This study was conducted to determine the effect of mathematical transformation on near infrared spectroscopy (NIRS) calibrations for the prediction of chemical composition and fermentation parameters in corn silage. Corn silage samples (n=407) were collected from cattle farms and feed companies in Korea between 2014 and 2015. Samples of silage were scanned at 1 nm intervals over the wavelength range of 680~2,500 nm. The optical data were recorded as log 1/Reflectance (log 1/R) and 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 several spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation (R2 cv) and the lowest standard error of cross validation (SECV). Results of this study revealed that the NIRS method could be used to predict chemical constituents accurately (correlation coefficient of cross validation, R2 cv, ranging from 0.77 to 0.91). The best mathematical treatment for moisture and crude protein (CP) was first-order derivatives (1, 16, 16, and 1, 4, 4), whereas the best mathematical treatment for neutral detergent fiber (NDF) and acid detergent fiber (ADF) was 2, 16, 16. The calibration models for fermentation parameters had lower predictive accuracy than chemical constituents. However, pH and lactic acids were predicted with considerable accuracy (R2 cv 0.74 to 0.77). The best mathematical treatment for them was 1, 8, 8 and 2, 16, 16, respectively. Results of this experiment demonstrate that it is possible to use NIRS method to predict the chemical composition and fermentation quality of fresh corn silages as a routine analysis method for feeding value evaluation to give advice to farmers.

Ⅰ. 서 론
 Ⅱ. 재료 및 방법
  1. 시료 및 NIR 스펙트라 수집
  2. 사료가치 및 발효품질 분석
  3. NIR 검량식 작성
 Ⅲ. 결과 및 고찰
  1. NIR 스펙트라의 특성
  2. 사료용 옥수수 사일리지의 이화학적 특성
  3. 화학적 조성분 및 발효품질 예측 검량식 작성 및검증
  4. 발효품질 예측 검량식 작성 및 검증
 Ⅳ. 요 약
 Ⅴ. 사 사
 Ⅵ. REFERENCES

• 김현섭(국립축산과학원) | Hyeon-Seop Kim
• 최기춘(국립축산과학원) | Ki-Choon Choi
• 김지혜(국립축산과학원) | Ji-Hye Kim Corresponding author
• 박형수(국립축산과학원) | Hyung-Soo Park