Crop profile

Sorghum genomics & breeding

Sorghum bicolor · USA, Nigeria, Sudan, India, Mexico, Ethiopia

Sorghum thrives where maize fails — heat, drought, and low fertility. Genomic prediction and stress-trait GWAS make it possible to stack resilience without giving up yield.

~60 million tonnes, a key resilience crop for semi-arid regions.

Typical breeding goals

•Grain yield under drought
•Stay-green and heat tolerance
•Stalk strength
•Bird and midge resistance

Common challenges

•Drought
•Striga
•Sorghum midge
•Lodging

Pre-loaded trait library

When you upload sorghum data, our phenotype column picker pre-suggests these standard traits so you don't start from a blank slate.

Yield

yield · t/ha

Biomass

biomass · t/ha

Days to flowering

days_to_flowering · days

Days to maturity

days_to_maturity · days

Plant height

plant_height · cm

Drought tolerance score

drought_tolerance · 0–10

Heat tolerance score

heat_tolerance · 0–10

Disease resistance score

disease_resistance · 0–10

Tannin

tannin_pct · %

What you can run on sorghum data

Every module below works on your uploaded sorghum dataset. The math is crop-agnostic; the defaults are crop-aware.

GWAS

Find SNPs significantly associated with any trait you've measured.

Genomic Selection

Predict GEBVs and cross-validate accuracy before deploying in the program.

Population Structure

PCA and ancestry decomposition to control for stratification.

Multi-Environment Trials

GxE heatmap, AMMI, and Finlay–Wilkinson stability for cross-location data.

Selection Index

Rank parents by weighted multi-trait scores.

Gene Annotation

Map top hits to genes via Ensembl Plants.

Environmental Intelligence

Historical weather, GDD, heat-stress days.

Yield Prediction

Whole-genome GBLUP yield predictions on your dataset.

Start analyzing your sorghum data

Upload a CSV, run a real GWAS or genomic-selection model, and get publication-ready output in minutes.

Get started