Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Digital Biomass Accumulation Using High-Throughput Plant Phenotype Data Analysis.

Journal of integrative bioinformatics - 1 Sept 2017

Rahaman Md Matiur, Ahsan Md Asif, Gillani Zeeshan, Chen Ming

Abstract excerpt

Biomass is an important phenotypic trait in functional ecology and growth analysis. The typical methods for measuring biomass are destructive, and they require numerous individuals to be cultivated for repeated measurements. With the advent of image-based high-throughput plant phenotyping facilities, non-destructive biomass measuring methods have attempted to overcome this problem. Thus, the estimation of plant...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Biomass
Share to Droughts
Share to Image Processing, Computer-Assisted

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Phenotype

Share to Plants

Share to Stress, Physiological

Source

Open in PubMed Open full text

Identifiers

PMID: 28862986
DOI: 10.1515/jib-2017-0028
PMCID: PMC6042821

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026. Manifest publication-graph-cohort-2026-09-05.1.

Source receipt: pubmed, retrieved 5 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Digital Biomass Accumulation Using High-Throughput Plant Phenotype Data Analysis.PMID 28862986Read ↗

Predicting plant biomass accumulation from image-derived parameters.Semantic proximity Read ↗

Genetic analysis of predicted vegetative biomass and biomass-related traits from digital phenotyping of strawberry.Semantic proximity Read ↗

A growth phenotyping pipeline for Arabidopsis thaliana integrating image analysis and rosette area modeling for robust quantification of genotype effects.Semantic proximity Read ↗

Advancements in 3D Reconstruction for Plant Phenotyping: Technologies, Applications, Challenges, and Future Directions.Semantic proximity Read ↗

An Overview of High-Throughput Crop Phenotyping: Platform, Image Analysis, Data Mining, and Data Management.Semantic proximity Read ↗

Functional approach to high-throughput plant growth analysis.Semantic proximity Read ↗

Growth Analysis of Wheat Using Machine Vision: Opportunities and Challenges.Semantic proximity Read ↗

A comparative study of plant phenotyping workflows based on three-dimensional reconstruction from multi-view imagesSemantic proximity Read ↗

An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis.Semantic proximity Read ↗

Affordable Imaging Lab for Noninvasive Analysis of Biomass and Early Vigour in Cereal Crops.Semantic proximity Read ↗

A Straightforward High-Throughput Aboveground Phenotyping Platform for Small- to Medium-Sized Plants.Semantic proximity Read ↗

RGB images-based vegetative index for phenotyping kenaf (Hibiscus cannabinus L.).Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.