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Effect of Sample Preparation on Prediction of Fermentation Quality of Maize Silages by Near Infrared Reflectance Spectroscopy

Asian-Australasian journal of animal sciences v.18 no.5 , 2005년, pp.643 - 648  
Park, H.S. (National Institute of Subtropical Agriculture, Rural Development Administration ) ;  Lee, J.K. ( Hanwoo Experiment Station, National Livestock Research Institute, RDA ) ;  Fike, J.H. ( Crop and Soil Environmental Science Department, Virginia Tech. ) ;  Kim, D.A. ( School of Agricultural Biotechnology, Seoul National University ) ;  Ko, M.S. ( National Institute of Subtropical Agriculture, Rural Development Administration ) ;  Ha, Jong Kyu ( School of Agricultural Biotechnology, Seoul National University)
Abstract

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid, accurate method of evaluating some chemical constituents in cereal grains and forages. If samples could be analyzed without drying and grinding, then sample preparation time and costs may be reduced. This study was conducted to develop robust NIRS equations to predict fermentation quality of corn (Zea mays) silage and to select acceptable sample preparation methods for prediction of fermentation products in corn silage by NIRS. Prior to analysis, samples (n = 112) were either oven-dried and ground (OD), frozen in liquid nitrogen and ground (LN) and intact fresh (IF). Samples were scanned from 400 to 2,500 nm with an NIRS 6,500 monochromator. The samples were divided into calibration and validation sets. The spectral data were regressed on a range of dry matter (DM), pH and short chain organic acids using modified multivariate partial least squares (MPLS) analysis that used first and second order derivatives. All chemical analyses were conducted with fresh samples. From these treatments, calibration equations were developed successfully for concentrations of all constituents except butyric acid. Prediction accuracy, represented by standard error of prediction (SEP) and $R^2_{v}$ (variance accounted for in validation set), was slightly better with the LN treatment ($R^2$ 0.75-0.90) than for OD ($R^2$ 0.43-0.81) or IF ($R^2$ 0.62-0.79) treatments. Fermentation characteristics could be successfully predicted by NIRS analysis either with dry or fresh silage. Although statistical results for the OD and IF treatments were the lower than those of LN treatment, intact fresh (IF) treatment may be acceptable when processing is costly or when possible component alterations are expected.

주제어

#Near Infrared Reflectance Spectroscopy   #Fermentation Quality   #Corn Silage   #Sample Preparation  

참고문헌 (20)

