Evaluation of Moisture and Feed Values for Winter Annual Forage Crops Using Near Infrared Reflectance Spectroscopy

근적외선분광법을 이용한 동계사료작물 풀 사료의 수분함량 및 사료가치 평가

  • 김지혜 (농촌진흥청 국립축산과학원) ;
  • 이기원 (농촌진흥청 국립축산과학원) ;
  • 오미래 (농촌진흥청 국립축산과학원) ;
  • 최기춘 (농촌진흥청 국립축산과학원) ;
  • 양승학 (농촌진흥청 국립축산과학원) ;
  • 김원호 (농촌진흥청 국립축산과학원) ;
  • 박형수 (농촌진흥청 국립축산과학원)
  • Received : 2019.05.24
  • Accepted : 2019.06.19
  • Published : 2019.06.30


This study was carried out to explore the accuracy of near infrared spectroscopy(NIRS) for the prediction of moisture content and chemical parameters on winter annual forage crops. A population of 2454 winter annual forages representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares(PLS) multivariate analysis in conjunction with spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation($R^2$) and the lowest standard error of cross-validation(SECV). The results of this study showed that NIRS calibration model to predict the moisture contents and chemical parameters had very high degree of accuracy except for barely. The $R^2$ and SECV for integrated winter annual forages calibration were 0.99(SECV 1.59%) for moisture, 0.89(SECV 1.15%) for acid detergent fiber, 0.86(SECV 1.43%) for neutral detergent fiber, 0.93(SECV 0.61%) for crude protein, 0.90(SECV 0.45%) for crude ash, and 0.82(SECV 3.76%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of winter annual forage for routine analysis method to evaluate the feed value.


Near infrared reflectance spectroscopy;Chemical composition;Moisture;Italian ryegrass;Rye;Barely


