Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy

Autores
Coria, Maria Sumampa; Castaño Ledesma, María Sofía; Gomez Rojas, Jorge Raul; Grigioni, Gabriela Maria; Palma, Gustavo Adolfo; Borsarelli, Claudio Darío
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Objective: This study was conducted to evaluate Raman spectroscopy technique as a noninvasive tool to predict meat quality traits on Braford longissimus thoracis et lumborum muscle. Methods: Thirty samples of muscle from Braford steers were analyzed by classical meat quality techniques and by Raman spectroscopy with 785 nm laser excitation. Water holding capacity (WHC), intramuscular fat content (IMF), cooking loss (CL), and texture profile analysis recording hardness, cohesiveness, and chewiness were determined, along with fiber diameter and sarcomere length by scanning electron microscopy. Warner-Bratzler shear force (WBSF) analysis was used to differentiate tender and tough meat groups. Results: Higher values of cohesiveness and CL, together with lower values of WHC, IMF, and shorter sarcomere were obtained for tender meat samples than for the tougher ones. Raman spectra analysis allows tender and tough sample differentiation. The correlation between the quality attributes predicted by Raman and the physical measurements resulted in values of R2 = 0.69 for hardness and 0,58 for WBSF. Pearson's correlation coefficient of hardness (r = 0.84) and WBSF (r = 0.79) parameters with the phenylalanine Raman signal at 1,003 cm–1, suggests that the content of this amino acid could explain the differences between samples. Conclusion: Raman spectroscopy with 785 nm laser excitation is a suitable and accurate technique to identify beef with different quality attributes.
Fil: Coria, Maria Sumampa. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; Argentina
Fil: Castaño Ledesma, María Sofía. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; Argentina
Fil: Gomez Rojas, Jorge Raul. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; Argentina
Fil: Grigioni, Gabriela Maria. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Agroindustria. Instituto de Tecnología de Alimentos. Instituto de Ciencia y Tecnología de Sistemas Alimentarios Sustentables. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Ciencia y Tecnología de Sistemas Alimentarios Sustentables; Argentina. Universidad de Morón. Facultad de Agronomía y Ciencias Agroalimentarias; Argentina
Fil: Palma, Gustavo Adolfo. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; Argentina
Fil: Borsarelli, Claudio Darío. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; Argentina. Universidad Nacional de Santiago del Estero. Facultad de Agronomía y Agroindustrias. Instituto de Ciencias Químicas; Argentina
Materia
CHEMIOMETRIC ANALYSIS
MEAT QUALITY
RAMAN SPECTROSCOPY
TENDERNESS PREDICTION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/228901
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/228901
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopyCoria, Maria SumampaCastaño Ledesma, María SofíaGomez Rojas, Jorge RaulGrigioni, Gabriela MariaPalma, Gustavo AdolfoBorsarelli, Claudio DaríoCHEMIOMETRIC ANALYSISMEAT QUALITYRAMAN SPECTROSCOPYTENDERNESS PREDICTIONhttps://purl.org/becyt/ford/4.4https://purl.org/becyt/ford/4Objective: This study was conducted to evaluate Raman spectroscopy technique as a noninvasive tool to predict meat quality traits on Braford longissimus thoracis et lumborum muscle. Methods: Thirty samples of muscle from Braford steers were analyzed by classical meat quality techniques and by Raman spectroscopy with 785 nm laser excitation. Water holding capacity (WHC), intramuscular fat content (IMF), cooking loss (CL), and texture profile analysis recording hardness, cohesiveness, and chewiness were determined, along with fiber diameter and sarcomere length by scanning electron microscopy. Warner-Bratzler shear force (WBSF) analysis was used to differentiate tender and tough meat groups. Results: Higher values of cohesiveness and CL, together with lower values of WHC, IMF, and shorter sarcomere were obtained for tender meat samples than for the tougher ones. Raman spectra analysis allows tender and tough sample differentiation. The correlation between the quality attributes predicted by Raman and the physical measurements resulted in values of R2 = 0.69 for hardness and 0,58 for WBSF. Pearson's correlation coefficient of hardness (r = 0.84) and WBSF (r = 0.79) parameters with the phenylalanine Raman signal at 1,003 cm–1, suggests that the content of this amino acid could explain the differences between samples. Conclusion: Raman spectroscopy with 785 nm laser excitation is a suitable and accurate technique to identify beef with different quality attributes.Fil: Coria, Maria Sumampa. