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Vibe for research labs

Grain and Seed Phenotyping
Built for Research

High-throughput, non-destructive phenotyping and analytical solutions for the grain industry. Quantify morphology, L*a*b* color, defects, and purity with consistent, repeatable measurements. Export bioinformatics-ready CSV/Parquet outputs compatible with R and Python pipelines.

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Vibe QM imaging system and analysis UI
QM3i Analyzer imaging system and analysis software for grain quality, purity, and seed phenotyping.

Used By

University and research labs worldwide

Standardized

Protocols across operators and seasons

Publication-Ready Data

Outputs (CSV + images + metadata)

Research-grade

Consistency across sites and time

Partners

Used by Leading Institutions

High-throughput phenotyping programs at agricultural universities, research centers, and breeding labs rely on Vibe for reproducible, non-destructive grain and seed imaging with genotype-to-phenotype workflows that stay consistent across operators, seasons, and sites.

University of Arkansas logo

University of Arkansas

Fayetteville, AR, USA

A public land-grant research university in Fayetteville, Arkansas, with long-standing programs in agricultural and food science.

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Publications

Peer-reviewed publications using Vibe instruments

Peer-reviewed evidence from breeding programs and grain quality labs using Vibe for high-throughput phenotyping (HTP), morphological profiling, and non-destructive seed analysis. Browse the publications library for methods, citations, and genotype-to-phenotype research.

Improving panicle blast resistance and fragrance in a high-quality japonica rice variety through breeding

Shanghai Academy of Agricultural Sciences

Improving panicle blast resistance and fragrance in a high-quality japonica rice variety through breeding

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Coverage

Crop types commonly analyzed in research labs

From morphological profiling to color characterization - workflows handle varieties, mixtures, and custom label definitions for any crop.

Key outputs

Per-kernel morphological profiling, size distributions, broken-grain percentage, defect indicators, purity metrics, and L*a*b* color features, all exportable for downstream bioinformatics and R/Python analysis.

Morphological profiling
L*a*b* Color
Defect detection
Purity
Size distributions

Rice

Rice phenotyping for breeding programs, agricultural universities, and research institutes: per-kernel morphology, color, chalkiness, translucency, and integrity across paddy, brown, milled, parboiled, and specialty cultivar material. Trait distributions can be compared across breeding lines, trials, and environments, with per-kernel images and structured data exported for statistical analysis.

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Workflows

Lab workflows and protocols

Practical workflows for purity testing, grading, defect detection, morphology, and more. Each workflow shows what to measure, how to run it, and which outputs to export. Explore the workflow library for additional examples.

Wheat FDK Detection: Fusarium-Damaged Kernel Analysis
Grain Quality & Screening

Wheat FDK Detection: Fusarium-Damaged Kernel Analysis

Automated Fusarium-damaged kernel (FDK) screening using imaging-based morphology and color analysis to quantify FDK prevalence as a quality-control indicator.

About

Built for publishable, repeatable grain and seed research

Vibe helps research teams run high-throughput, non-destructive phenotyping with consistent measurements comparable across operators, seasons, and sites. This hub brings together peer-reviewed publications, bioinformatics-ready datasets, and validated laboratory workflows.

High-Throughput Phenotyping (HTP)
Bioinformatics-Ready Exports (CSV/Parquet)
Consistent, Repeatable Measurements
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FAQ

Common questions from research teams

Short answers focused on repeatability, workflows, and exports.


Vibe is a high-throughput, non-destructive imaging platform for reproducible grain and seed phenotyping, built so research labs get consistent, repeatable measurements for every analysis.

Per-kernel morphological profiling (length, width, area, shape), L*a*b* color, defect indicators, purity, broken-grain percentage, and batch comparisons - all exportable as CSV/Parquet for R and Python pipelines.

Yes. The QM3i Analyzer uses optical imaging - samples are not altered, so the same material remains available for further downstream analysis.

Yes. Exports include structured CSV/Parquet tables with analysis metadata so downstream analysis is fully reproducible and figures can be regenerated without manual steps.

Yes. Rapid, high-throughput analysis makes it practical for large breeding trials and genotype-to-phenotype studies.

Yes. Samples are analyzed sequentially with barcode scanning and results aggregated automatically, designed to support breeding programs with large sample volumes.

Most start with a short demo, confirm the protocol and outputs match their study needs, then run a limited-scope pilot before expanding to more crop types and workflows.