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 sample.

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Problem

Chalkiness reduces 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 structured exports.

Measured outcomes

Quantified chalkiness rates per sample, clearer classification tiers based on configured criteria, 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.

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