Submitted to: Information Processing in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/15/2016
Publication Date: 1/22/2016
Citation: Liu, Y., Delhom, C.D., Campbell, B.T., Martin, V. 2016. Application of near infrared spectroscopy in cotton fiber micronaire measurement. Information Processing in Agriculture. 3: 30-35.
Interpretive Summary: Micronaire is one of important cotton properties as it reflects fiber maturity and fineness. Automation-based high volume instrumentation (HVITM) measurement has been well established as a primary and routine tool of providing fiber micronaire and other quality properties to cotton breeders and fiber processors. This study examined the potential of near-infrared (NIR) spectroscopy for the prediction of cotton micronaire by applying the NIR micronaire model developed from earlier crop year cottons to the newly crop year fibers, and the result indicated the feasibility of NIR model for micronaire assessment of different crop-year cottons. The outcome provides cotton fiber researchers a new sight in applying NIR technique for cotton micronaire screening.
Technical Abstract: The term “micronaire” describes an important cotton fiber property by characterizing the fiber maturity and fineness. In practice, micronaire is regularly measured in laboratories with well established high volume instrumentation (HVITM) protocol. Most often, cotton breeders/geneticists sent cotton breeding line field trial samples to laboratories equipped to use the HVITM systems available for fiber micronaire determination. One alternate way to acquire micronaire values away from standard laboratories or at breeding sites is to utilize near-infrared (NIR) spectroscopy technique. As a proof-of-concept investigation, this study collected both NIR spectra and HVI micronaire from a total of 381 cottons harvested in the 2011 and 2012 crop years. Partial least square (PLS) calibration model relating NIR spectral information to fiber HVI micronaire was developed and then applied to both a validation sample set from identical crop years and an independent test sample set from the 2014 crop year. Results indicated an acceptable bias (or differences between HVI measured and NIR predicted micronaire) and an over 97% of correctly micronaire predictions (within ± 0.3 micronaire unit) in independent test set. Therefore, the development of a robust and effective NIR model for rapid micronaire assessment at remote / breeding locations is feasible.