01965naa a2200253 a 450000100080000000500110000800800410001902400380006010000150009824501280011326000090024150001110025052011100036165000100147165300290148165300180151065300260152865300190155470000180157370000170159170000170160870000180162577300680164310128252019-10-30       2009    bl uuuu     u00u1 u    #d7 a10.1016/j.compag.2009.03.0012DOI1 aFASSIO, A.  aPredicting the nutritive value of high moisture grain corn by near infrared reflectance spectroscopyh[electronic resource]  c2009  aArticle history: Received 23 July 2008 / Received in revised form 23 January 2009 / Accepted 4 March 2009.  aABSTRACT. The aim of this study was to evaluate the potential use of near infrared reflectance (NIR) spectroscopy to predict the nutritive value of high moisture grain corn (HMC). Additionally the use of the jack-knifing as a method to reduce redundant wavelengths was explored when the calibration models were developed. The coefficient of determination in calibration (RCAL2) and the standard error in cross validation (SECV) were (RCAL2 = 0.90, SECV: 2.6%) for dry matter, (RCAL2 = 0.85, SECV: 0.52%) for crude protein, (RCAL2 = 0.90, SECV: 1.8%) for acid detergent fibre, (ADF), (RCAL2 = 0.91, SECV: 2.0%) for in vitro organic matter digestibility (OMD), (RCAL2 = 0.84, SECV: 0.33%) for ash, (RCAL2 = 0.91, SECV: 0.3%) for pH and (RCAL2 = 0.90, SECV: 1.07%) for ammonia nitrogen (N), respectively. The results from this study suggested that dry matter, acid detergent fibre and in vitro organic matter digestibility were accurately predicted using NIR spectroscopy in HMC samples. The use of the jack-knifing method improved the calibration models obtained.  © 2009 Elsevier B.V. All rights reserved.  aMAÍZ  aHigh moisture grain corn  aNear infrared  aPartial least squares  aSilage quality1 aFERNANDEZ, E.1 aRESTAINO, E.1 aLA MANNA, A.1 aCOZZOLINO, D.  tComputers and Electronics in Agriculture, 2009, 67 (1-2): 59-63