Cotton Quality Prediction on a New, Improved Wavelength

By Jill Lee
January 8, 1997

High volume instrumentation (HVI) is the cotton industry’s standard tool for determining the length, strength and natural color of cotton. Adding another process--called near-infrared spectroscopy--can reveal bulk maturity, a characteristic that’s key to how well the cotton will take dye, a U.S. Department of Agriculture researcher says.

“Near-infrared spectroscopy (NIR) uses light wavelengths that humans can’t see to detect otherwise invisible fiber qualities,” said chemist Joe Montalvo. He’s at the Southern Regional Research Center operated in New Orleans by USDA’s Agricultural Research Service.

The NIR simultaneously measures the fiber’s cell wall thickness and its perimeter, Montalvo said. This data is fed into a computer programmed to calculate the fiber’s dyeability and maturity. The information generated by the computer can help mills determine what products can be made from that particular fiber and how well it will take dye.

"Earlier tries at making NIR a part of HVI left users wanting more speed and greater accuracy,” Montalvo said. “We feel we’ve met and exceeded those demands through extensive scientific fine-tuning.”

Dye imperfections cost the U.S. cotton industry approximately $200 million annually. Since the cotton industry can’t completely prevent poor-dyeing fiber from getting into mills, fabric makers typically discover dyeing imperfections too late and must resign themselves to selling the cloth at a loss.

“NIR-enhanced HVI won’t solve all fiber quality problems outright, but it could be an important prediction tool for mills and growers,” said Montalvo. “That’s why we encourage our colleagues in the cotton research community to look at what we’ve done and see if they agree with our findings.”

In the new HVI model, a mechanical arm pushes a larger cotton sample--about five inches in diameter--against a bigger glass plate where light waves shoot through the fiber. Previously, samples were about the size of a quarter. The bigger sample helps reduce measurement errors. Improvements in the spectrophotometer, the device that produces and measures the light waves, have cut sample reading time from 30 seconds to one second.

Montalvo collaborated with teams of statisticians in government and private industry to develop appropriate mathematical treatments for analyzing NIR data. More than 200 cotton samples were used to develop the equations. In tests, the improved NIR analysis showed less than 2 percent error in its ability to predict maturity.

Scientific contact: Joe Montalvo, Fiber Physics and Biochemistry Research, Southern Regional Research Center, Agricultural Research Service, USDA, New Orleans, La. 70179. Telephone (504) 286-4249; fax (504) 286-4419

U.S. Department of Agriculture
 


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