Grant : 국산 조사료 품질평가 NIRS DB 확장 및 고도화 기술 개발

Supported by : 농촌진흥청


  1. Ahn, H. and Kim, Y. 2012. Discrimination of Korean domestic and foreign soybeans using Near Infrared Reflectance Spectroscopy. Korean Journal of Crop Science/Hanguk Jakmul Hakhoe Chi. 57(3):296-300.
  2. AOAC. 1990. Official Methods of Analysis, 15th ed. Association of Official Analytical Chemists, Washington, DC.
  3. Choe, E.Y., Hong, S.Y., Kim, Y.H., and Zhang, Y.S. 2010. Estimation and mapping of soil organic matter using visible-near infrared spectroscopy. Korean Journal of Soil Science and Fertilizer. 43(6):968-974.
  4. Clark, D.H., Mayland, H.F., and Lamb, R.C. 1987. Mineral Analysis of Forages with near Infrared Reflectance Spectroscopy 1. Agronomy Journal. 79(3):485-490.
  5. Cozzolino, D. and Moron, A. 2004. Exploring the use of near infrared reflectance spectroscopy (NIRS) to predict trace minerals in legumes. Animal Feed Science and Technology, 111(1-4):161-173.
  6. Garcia-Ciudad, A., Garcia-Criado, B., Perez-Corona, M.E., De Aldana, B.R.V., and Ruano-Ramos, A.M. 1993. Application of near-infrared reflectance spectroscopy to chemical analysis of heterogeneous and botanically complex grassland samples. Journal of the Science of Food and Agriculture. 63(4):419-426.
  7. Goering, H.K. and Van Soest, P.J. 1970. Forage Fiber Analysis. Agric. Handb. 379. US Department of Agriculture, Washington, DC.
  8. Holland, C.W., Kezar, W.P. Kautz, E.J. Lazowski, W.C. Mahanna, and Reinhart, R. 1990. The Pioneer Forage Manual-A Nutritional Guide. Pioneer Hi-Bred Int. Inc., Des Moines, IA.
  9. Hruschka, W.R. 1987. Data analysis: wavelength selection methods. In P. Williams and K. Norris (eds.) Near-Infrared Technology in the Agricultural and Food Industries. St. Paul, MN: Am. Assoc. of Cereal Chemists Inc. p. 35-55.
  10. Ki, K.S., Kim, S.B., Lee, H.J., Yang, S.H., Lee, J.S., Jin, Z.L., and Cho, J.K. 2009. Prediction on the quality of total mixed ration for dairy cows by near infrared reflectance spectroscopy. Journal of The Korean Society of Grassland and Forage Science. 29(3):253-262.
  11. Kim, J.S., Song, M.H., Choi, J.E., Lee, H.B., and Ahn, S.N. 2008. Quantification of protein and amylose contents by near infrared reflectance spectroscopy in aroma rice. Korean Journal of Food Science and Technology. 40(6):603-610.
  12. Kim, K., Kang, C., Choi, I., Kim, H., Hyun, J., and Park, C. 2016. Analysis of grain characteristics in Korean wheat and screening wheat for quality using near infrared reflectance spectroscopy. Korean Journal of Breeding Science. 48(4):442-449.
  13. Lee, H.W., Kim, J.D., Kim, W.H., and Lee, J.K. 2009. Prediction on the Quality of Forage Crop by Near Infrared Reflectance Spectroscopy. Journal of The Korean Society of Grassland and Forage Science. 29(1):31-36.
  14. Lee, K.J., Kang, S.W., and Choi, K.H. 2004. Nondestructive quality measurement of fruits and vegetables using near-infrared spectroscopy. Food Engineering Progress.
  15. MAFRA. 2019. Business Enforcement Policy on Government's Support for Forage Production Enlargement. Minister of Agriculture Food and Rural Affairs.
  16. Park, H.S., Lee, S.H., Choi, K.C., Lim, Y.C., Kim, J.G., Jo, K.C., and Choi, G.J. 2012. Evaluation of the quality of Italian ryegrass silages by near infrared spectroscopy. Journal of The Korean Society of Grassland and Forage Science. 32(3):301-308.
  17. Park, H.S., Lee, S.H., Choi, K.C., Lim, Y.C., Kim, J.H., Lee, K.W., and Choi, G.J. 2014. Prediction of the Chemical Composition and Fermentation Parameters of Winter Rye Silages by Near Infrared Spectroscopy. Journal of The Korean Society of Grassland and Forage Science. 34(3):209-213.
  18. Park, H.S., Lee, S.H., Lim, Y.C., Seo, S., Choi, K.C., Kim, J.H., and Choi, G.J. 2013. Prediction of the Chemical Composition of Fresh Whole Crop Barley Silages by Near Infrared Spectroscopy. Journal of The Korean Society of Grassland and Forage Science. 33(3):171-176.
  19. Scientific, U. 2010. Ucal version 1.10 operation manual. Unity Scientific, LLC., Columbus, MD.
  20. Shenk, J.S. and Westerhaus, M.O. 1985. Accuracy of Nirs Instruments to Analyze Forage and Grain 1. Crop science, 25(6):1120-1122.
  21. Shenk, J. S., and Westerhaus, M. O. 1991a. Population definition, sample selection, and calibration procedures for near infrared reflectance spectroscopy. Crop science. 31(2):469-474.
  22. Shenk, J.S. and Westerhaus, M.O. 1991b. Population structuring of near infrared spectra and modified partial least squares regression. Crop Science. 31:1548-1555.
  23. Shin, J.H., Yu, J., Jeong, Y.S., Kim, S., Koh, S.M., and Park, G. 2016. Spectral characteristics of heavy metal contaminated soils in the vicinity of Boksu mine. Journal of the Mineralogical Society of Korea. 29(3):89-101.
  24. Valdes, E.V., R.B. Hunter and Pinter, L. 1987. Determination of quality parameters by near infrared reflectance spectroscopy in whole-plant corn silage. Canadian journal of plant science. 67(3):747-754.
  25. Whetsel, K.B. 1968. Near-infrared spectrophotometry. Applied Spectroscopy Reviews. 2(1):1-67.
  26. Woo, Y.A., Kim, H.J., Cho, J., and Chung, H. 1999. Discrimination of herbal medicines according to geographical origin with near infrared reflectance spectroscopy and pattern recognition techniques. Journal of pharmaceutical and biomedical analysis. 21(2):407-413.