Vibe Workflows

Rice Chalky Kernel Detection

Food Science & Quality Control

Automated chalky rice kernel detection using imaging-based translucency and color analysis to quantify chalkiness percentage and distribution across the lot.

Problem

Chalkiness reduces milling yield and market value; visual chalky-grain counts are subjective and do not scale to distribution-level analysis across large samples.

Vibe solution

Imaging classification to detect opaque/chalky regions per kernel, quantify chalkiness percentage, and produce severity-scored distributions with traceable exports.

Measured outcomes

Objective chalkiness rates per lot, clearer grade tier assignments, and consistent documentation for milling and export QC.

This workflow is part of Vibe's Rice analysis & imaging workflows. Visit the crop page for the full set of measurements, traits, varieties, and related analysis methods.

More workflows with Vibe

Food Science & Quality Control

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.

Food Science & Quality Control

Brown Basmati Rice Grading

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

Food Science & Quality Control

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.