Measurement of the Color grade and trash

Color Grade

  • Color grade is determined by the degree of reflectance (Rd) and yellowness (+b) as established by official standards and measured by the high volume instrument. Reflectance indicates how bright or dull a sample is, and yellowness indicates the degree of pigmentation. A three-digit color code is determined by locating the point at which the Rd and +b values intersect on the color chart for American Upland cotton.
  • The color of cotton fibers can be affected by rainfall, freezes, insects, fungi, and staining through contact with soil, grass or cotton-plant leaf. Color can also be affected by excessive moisture and temperature levels during storage, both before and after ginning. Color deterioration because of environmental conditions affects the fibers’ ability to absorb and hold dyes and finishes and is likely to reduce processing efficiency.


  • Trash is a measure of the amount of non-lint materials in cotton, such as leaf and bark from the cotton plant.
  • The ratio between percent area of trash and trash particle count is a good indicator of the average particle size in a cotton sample. For instance, a low percent area combined with a high particle count indicates a smaller average particle size than does a high percent area with a low particle count.
  • A high percent area of trash results in greater textile mill processing waste and lower yarn quality. Small trash particles, or “pepper trash”, are highly undesirable, because they are more difficult for the mill to remove from the cotton lint than are larger trash particles.

Measuring principle

The cassette of the FIBERMAP is filled with raw cotton and the sample is pressed on a glass window. A camera scans the surface of the cotton sample and the digital image is analyzed. The color and the reflectance as well as the percentage of the surface area occupied by trash particles (percent area) and the number of trash particles visible (particle count) are calculated and reported.



Fiber Classing

  • Cotton classing
  • Stickiness measurement and grading
  • Automated testing


Data monitoring for fiber and yarn testing

  • Value-added reports
  • Data for quality management
  • Customer specific sample identification