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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
02/02/2022 |
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Actualizado : |
02/02/2022 |
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Autor : |
PRIETO, N.; ROSS, D.W.; NAVAJAS, E.; NUTE, G.R.; RICHARDSON, R.I.; HYSLOP, J.J.; SIMM, G.; ROEHE, R. |
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Afiliación : |
N. PRIETO, Sustainable Livestock Systems Group, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG, UK; D.W. ROSS, Sustainable Livestock Systems Group, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG, UK; ELLY ANA NAVAJAS VALENTINI, Sustainable Livestock Systems Group, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG, UK; G.R. NUTE, University of Bristol, Division of Farm Animal Science, Langford, Bristol BS40 5DU, UK; R.I. RICHARDSON, University of Bristol, Division of Farm Animal Science, Langford, Bristol BS40 5DU, UK; J.J. HYSLOP, Select Services, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG, UK; G. SIMM, Sustainable Livestock Systems Group, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG, UK; R. ROEHE, Sustainable Livestock Systems Group, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG, UK. |
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Título : |
On-line application of visible and near infrared reflectance spectroscopy to predict chemical?physical and sensory characteristics of beef quality. |
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Fecha de publicación : |
2009 |
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Fuente / Imprenta : |
Meat Science, 2009, Volume 83, Issue 1, Pages 96-103. doi: https://doi.org/10.1016/j.meatsci.2009.04.005 |
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ISSN : |
0309-1740 |
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DOI : |
10.1016/j.meatsci.2009.04.005 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 18 January 2009; Received in revised form 30 March 2009; Accepted 3 April 2009. |
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Contenido : |
ABSTRACT.- The aim of this study was to assess the on-line implementation of visible and near infrared reflectance (Vis-NIR) spectroscopy as an early predictor of beef quality traits, by direct application of a fibre-optic probe to the muscle immediately after exposing the meat surface in the abattoir. Samples from M. longissimus
thoracis from 194 heifers and steers were scanned at quartering 48 h postmortem over the Vis-NIR spectral range from 350 to 1800 nm. Thereafter, samples from M. longissimus thoracis et lumborum were analysed for colour (L*, a*, b*; 48 h postmortem), cooking loss (14 days postmortem), instrumental texture (Volodkevitch, 10 days aged meat; slice shear force, 3 and 14 days aged meat) and sensory characteristics. Vis-NIR calibrations, tested by cross-validation, showed high predictability for
L*, a* and b* (R2 = 0.86, 0.86 and 0.91; SECV = 0.96, 0.95 and 0.69, respectively). The accuracy of Vis-NIR to estimate cooking loss and instrumental texture ranged from R2 = 0.31 to 0.54, suggesting relatively low prediction ability. Sensory characteristics assessed on 14 days aged meat samples showed R2 in the range from 0.21 (juiciness) to 0.59 (flavour). Considering the subjective assessment of sensory characteristics the correlations of Vis-NIR measurements and several meat quality traits in the range from 0.46 to 0.95 support the use of on-line Vis-NIR in the abattoir. Improvement of predictability was achieved if only extreme classes of meat characteristics have to be predicted by Vis-NIR spectroscopy.
@ 2009 Elsevier Ltd. All rights reserved. MenosABSTRACT.- The aim of this study was to assess the on-line implementation of visible and near infrared reflectance (Vis-NIR) spectroscopy as an early predictor of beef quality traits, by direct application of a fibre-optic probe to the muscle immediately after exposing the meat surface in the abattoir. Samples from M. longissimus
thoracis from 194 heifers and steers were scanned at quartering 48 h postmortem over the Vis-NIR spectral range from 350 to 1800 nm. Thereafter, samples from M. longissimus thoracis et lumborum were analysed for colour (L*, a*, b*; 48 h postmortem), cooking loss (14 days postmortem), instrumental texture (Volodkevitch, 10 days aged meat; slice shear force, 3 and 14 days aged meat) and sensory characteristics. Vis-NIR calibrations, tested by cross-validation, showed high predictability for
L*, a* and b* (R2 = 0.86, 0.86 and 0.91; SECV = 0.96, 0.95 and 0.69, respectively). The accuracy of Vis-NIR to estimate cooking loss and instrumental texture ranged from R2 = 0.31 to 0.54, suggesting relatively low prediction ability. Sensory characteristics assessed on 14 days aged meat samples showed R2 in the range from 0.21 (juiciness) to 0.59 (flavour). Considering the subjective assessment of sensory characteristics the correlations of Vis-NIR measurements and several meat quality traits in the range from 0.46 to 0.95 support the use of on-line Vis-NIR in the abattoir. Improvement of predictability was achieved if only extreme classes of meat characteristics ... Presentar Todo |
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Palabras claves : |
Beef; Chemical-physical parameters; Meat quality; Near infrared reflectance spectroscopy; Sensory characteristics. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
LEADER 02666naa a2200301 a 4500
001 1062724
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008 2009 bl uuuu u00u1 u #d
022 $a0309-1740
024 7 $a10.1016/j.meatsci.2009.04.005$2DOI
100 1 $aPRIETO, N.