  1. Daniel Alomar, Rita Fuchslocher and Sergio Stockebrand. 1999. Effects of oven- or freeze-drying on chemical composition and NIR spectra of pasture silage. Anim. Feed Sci. Technol. 80:309-319. 
  2. Windham, W. R., J. A. Robertsons and R. G. Leffler. 1987. A comparison of methods for moisture determination of forages for near infrared reflectance spectroscopy calibration and validation. Crop Sci. 27:777-783. 
  3. Baker, C. W., D. I. Givens and E. R. Deaville. 1994. Prediction of organic matter digestibility in vivo of grass silages by near infrared reflectance spectroscopy: Effect of calibration method, residual moisture and particle size. Anim. Feed Sci. Technol. 50:17-26. 
  4. Kennedy, C. A., J. A. Shelford and P. C. Williams. 1996. Near infrared spectroscopic analysis of intact grass silage and fresh grass for dry matter, crude protein and acid detergent fiber. In (Ed. A. M. C. Davies and P. Williams), Near Infrared Spectroscopy: The Future Waves, Proceedings of the 7th International Conference on Near Infrared Spectroscopy, Montreal, Canada, 6-11 August 1995, NIR Publications, Chichester, UK. pp. 524-530. 
  5. Shenk, J. S. and M. O. Westerhaus. 1995. The application of near infrared reflectance spectroscopy (NIRS) to forage analysis. In (Ed. G. C. Fahey, Jr.) Forage Quality, Evaluation, and Utilization. ASA, Madison. WI. pp. 406-449. 
  6. Adesogan, A. T., E. Owen and D. I. Givens. 1998. Prediction of the in vivo digestibility of whole crop wheat from in vitro digestibility, chemical composition, in situ rumen degradability, in vitro gas production and near infrared reflectance spectroscopy. Anim. Feed Sci. Technol. 74:259-272. 
  7. McDonald, P., A. R. Henderson and S. J. E. Heron. 1991. The biochemistry of silage, second edn. Chalcombe Publications, Marlow. p. 340. 
  8. Gordon, F. J., K. M. Cooper, R. S. Park and R. W. J. Steen. 1998. The prediction of intake potential and organic matter digestibility of grass silages by near infrared spectroscopy analysis of undried samples. Anim. Feed Sci. Technol. 70:339-351. 
  9. Shenk, J. S. 1992. NIRS analysis of natural agricultural products. In (Ed. K. I. Hildrum, T. Isaaksson, T. Naes and A. Tandberg) Near Infrared Spectroscopy. Bridging the Gap between Data Analysis and NIR Applications. London: Ellis Horwood. pp. 235-240. 
  10. Sinnaeve, G., P. Dardenne, R. Agneessens and R. Biston. 1994. The use of near infrared spectroscopy for the analysis of fresh grass silage. J. Near Infrared Spectrosc. 2:79-84. 
  11. Cozzolino, D. A. Fassio and A. Giminez. 2000. The use of nearinfrared reflectance spectroscopy (NIRS) to predict the composition of whole maize plants. J. Sci. Food Agric. 81:142-146. 
  12. De la Roza, B., A. Martinez, S. Modrono and B. Santos. 1996. Determination of the quality of fresh silage by near infrared reflectance spectroscopy. In (Ed. A. M. C. Davies and P. Williams), Near Infrared Spectroscopy: The Future Waves, Proceedings of the 7th International Conference on Near Infrared Spectroscopy, Montreal, Canada, 6-11 August 1995, NIR Publications, Chichester, UK. pp. 537-541. 
  13. Park, R. S., R. E. Agnew and D. J. Kilpatrick. 2002. The effect of freezing and thawing on grass silage quality predictions based on near infrared reflectance spectroscopy. Anim. Feed Sci. Technol. 101:151-167. 
  14. Park, R. S., F. J. Gordon, R. E. Agnew and R. W. J. Steen. 1998. The use of near infrared reflectance spectroscopy (NIRS) on undried samples of grass silage to predict chemical composition and digestibility parameters. Anim. Feed Sci. Technol. 72:155-167. 
  15. Shenk, J. S. and M. O. Westerhaus. 1991. Population definition, sample selection, and calibration procedures for near infrared reflectance spectroscopy. Crop Sci. 31:469-474. 
  16. Williams, P. C. 1987. Variables affecting near-infrared reflectance spectroscopic analysis. In (Ed. P. Williams and K. Norris) Near-Infrared Technology in the Agricultural and Food Industries. St. Paul, MN: American Association of Cereal Chemists Inc. pp. 143-167. 
  17. Givens, D. I., J. L. De Boever and E. R. Deaville. 1997. The principles, practices and some future applications of near infrared spectroscopy for predicting the nutritive value of foods for animals and humans. Nutrition Research Reviews. 10:83-114. 
  18. Watson, C. A., G. Etchevers and W. C. Shuey. 1976. Relationship between ash and protein contents of flourmill streams determined with the InfraAnalyzer and standard approved methods. Cereal Chem. 53:803-804. 
  19. Reeves, J. B., III, T. H. Blosser and V. F. Colenbrander. 1989. Near infrared reflectance spectroscopy for analyzing undried silage. J. Dairy Sci. 72:79-88. 
  20. Windham, W. R. 1987. Influence of grind and gravimetric technique on dry matter determination of forages intended for analysis by near infrared reflectance spectroscopy. Crop Sci. 27:773-776. 

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