Rice Classification & Analysis

Overview

Rice workflows cover chalkiness and translucency scoring, whiteness analysis, broken grain detection, and calibrated color metrics - across short, sushi, sweet, wild, jasmine, basmati, paddy, parboiled, and brown varieties. Measurements are based on USDA rice standards, ISO 7301, and Codex Alimentarius rice quality-factor definitions.

Analysis workflows

Mixed Rice Ratio Analysis: Basmati, Brown, Red and Wild

Quantify mix ratios and composition in mixed rice using calibrated imaging, segmentation, morphology, and color index classification.

Paddy Rice Quality Analysis

Non-destructive paddy rice assessment using morphology, defect screening, and calibrated color index to predict milling performance and grain health.

Brown Basmati Rice Grading

Brown basmati QC with per-grain length/width distributions, calibrated color index, and compliance checks for premium long-grain standards.

Milled Long Grain Rice Analysis

Milled long-grain rice analysis for whiteness/color index, chalkiness detection, broken kernels, and defect severity scoring via calibrated imaging.

Parboiled Rice Quality Standards

Parboiled rice QC using calibrated color index and uniformity scoring to detect uneven processing signals batch-by-batch.

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Key measurements

Morphology

Color

Defects

Purity

Distributions

What We Measure

Head rice yield indicators

Chalkiness / translucency

Broken grain detection

Whiteness analysis

Length/width ratio

Color consistency

Size distributions

Short rice classification

Sushi rice classification

Sweet rice classification

Wild rice classification

Jasmine rice classification

Basmati rice classification

Variants

paddy

basmati

milled

parboiled

forbidden

brown

long

medium

short

sushi

sweet

wild

jasmine

Standards and references

USDA Rice Standards ISO 7301 Codex Standard for Rice

Related crop types

Quinoa

Morphology and color metrics for grading and mix analysis.

Measures 5

Traits 3

Variants 3

Workflows 3

Teff

Small-grain imaging for morphology, purity, and agronomical decision support.

Measures 5

Traits 4

Workflows 2

Lentils

Defect detection, grading, red removal, sieving, and color homogeneity analysis for lentil samples.

Measures 5

Traits 6

Variants 5

Workflows 5

Research using Rice

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

Marker-assisted backcrossing introgressed blast-resistance genes (Pigm, Pi-ta) and the aroma gene badh2 into Huruan1212, producing lines with improved panicle blast resistance and fragrance while maintaining high eating and cooking quality.

Investigating the Malting Suitability and Brewing Quality of Different Rice Cultivars

A brewing-focused evaluation of rice cultivars for malting, linking cultivar-dependent differences in wort/beer quality metrics to grain and processing characteristics.

Utilizing X-ray radiography for non-destructive assessment of paddy rice grain quality traits

A proof-of-concept workflow that uses single 2D X-ray radiographs of whole paddy rice grains to non-destructively infer chaffiness, chalky rice kernel percentage (CRK%), and head rice recovery percentage (HRR%).