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Evaluation of Feed Values for Whole Crop Rice Using Near Infrared Reflectance Spectroscopy

근적외선분광법을 이용한 사료용 벼의 사료가치 평가

  • 김지혜 (농촌진흥청 국립축산과학원) ;
  • 이기원 (농촌진흥청 국립축산과학원) ;
  • 오미래 (농촌진흥청 국립축산과학원) ;
  • 박형수 (농촌진흥청 국립축산과학원)
  • Received : 2019.12.05
  • Accepted : 2019.12.12
  • Published : 2019.12.31

Abstract

In this study, whole crop rice samples were used to develop near-infrared reflectance (NIR) equations to estimate six forage quality parameters: Moisture, crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), Ash and relative feed value (RFV). A population of 564 whole crop rice representing a wide range in chemical parameters was used in this study. Undried finely chopped whole crop rice samples were scanned at 1 nm intervals over the wavelength range 680-2500 nm and the optical data recorded as log 1/Reflectance (log 1/R). NIRS calibrations were developed by means of partial least-squares (PLS) regression. The correlation coefficients of cross-validation (R2cv) and standard error of cross-validation (SECV) for whole crop rice calibration were 0.98 (SECV 1.81%) for moisture, 0.89 (SECV 0.50%) for CP, 0.86 (SECV 1.79%) for NDF, 0.89 (SECV 0.86%) for ash, and 0.84 (SECV 5.21%) for RFV on a dry matter (%), respectively. The NIRS calibration equations developed in this study will be useful in predicting whole crop rice quality for these six quality parameters.

본 연구는 국내산 사료용 벼를 수집하여 근적외선분광법을 이용한 신속한 품질평가를 위하여 2018년 조사료 품질분석 기관의뢰 된 시료 564점을 수집하여 품질평가 NIR-DB를 구축하고 구축된 DB를 바탕으로 최적의 품질평가 검량식을 개발하고 검증하였다. 각 성분별로 예측 정확성을 평가하기 위해 스펙트라를 측정한 값과 실험실 분석값 간의 상관관계를 이용한 다변량분석법을 이용하였다. 사료용 벼의 수분함량 평가에 대한 예측능력은 각각 SEC 1.66% (R2=0.99)와 SECV 1.81% (R2=0.98)로 나타나 사료가치 평가 성분 중 가장 우수한 예측 능력을 보였으며, CP 함량 각각 SEC 0.42% (R2=0.93)와 SECV 0.50% (R2=0.89)로 나타났다. ADF와 NDF 함량의 예측능력은 각각 SEC 1.25% (R2=0.84), SECV 1.42% (R2=0.79) 및 SEC 1.61% (R2=0.90), SECV 1.79%(R2=0.86)로 나타났다. 사료용 벼의 품질 등급인 RFV의 예측 능력은 SEC 4.67% (R2=0.88), SECV 5.21% (R2=0.84)로 나타났다. 이상의 결과를 종합해보면 근적외선분광법을 이용하여 국내산 사료용 벼의 수분함량과 각종 영양성분을 적은 오차범위에서 분석·평가가 가능하였다.

Keywords

References

  1. Ahn, H. and Kim, Y. 2012. Discrimination of Korean domestic and foreign soybeans using Near Infrared Reflectance Spectroscopy. Korean Journal of Crop Science. 57:296-300. https://doi.org/10.7740/kjcs.2012.57.3.296
  2. AOAC. 2011. Association of official and analytical chemists. Official methods of analysis. 18th.
  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. 43:968-974.
  4. Goering, H.K. and Van Soest, P.J. 1970. Forage Fiber Analysis. Agric. Handb. 379. US Department of Agriculture, Washington, DC.
  5. Holland, C., Kezar, W., Kautz, W.P., E.J. Lazowski, E.J., Mahanna, W.C. and Reinhart, R. 1990. The Pioneer Forage Manual-A Nutritional Guide. Pioneer Hi-Bred Int. Inc., Des Moines, IA.
  6. 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. 29:253-262. https://doi.org/10.5333/KGFS.2009.29.3.253
  7. Kim, J.H., Lee, K.W., Oh, M., Choi, K.C., Yang, S.H., Kim, W.H. and Park, H.S. 2019. Evaluation of moisture and feed values for winter annual forage crops using near infrared reflectance spectroscopy. Journal of The Korean Society of Grassland and Forage Science. 39:114-120. https://doi.org/10.5333/KGFS.2019.39.2.114
  8. 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. 40:603-610.
  9. Kim, K.H, Kang, C.S., Choi, I.D., Kim, H.S, Hyun, J.N. and Park, C.S. 2016. Analysis of grain characteristics in Korean wheat and screening wheat for quality using near infrared reflectance spectroscopy. Korean Journal of Breeding Science. 48:442-449. https://doi.org/10.9787/KJBS.2016.48.4.442
  10. 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.
  11. MAFRA. 2019. Business Enforcement Policy on Government's Support for Forage Production Enlargement. Minister of Agriculture Food and Rural Affairs.
  12. Park, H.S., Kim, J.H., Choi, K.C. and Kim, H.S. 2016. Mathematical transformation influencing accuracy of near infrared spectroscopy (NIRS) calibrations for the prediction of chemical composition and fermentation parameters in corn silage. Journal of the Korean Society of Grassland and Forage Science. 36:50-57. https://doi.org/10.5333/KGFS.2016.36.1.50
  13. 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. 32:301-308. https://doi.org/10.5333/KGFS.2012.32.3.301
  14. 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. 34:209-213. https://doi.org/10.5333/KGFS.2014.34.3.209
  15. 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. 33:171-176. https://doi.org/10.5333/KGFS.2013.33.3.171
  16. Roberts, C.A., Stuth, J. and Finn, P.C. 2003. NIRS applications in forages and feedstuffs. Near Infra-spectroscopy in Agriculture. Agron. Monogr, 321.
  17. Shenk, J.S. and Westerhaus, M.O. 1991. Population definition, sample selection, and calibration procedures for near infrared reflectance spectroscopy. Crop science. 31:469-474. https://doi.org/10.2135/cropsci1991.0011183X003100020049x
  18. Shenk, J.S. and Westerhaus, M.O. 1994. The application of near infrared reflectance spectroscopy (NIRS) to forage analysis. Forage quality, evaluation, and utilization, (foragequalityev). pp. 406-449.
  19. 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. 29:89-101. https://doi.org/10.9727/jmsk.2016.29.3.89
  20. Valdes, E.V., Hunter, R.B. and Pinter, L. 1987. Determination of quality parameters by near infrared reflectance spectroscopy in whole-plant corn silage. Canadian Journal of Plant Science. 67:747-754. https://doi.org/10.4141/cjps87-102
  21. 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. 21:407-413. https://doi.org/10.1016/S0731-7085(99)00145-4