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; ArgentinaFil: Castaño Ledesma, María Sofía. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; ArgentinaFil: Gomez Rojas, Jorge Raul. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; ArgentinaFil: Grigioni, Gabriela Maria. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Agroindustria. Instituto de Tecnología de Alimentos. Instituto de Ciencia y Tecnología de Sistemas Alimentarios Sustentables. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Ciencia y Tecnología de Sistemas Alimentarios Sustentables; Argentina. Universidad de Morón. Facultad de Agronomía y Ciencias Agroalimentarias; ArgentinaFil: Palma, Gustavo Adolfo. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; ArgentinaFil: Borsarelli, Claudio Darío. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; Argentina. Universidad Nacional de Santiago del Estero. Facultad de Agronomía y Agroindustrias. Instituto de Ciencias Químicas; ArgentinaAsian-Australasian Association of Animal Production Societies2023-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/228901Coria, Maria Sumampa; Castaño Ledesma, María Sofía; Gomez Rojas, Jorge Raul; Grigioni, Gabriela Maria; Palma, Gustavo Adolfo; et al.; Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy; Asian-Australasian Association of Animal Production Societies; Animal Bioscience; 36; 9; 10-2023; 1435-14442765-01892765-0235CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.animbiosci.org/journal/view.php?doi=10.5713/ab.22.0451info:eu-repo/semantics/altIdentifier/doi/10.5713/ab.22.0451info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:15:44Zoai:ri.conicet.gov.ar:11336/228901instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:15:44.67CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy
title Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy
spellingShingle Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy
Coria, Maria Sumampa
CHEMIOMETRIC ANALYSIS
MEAT QUALITY
RAMAN SPECTROSCOPY
TENDERNESS PREDICTION
title_short Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy
title_full Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy
title_fullStr Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy
title_full_unstemmed Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy
title_sort Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy
dc.creator.none.fl_str_mv Coria, Maria Sumampa
Castaño Ledesma, María Sofía
Gomez Rojas, Jorge Raul
Grigioni, Gabriela Maria
Palma, Gustavo Adolfo
Borsarelli, Claudio Darío
author Coria, Maria Sumampa
author_facet Coria, Maria Sumampa
Castaño Ledesma, María Sofía
Gomez Rojas, Jorge Raul
Grigioni, Gabriela Maria
Palma, Gustavo Adolfo
Borsarelli, Claudio Darío
author_role author
author2 Castaño Ledesma, María Sofía
Gomez Rojas, Jorge Raul
Grigioni, Gabriela Maria
Palma, Gustavo Adolfo
Borsarelli, Claudio Darío
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv CHEMIOMETRIC ANALYSIS
MEAT QUALITY
RAMAN SPECTROSCOPY
TENDERNESS PREDICTION
topic CHEMIOMETRIC ANALYSIS
MEAT QUALITY
RAMAN SPECTROSCOPY
TENDERNESS PREDICTION
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.4
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv Objective: This study was conducted to evaluate Raman spectroscopy technique as a noninvasive tool to predict meat quality traits on Braford longissimus thoracis et lumborum muscle. Methods: Thirty samples of muscle from Braford steers were analyzed by classical meat quality techniques and by Raman spectroscopy with 785 nm laser excitation. Water holding capacity (WHC), intramuscular fat content (IMF), cooking loss (CL), and texture profile analysis recording hardness, cohesiveness, and chewiness were determined, along with fiber diameter and sarcomere length by scanning electron microscopy. Warner-Bratzler shear force (WBSF) analysis was used to differentiate tender and tough meat groups. Results: Higher values of cohesiveness and CL, together with lower values of WHC, IMF, and shorter sarcomere were obtained for tender meat samples than for the tougher ones. Raman spectra analysis allows tender and tough sample differentiation. The correlation between the quality attributes predicted by Raman and the physical measurements resulted in values of R2 = 0.69 for hardness and 0,58 for WBSF. Pearson's correlation coefficient of hardness (r = 0.84) and WBSF (r = 0.79) parameters with the phenylalanine Raman signal at 1,003 cm–1, suggests that the content of this amino acid could explain the differences between samples. Conclusion: Raman spectroscopy with 785 nm laser excitation is a suitable and accurate technique to identify beef with different quality attributes.
