Calibration models for the nutritional quality of fresh pastures by near-infrared reflectance spectroscopy

Abstract High levels of animal performance and health depend on high-quality nutrition. Determining forage quality both reliably and quickly is essential for improving animal production. The present study describes the use of near infrared reflectance spectroscopy (NIRS) for the quantification of nu...

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Autores principales:	Lobos,Iris, Moscoso,Cristian J., Pavez,Paula
Lenguaje:	English
Publicado:	Pontificia Universidad Católica de Chile. Facultad de Agronomía e Ingeniería Forestal 2019
Materias:	calibration models external validation forage NIRS nutritive value
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-16202019000300234
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spelling	oai:scielo:S0718-162020190003002342020-01-16Calibration models for the nutritional quality of fresh pastures by near-infrared reflectance spectroscopyLobos,IrisMoscoso,Cristian J.Pavez,Paula calibration models external validation forage NIRS nutritive value Abstract High levels of animal performance and health depend on high-quality nutrition. Determining forage quality both reliably and quickly is essential for improving animal production. The present study describes the use of near infrared reflectance spectroscopy (NIRS) for the quantification of nutritional quality (dry matter (DM), water-soluble carbohydrates (WSC), crude protein (CP), in vitro dry matter digestibility (DMD), organic matter digestibility (OMD), neutral detergent fiber (NDF) and the WSC/CP ratio) in samples from fresh pastures in southern Chile (39° to 40° S). Calibration models were developed with wet chemistry and NIRS spectral data using partial least squares regression (PLSR). The coefficients of determination in the validation set ranged between 0.69 and 0.93, and the error of prediction varied from 0.064 to 2.89. The evaluation of the model confirmed the high predictive ability of NIRS for DM and CP and its low predictive ability for DMD, OMD, NDF and the WSC/CP ratio. It was not possible to obtain a model for WSC because it would have required an increased number of samples to improve the spectral variability and the R2 value (> 80%).info:eu-repo/semantics/openAccessPontificia Universidad Católica de Chile. Facultad de Agronomía e Ingeniería ForestalCiencia e investigación agraria v.46 n.3 20192019-12-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-16202019000300234en10.7764/rcia.v46i3.2020
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	calibration models external validation forage NIRS nutritive value
spellingShingle	calibration models external validation forage NIRS nutritive value Lobos,Iris Moscoso,Cristian J. Pavez,Paula Calibration models for the nutritional quality of fresh pastures by near-infrared reflectance spectroscopy
description	Abstract High levels of animal performance and health depend on high-quality nutrition. Determining forage quality both reliably and quickly is essential for improving animal production. The present study describes the use of near infrared reflectance spectroscopy (NIRS) for the quantification of nutritional quality (dry matter (DM), water-soluble carbohydrates (WSC), crude protein (CP), in vitro dry matter digestibility (DMD), organic matter digestibility (OMD), neutral detergent fiber (NDF) and the WSC/CP ratio) in samples from fresh pastures in southern Chile (39° to 40° S). Calibration models were developed with wet chemistry and NIRS spectral data using partial least squares regression (PLSR). The coefficients of determination in the validation set ranged between 0.69 and 0.93, and the error of prediction varied from 0.064 to 2.89. The evaluation of the model confirmed the high predictive ability of NIRS for DM and CP and its low predictive ability for DMD, OMD, NDF and the WSC/CP ratio. It was not possible to obtain a model for WSC because it would have required an increased number of samples to improve the spectral variability and the R2 value (> 80%).
author	Lobos,Iris Moscoso,Cristian J. Pavez,Paula
author_facet	Lobos,Iris Moscoso,Cristian J. Pavez,Paula
author_sort	Lobos,Iris
title	Calibration models for the nutritional quality of fresh pastures by near-infrared reflectance spectroscopy
title_short	Calibration models for the nutritional quality of fresh pastures by near-infrared reflectance spectroscopy
title_full	Calibration models for the nutritional quality of fresh pastures by near-infrared reflectance spectroscopy
title_fullStr	Calibration models for the nutritional quality of fresh pastures by near-infrared reflectance spectroscopy
title_full_unstemmed	Calibration models for the nutritional quality of fresh pastures by near-infrared reflectance spectroscopy
title_sort	calibration models for the nutritional quality of fresh pastures by near-infrared reflectance spectroscopy
publisher	Pontificia Universidad Católica de Chile. Facultad de Agronomía e Ingeniería Forestal
publishDate	2019
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-16202019000300234
work_keys_str_mv	AT lobosiris calibrationmodelsforthenutritionalqualityoffreshpasturesbynearinfraredreflectancespectroscopy AT moscosocristianj calibrationmodelsforthenutritionalqualityoffreshpasturesbynearinfraredreflectancespectroscopy AT pavezpaula calibrationmodelsforthenutritionalqualityoffreshpasturesbynearinfraredreflectancespectroscopy
_version_	1714202188597690368

Calibration models for the nutritional quality of fresh pastures by near-infrared reflectance spectroscopy

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