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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
21/02/2014 |
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Actualizado : |
30/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
A - 1 |
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Autor : |
FASSIO, A.; FERNANDEZ, E.; RESTAINO, E.; LA MANNA, A.; COZZOLINO, D. |
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Afiliación : |
ALBERTO SANTIAGO FASSIO ARAUJO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ENRIQUE GENARO FERNANDEZ RODRIGUEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ERNESTO ANGEL RESTAINO GALUP, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALEJANDRO FRANCISCO LA MANNA ALONSO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DANIEL COZZOLINO GÓMEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Predicting the nutritive value of high moisture grain corn by near infrared reflectance spectroscopy |
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Fecha de publicación : |
2009 |
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Fuente / Imprenta : |
Computers and Electronics in Agriculture, 2009, 67 (1-2): 59-63 |
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DOI : |
10.1016/j.compag.2009.03.001 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 23 July 2008 / Received in revised form 23 January 2009 / Accepted 4 March 2009. |
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Contenido : |
ABSTRACT.
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. |
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Palabras claves : |
High moisture grain corn; Near infrared; Partial least squares; Silage quality. |
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Thesagro : |
MAÍZ. |
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Asunto categoría : |
F01 Cultivo |
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Marc : |
LEADER 01965naa a2200253 a 4500
001 1012825
005 2019-10-30
008 2009 bl uuuu u00u1 u #d
024 7 $a10.1016/j.compag.2009.03.001$2DOI
100 1 $aFASSIO, A.
245 $aPredicting the nutritive value of high moisture grain corn by near infrared reflectance spectroscopy$h[electronic resource]
260 $c2009
500 $aArticle history: Received 23 July 2008 / Received in revised form 23 January 2009 / Accepted 4 March 2009.
520 $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.
650 $aMAÍZ
653 $aHigh moisture grain corn
653 $aNear infrared
653 $aPartial least squares
653 $aSilage quality
700 1 $aFERNANDEZ, E.
700 1 $aRESTAINO, E.
700 1 $aLA MANNA, A.
700 1 $aCOZZOLINO, D.
773 $tComputers and Electronics in Agriculture, 2009, 67 (1-2): 59-63
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