A new method for non-invasive biomass determination based on stereo photogrammetry

Applications of hyperspectral imaging in plant phenotyping

Our ability to interrogate and manipulate the genome far exceeds our capacity to measure the effects of genetic changes on plant traits. Much effort has been made recently by the plant science research community to address this imbalance. The responses of plants to environmental conditions can now be defined using a variety of imaging approaches. Hyperspectral imaging (HSI) has emerged as a promising approach to measure traits using a wide range of wavebands simultaneously in 3D to capture information in lab, glasshouse, or field settings. HSI has been applied to define abiotic, biotic, and quality traits for optimisation of crop management.

A miniaturized phenotyping platform for individual plants using multi-view stereo 3D reconstruction

Plant phenotyping is essential in plant breeding and management. High-throughput data acquisition and automatic phenotypes extraction are common concerns in plant phenotyping. Despite the development of phenotyping platforms and the realization of high-throughput three-dimensional (3D) data acquisition in tall plants, such as maize, handling small-size plants with complex structural features remains a challenge. This study developed a miniaturized shoot phenotyping platform MVS-Pheno V2 focusing on low plant shoots. The platform is an improvement of MVS-Pheno V1 and was developed based on multi-view stereo 3D reconstruction. It has the following four components: Hardware, wireless communication and control, data acquisition system, and data processing system. The hardware sets the rotation on top of the platform, separating plants to be static while rotating. A novel local network was established to realize wireless communication and control; thus, preventing cable twining. The data processing system was developed to calibrate point clouds and extract phenotypes, including plant height, leaf area, projected area, shoot volume, and compactness. This study used three cultivars of wheat shoots at four growth stages to test the performance of the platform. The mean absolute percentage error of point cloud calibration was 0.585%. The squared correlation coefficient R ² was 0.9991, 0.9949, and 0.9693 for plant height, leaf length, and leaf width, respectively. The root mean squared error (RMSE) was 0.6996, 0.4531, and 0.1174 cm for plant height, leaf length, and leaf width. The MVS-Pheno V2 platform provides an alternative solution for high-throughput phenotyping of low individual plants and is especially suitable for shoot architecture-related plant breeding and management studies.

Photogrammetry as an alternative for acquiring digital dental models: A proof of concept

Photogrammetry is a mathematical technique that generates three-dimensional coordinates of specific points identified from multiple images of the same object obtained at different angles. This technique may be a low-cost alternative for traditional scanning. The objective of this proof of concept was to evaluate the accuracy and precision in obtaining digital models (DM) from a plaster model (PM) using photogrammetry. Five DM were generated from 50 photographs taken surrounding the PM. The photographs were taken by a single operator on five consecutive days using natural light. The images obtained were processed on 3DF Zephyr Free software. The height and width of all teeth were recorded on both PM and DM, as well as the distance between the canine cusps (C-C) and between the mesiobuccal cusps of the first molars (1 M-1 M). For the PM the measurements were taken with a digital caliper, whereas the DM was measured using the software Blender. The DM and PM measurements presented a limit of agreement between -0.433 and 0.611 mm. The accuracy of DM measurements showed a SD of ±0.171 mm and a repeatability coefficient of 0.474. In the superimposition of all DM, it was possible to notice a greater discrepancy in the posterior region of the arch and palate, but this difference decreased when the region was segmented. It can be concluded that photogrammetry appears to be a viable technique for the digitization of dental models. Further studies need to be performed to evaluate its clinical application.