ArticlePlant methods2017
A novel 3D imaging system for strawberry phenotyping.
Article in Plant methods, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- Visualization of Three-Dimensional SSC (Soluble Solids Content) Across the Entire Surface of Strawberries Using Near-Infrared Hyperspectral Imaging.Foods (Basel, Switzerland) · 2026Article
- Advancements in 3D Reconstruction for Plant Phenotyping: Technologies, Applications, Challenges, and Future Directions.Sensors (Basel, Switzerland) · 2026Review
- BerryPortraits: Phenotyping Of Ripening Traits cranberry (Vaccinium macrocarpon Ait.) with YOLOv8.Plant methods · 2024Article
- Crop Leaf Phenotypic Parameter Measurement Based on the RKM-D Point Cloud Method.Sensors (Basel, Switzerland) · 2024Article
- Development of a deep-learning phenotyping tool for analyzing image-based strawberry phenotypes.Frontiers in plant science · 2024Article
- Extraction of soybean plant trait parameters based on SfM-MVS algorithm combined with GRNN.Frontiers in plant science · 2023Article
- Introducing Three-Dimensional Scanning for Phenotyping of Olive Fruits Based on an Extensive Germplasm Survey.Plants (Basel, Switzerland) · 2022Article
- Development of Multiple UAV Collaborative Driving Systems for Improving Field Phenotyping.Sensors (Basel, Switzerland) · 2022Article
- A miniaturized phenotyping platform for individual plants using multi-view stereo 3D reconstruction.Frontiers in plant science · 2022Article
- Multivariate Analysis Approaches for Dimension and Shape Discrimination ofPlants (Basel, Switzerland) · 2021Article
- Strawberry fruit shape: quantification by image analysis and QTL detection by genome-wide association analysis.Breeding science · 2021Article
- Application of Hyperspectral Imaging for Maturity and Soluble Solids Content Determination of Strawberry With Deep Learning Approaches.Frontiers in plant science · 2021Article
- Identification for surrogate drought tolerance in maize inbred lines utilizing high-throughput phenomics approach.PloS one · 2021Article
- Automatic Fruit Morphology Phenome and Genetic Analysis: An Application in the Octoploid Strawberry.Plant phenomics (Washington, D.C.) · 2021Article
- Leveraging Image Analysis to Compute 3D Plant Phenotypes Based on Voxel-Grid Plant Reconstruction.Frontiers in plant science · 2020Article
- MVS-Pheno: A Portable and Low-Cost Phenotyping Platform for Maize Shoots Using Multiview Stereo 3D Reconstruction.Plant phenomics (Washington, D.C.) · 2020Article
- Reconstruction method and optimum range of camera-shooting angle for 3D plant modeling using a multi-camera photography system.Plant methods · 2020Article
- Defining strawberry shape uniformity using 3D imaging and genetic mapping.Horticulture research · 2020Article
- Leveraging Image Analysis for High-Throughput Plant Phenotyping.Frontiers in plant science · 2019Review
- Crop Phenomics: Current Status and Perspectives.Frontiers in plant science · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAccurate and quantitative phenotypic data in plant breeding programmes is vital in breeding to assess the performance of genotypes and to make selections. Traditional strawberry phenotyping relies on the human eye to assess most external fruit quality attributes, which is time-consuming and subjective. 3D imaging is a promising high-throughput technique that allows multiple external fruit quality attributes to be measured simultaneously.
resultsA low cost multi-view stereo (MVS) imaging system was developed, which captured data from 360° around a target strawberry fruit. A 3D point cloud of the sample was derived and analysed with custom-developed software to estimate berry height, length, width, volume, calyx size, colour and achene number. Analysis of these traits in 100 fruits showed good concordance with manual assessment methods.
conclusionThis study demonstrates the feasibility of an MVS based 3D imaging system for the rapid and quantitative phenotyping of seven agronomically important external strawberry traits. With further improvement, this method could be applied in strawberry breeding programmes as a cost effective phenotyping technique.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.