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Abstract
Hyung Soo Park, Ki Choon Choi, Ji Hye Kim, Min Jeong So, Ki Won Lee and Sang Hoon Lee*National Institute of Animal Science, Cheonan, 330-801, KoreaABSTRACTThe objective of this study was to investigate the feasibility of using near infrared spectroscopy(NIRS) to discriminate between grass spices. A combination of NIRS and chemometrics was used to discriminate between Italian ryegrass, perennial ryegrass, and tall fescue seeds. A total of 240 samples were used to develop the best discriminant equation, whereby three spectra range (visible, NIR, and full range) were applied within a 680nm to 2500nm wavelength. The calibration equation for the discriminant analysis was developed using partial least square(PLS) regression and discrimination equation(DE) analysis. A PLS discriminant analysis model for the three spectra range that was developed with the mathematic pretreatment “1,8,8,1” successfully discriminated between Italian ryegrass, perennial ryegrass, and tall fescue. An external validation indicated that all of the samples were discriminated correctly. The discriminant accuracy was shown as 68%, 78%, and 73% for Italian ryegrass, perennial ryegrass, and tall fescue, respectively, with the NIR full-range spectra. The results demonstrate the usefulness of the NIRS- chemometrics combination as a rapid method for the discrimination of grass species by seed. (Key words :Identification, Pasture seeds, Seed quality, Species discrimination)
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