Fil: Coria, Maria Sumampa. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; Argentina
Fil: Castaño Ledesma, María Sofía. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; Argentina
Fil: Gomez Rojas, Jorge Raul. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; Argentina
Fil: Grigioni, Gabriela Maria. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Agroindustria. Instituto de Tecnología de Alimentos. Instituto de Ciencia y Tecnología de Sistemas Alimentarios Sustentables. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Ciencia y Tecnología de Sistemas Alimentarios Sustentables; Argentina. Universidad de Morón. Facultad de Agronomía y Ciencias Agroalimentarias; Argentina
Fil: Palma, Gustavo Adolfo. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; Argentina
Fil: Borsarelli, Claudio Darío. Universidad Nacional de Santiago del Estero. Instituto de Bionanotecnología del Noa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Bionanotecnología del Noa; Argentina. Universidad Nacional de Santiago del Estero. Facultad de Agronomía y Agroindustrias. Instituto de Ciencias Químicas; Argentina
description Objective: This study was conducted to evaluate Raman spectroscopy technique as a noninvasive tool to predict meat quality traits on Braford longissimus thoracis et lumborum muscle. Methods: Thirty samples of muscle from Braford steers were analyzed by classical meat quality techniques and by Raman spectroscopy with 785 nm laser excitation. Water holding capacity (WHC), intramuscular fat content (IMF), cooking loss (CL), and texture profile analysis recording hardness, cohesiveness, and chewiness were determined, along with fiber diameter and sarcomere length by scanning electron microscopy. Warner-Bratzler shear force (WBSF) analysis was used to differentiate tender and tough meat groups. Results: Higher values of cohesiveness and CL, together with lower values of WHC, IMF, and shorter sarcomere were obtained for tender meat samples than for the tougher ones. Raman spectra analysis allows tender and tough sample differentiation. The correlation between the quality attributes predicted by Raman and the physical measurements resulted in values of R2 = 0.69 for hardness and 0,58 for WBSF. Pearson's correlation coefficient of hardness (r = 0.84) and WBSF (r = 0.79) parameters with the phenylalanine Raman signal at 1,003 cm–1, suggests that the content of this amino acid could explain the differences between samples. Conclusion: Raman spectroscopy with 785 nm laser excitation is a suitable and accurate technique to identify beef with different quality attributes.
publishDate 2023
dc.date.none.fl_str_mv 2023-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/228901
Coria, Maria Sumampa; Castaño Ledesma, María Sofía; Gomez Rojas, Jorge Raul; Grigioni, Gabriela Maria; Palma, Gustavo Adolfo; et al.; Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy; Asian-Australasian Association of Animal Production Societies; Animal Bioscience; 36; 9; 10-2023; 1435-1444
2765-0189
2765-0235
CONICET Digital
CONICET
url http://hdl.handle.net/11336/228901
identifier_str_mv Coria, Maria Sumampa; Castaño Ledesma, María Sofía; Gomez Rojas, Jorge Raul; Grigioni, Gabriela Maria; Palma, Gustavo Adolfo; et al.; Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy; Asian-Australasian Association of Animal Production Societies; Animal Bioscience; 36; 9; 10-2023; 1435-1444
2765-0189
2765-0235
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.animbiosci.org/journal/view.php?doi=10.5713/ab.22.0451
info:eu-repo/semantics/altIdentifier/doi/10.5713/ab.22.0451
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Asian-Australasian Association of Animal Production Societies
publisher.none.fl_str_mv Asian-Australasian Association of Animal Production Societies
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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