Journal of The Korean Society of Grassland and Forage Science (한국초지조사료학회지)

The Korean Society of Grassland and Forage Science (한국초지조사료학회)
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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
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Abstract

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.

본 연구는 근적외선분광법을 이용한 조사료품질 검사의 현장 이용성을 확대하기 위하여 기존 사일리지 중심의 근적외선 DB에 저 수분 함량의 근적외선 DB를 추가하여 저 수분 조사료의 품질평가 가능성을 검토하고 통합된 동계사료작물 단일의 근적외선 검량식을 개발하기 위하여 전국에서 동계사료작물 조사료 2454점을 수집하였다. 각각의 시료는 근적외선 분광기를 이용하여 스펙트럼을 측정한 후 측정된 스펙트럼과 실험실 분석값간에 상관관계를 이용한 다변량회귀분석법을 통하여 동계사료작물 초종별로 검량식을 유도한 다음 각 성분별로 예측 정확성을 평가하였다. 초종별 동계사료작물의 수분함량 예측에 대한 검량식 작성 결과는 검량식 작성시 표준오차(SEC)와 상호검증표준오차(SECV)는 이탈리안 라이그라스가 각각 1.16%($R^2=0.99$)와 1.27%($R^2=0.99$)로 가장 우수한 예측능력을 보였으며 통합된 동계사료작물은 1.53%($R^2=0.99$)와 1.59%($R^2=0.99$)로 매우 양호한 예측능력을 나타냈다. ADF와 NDF함량 평가를 위해 개발된 검량식의 초종별 상호검증(SECV) 결과는 청보리가 각각 1.47%($R^2=0.75$)와 2.07%($R^2=0.52$)로 가장 낮게 나타났다. 조단백질 함량은 청보리(SECV=0.64%, $R^2=0.61$)를 제외하고는 모든 초종에서 양호한 예측능력을 보였으며 특히 통합된 동계사료작물(SECV=0.61%, $R^2=0.93$)이 가장 높은 예측결과를 나타냈다. 조회분 함량 평가에 대한 검량식 검증결과는 청보리(SECV=0.75%, $R^2=0.61$)와 호밀(SECV=0.81%, $R^2=0.68$)이 다소 낮은 예측 정확성을 나타냈으며 통합된 동계사료작물(SECV=0.45%, $R^2=0.90$)이 가장 높은 예측결과를 나타냈다.

Keywords

References

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