilaria sinensis (Lour.) Spreng. have been reported in Hong Kong. Their native populations are under increasingly severe threat. Therefore, the development of a standard and efficient method to classify and document wounds on vulnerable trees is urgently needed for conservation purposes. In this study, photogrammetry was used to document wounds in A. sinensis through 3D modeling. A total of 752 wound records from 484 individual A. sinensis trees from Hong Kong were included to establish a new wound classification system. Our major findings include a novel standardized procedure for photogrammetric documentation and a wound classification system. The results of this study will facilitate A. sinensis conservation, by enhancing wound documentation and information transfer to law enforcement and education.

Increasing the impact of vertebrate scientific collections through 3D imaging: The openVertebrate (oVert) Thematic Collections Network

The impact of preserved museum specimens is transforming and increasing by three-dimensional (3D) imaging that creates high-fidelity online digital specimens. Through examples from the openVertebrate (oVert) Thematic Collections Network, we describe how we created a digitization community dedicated to the shared vision of making 3D data of specimens available and the impact of these data on a broad audience of scientists, students, teachers, artists, and more. High-fidelity digital 3D models allow people from multiple communities to simultaneously access and use scientific specimens. Based on our multiyear, multi-institution project, we identify significant technological and social hurdles that remain for fully realizing the potential impact of digital 3D specimens.

3D pollination biology using micro-computed tomography and geometric morphometrics in Theobroma cacao

Premise

Imaging technologies that capture three-dimensional (3D) variation in floral morphology at micro- and nano-resolutions are increasingly accessible. In herkogamous flowers, such as those of Theobroma cacao, structural barriers between anthers and stigmas represent bottlenecks that restrict pollinator size and access to reproductive organs. To study the unresolved pollination biology of cacao, we present a novel application of micro-computed tomography (micro-CT) using floral dimensions to quantify pollinator functional size limits.

Methods

We generated micro-CT data sets from field-collected flowers and museum specimens of potential pollinators. To compare floral variation, we used 3D Slicer to place landmarks on the surface models and performed a geometric morphometric (GMM) analysis using geomorph R. We identified the petal side door (an opening between the petal hoods and filament) as the main bottleneck for pollinator access. We compared its mean dimensions with proposed pollinators to identify viable candidates.

Results

We identified three levels of likelihood for putative pollinators based on the number of morphological (body) dimensions that fit through the petal side door. We also found floral reward microstructures whose presence and location were previously unclear.

Discussion

Using micro-CT and GMM to study the 3D pollination biology of cacao provides new evidence for predicting unknown pollinators. Incorporating geometry and floral rewards will strengthen plant-pollinator trait matching models for cacao and other species.

Using photogrammetry to create virtual permanent plots in rare and threatened plant communities

Premise

Many plant communities across the world are undergoing changes due to climate change, human disturbance, and other threats. These community-level changes are often tracked with the use of permanent vegetative plots, but this approach is not always feasible. As an alternative, we propose using photogrammetry, specifically photograph-based digital surface models (DSMs) developed using structure-from-motion, to establish virtual permanent plots in plant communities where the use of permanent structures may not be possible.

Methods

In 2021 and 2022, we took iPhone photographs to record species presence in 1-m2 plots distributed across alpine communities in the northeastern United States. We then compared field estimates of percent coverage with coverage estimated using DSMs.

Results

Digital surface models can provide effective, minimally invasive, and permanent records of plant species presence and percent coverage, while also allowing managers to mark survey locations virtually for long-term monitoring. We found that percent coverage estimated from DSMs did not differ from field estimates for most species and substrates.

Discussion

In order to continue surveying efforts in areas where permanent structures or other surveying methods are not feasible, photogrammetry and structure-from-motion methods can provide a low-cost approach that allows agencies to accurately survey and record sensitive plant communities through time.