245 $aOn-line application of visible and near infrared reflectance spectroscopy to predict chemical?physical and sensory characteristics of beef quality.$h[electronic resource]
260 $c2009
500 $aArticle history: Received 18 January 2009; Received in revised form 30 March 2009; Accepted 3 April 2009.
520 $aABSTRACT.- The aim of this study was to assess the on-line implementation of visible and near infrared reflectance (Vis-NIR) spectroscopy as an early predictor of beef quality traits, by direct application of a fibre-optic probe to the muscle immediately after exposing the meat surface in the abattoir. Samples from M. longissimus thoracis from 194 heifers and steers were scanned at quartering 48 h postmortem over the Vis-NIR spectral range from 350 to 1800 nm. Thereafter, samples from M. longissimus thoracis et lumborum were analysed for colour (L*, a*, b*; 48 h postmortem), cooking loss (14 days postmortem), instrumental texture (Volodkevitch, 10 days aged meat; slice shear force, 3 and 14 days aged meat) and sensory characteristics. Vis-NIR calibrations, tested by cross-validation, showed high predictability for L*, a* and b* (R2 = 0.86, 0.86 and 0.91; SECV = 0.96, 0.95 and 0.69, respectively). The accuracy of Vis-NIR to estimate cooking loss and instrumental texture ranged from R2 = 0.31 to 0.54, suggesting relatively low prediction ability. Sensory characteristics assessed on 14 days aged meat samples showed R2 in the range from 0.21 (juiciness) to 0.59 (flavour). Considering the subjective assessment of sensory characteristics the correlations of Vis-NIR measurements and several meat quality traits in the range from 0.46 to 0.95 support the use of on-line Vis-NIR in the abattoir. Improvement of predictability was achieved if only extreme classes of meat characteristics have to be predicted by Vis-NIR spectroscopy. @ 2009 Elsevier Ltd. All rights reserved.
653 $aBeef
653 $aChemical-physical parameters
653 $aMeat quality
653 $aNear infrared reflectance spectroscopy
653 $aSensory characteristics
700 1 $aROSS, D.W.
700 1 $aNAVAJAS, E.
700 1 $aNUTE, G.R.
700 1 $aRICHARDSON, R.I.
700 1 $aHYSLOP, J.J.
700 1 $aSIMM, G.
700 1 $aROEHE, R.
773 $tMeat Science, 2009, Volume 83, Issue 1, Pages 96-103. doi: https://doi.org/10.1016/j.meatsci.2009.04.005
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Registro original : |
INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha actual : |
08/09/2017 |
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Actualizado : |
05/07/2019 |
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Tipo de producción científica : |
Capítulo en Libro Técnico-Científico |
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Autor : |
AYALA, W.; SERRON, N.; MACEDO, I.; TERRA, J.A. |
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Afiliación : |
WALTER FELIZARDO AYALA SILVERA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; NESTOR DANIEL SERRON DUPLATT, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IGNACIO MACEDO YAPOR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JOSÉ ALFREDO TERRA FERNÁNDEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
¿Cuánto producen las pasturas en diferentes secuencias de arroz? |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
In: Zorrilla, G.; Martínez, S.; Saravia, H. (Eds.) Arroz 2017. Montevideo (UY): INIA, 2017. |
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Páginas : |
p. 83-85. |
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Serie : |
(INIA Serie Técnica; 233) |
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ISBN : |
978-9974-38-381-4 |
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ISSN : |
1688-9266 |
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DOI : |
http://doi.org/10.35676/INIA/ST.233 |
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Idioma : |
Español |
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Palabras claves : |
SISTEMAS INTEGRADOS; SISTEMAS PASTURAS-CULTIVOS. |
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Thesagro : |
ARROZ; PRODUCCION DE PASTURAS. |
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Asunto categoría : |
F62 Fisiología de la planta - Crecimiento y desarrollo |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/7479/1/ST-233-p.83-85.pdf
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Marc : |
LEADER 00792naa a2200253 a 4500
001 1057538
005 2019-07-05
008 2017 bl uuuu u00u1 u #d
020 $a978-9974-38-381-4
022 $a1688-9266
024 7 $ahttp://doi.org/10.35676/INIA/ST.233$2DOI
100 1 $aAYALA, W.
245 $a¿Cuánto producen las pasturas en diferentes secuencias de arroz?$h[electronic resource]
260 $c2017
300 $ap. 83-85.
490 $a(INIA Serie Técnica; 233)
650 $aARROZ
650 $aPRODUCCION DE PASTURAS
653 $aSISTEMAS INTEGRADOS
653 $aSISTEMAS PASTURAS-CULTIVOS
700 1 $aSERRON, N.
700 1 $aMACEDO, I.
700 1 $aTERRA, J.A.
773 $tIn: Zorrilla, G.; Martínez, S.; Saravia, H. (Eds.) Arroz 2017. Montevideo (UY): INIA, 2017.
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INIA Treinta y Tres (TT) |
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