Carne oscura, firme y seca (DFD). Causas, implicaciones y métodos de determinación

Objetivo. Revisar las causas, consecuencias y métodos de determinación de la carne DFD con el fin de contribuir al conocimiento de esta anomalía para encontrar alternativas que contrarresten su presencia. Desarrollo. La carne DFD se presenta cuando las reservas de glucógeno muscular no son suficient...

Full description

Autores:: Hernández-Hernández, Leonardo
Barragán-Hernández, Wilson Andrés
Angulo-Arizala, Joaquín
Mahecha-Ledesma, Liliana

Tipo de recurso:: Article of journal

Fecha de publicación:: 2023

Institución:: Universidad de Sucre

Repositorio:: Repositorio Unisucre

Idioma:: spa

id	RUNISUCRE2_697b361a10e82bce80fcdac456a92773
oai_identifier_str	oai:repositorio.unisucre.edu.co:001/1722
network_acronym_str	RUNISUCRE2
network_name_str	Repositorio Unisucre
repository_id_str
dc.title.spa.fl_str_mv	Carne oscura, firme y seca (DFD). Causas, implicaciones y métodos de determinación
dc.title.translated.eng.fl_str_mv	Dark-cutting meat. Causes, implications, and methods of determination
title	Carne oscura, firme y seca (DFD). Causas, implicaciones y métodos de determinación
spellingShingle	Carne oscura, firme y seca (DFD). Causas, implicaciones y métodos de determinación Beef quality Carcass Organoleptic properties Colorimetry Slaughter Consumers Calidad de la carne Canal animal Propiedades organolépticas colorimetría Sacrificio Consumidores
title_short	Carne oscura, firme y seca (DFD). Causas, implicaciones y métodos de determinación
title_full	Carne oscura, firme y seca (DFD). Causas, implicaciones y métodos de determinación
title_fullStr	Carne oscura, firme y seca (DFD). Causas, implicaciones y métodos de determinación
title_full_unstemmed	Carne oscura, firme y seca (DFD). Causas, implicaciones y métodos de determinación
title_sort	Carne oscura, firme y seca (DFD). Causas, implicaciones y métodos de determinación
dc.creator.fl_str_mv	Hernández-Hernández, Leonardo Barragán-Hernández, Wilson Andrés Angulo-Arizala, Joaquín Mahecha-Ledesma, Liliana
dc.contributor.author.spa.fl_str_mv	Hernández-Hernández, Leonardo Barragán-Hernández, Wilson Andrés Angulo-Arizala, Joaquín Mahecha-Ledesma, Liliana
dc.subject.eng.fl_str_mv	Beef quality Carcass Organoleptic properties Colorimetry Slaughter Consumers
topic	Beef quality Carcass Organoleptic properties Colorimetry Slaughter Consumers Calidad de la carne Canal animal Propiedades organolépticas colorimetría Sacrificio Consumidores
dc.subject.spa.fl_str_mv	Calidad de la carne Canal animal Propiedades organolépticas colorimetría Sacrificio Consumidores
description	Objetivo. Revisar las causas, consecuencias y métodos de determinación de la carne DFD con el fin de contribuir al conocimiento de esta anomalía para encontrar alternativas que contrarresten su presencia. Desarrollo. La carne DFD se presenta cuando las reservas de glucógeno muscular no son suficientes para que el pH descienda a su punto óptimo 24 h después del beneficio. Se estudian diversos factores ambientales e inherentes al animal que pueden estar interrelacionados y que serían los responsables de estrés y consecuente aparición de carne DFD. Así mismo, se revisan los diferentes métodos con los cuales se puede determinar esta condición. Consideraciones finales. El manejo de los animales pre- y pos-beneficio es determinante en la aparición de carnes DFD. Conocer los factores que influyen sobre su presencia y los métodos disponibles para su determinación puede contribuir con la disminución de esta anomalía y mejorar la calidad de las canales.
publishDate	2023
dc.date.accessioned.none.fl_str_mv	2023-06-29 05:46:57 2023-07-06T09:30:41Z
dc.date.available.none.fl_str_mv	2023-06-29 05:46:57 2023-07-06T09:30:41Z
dc.date.issued.none.fl_str_mv	2023-06-29
dc.type.spa.fl_str_mv	Artículo de revista
dc.type.coar.fl_str_mv	http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/article
dc.type.local.eng.fl_str_mv	Journal article
dc.type.version.spa.fl_str_mv	info:eu-repo/semantics/publishedVersion
dc.type.coar.spa.fl_str_mv	http://purl.org/coar/resource_type/c_6501 http://purl.org/coar/resource_type/c_dcae04bc
dc.type.content.spa.fl_str_mv	Text
dc.type.redcol.spa.fl_str_mv	http://purl.org/redcol/resource_type/ARTREV
dc.type.coarversion.spa.fl_str_mv	http://purl.org/coar/version/c_970fb48d4fbd8a85
format	http://purl.org/coar/resource_type/c_6501
status_str	publishedVersion
dc.identifier.uri.none.fl_str_mv	https://repositorio.unisucre.edu.co/handle/001/1722
dc.identifier.doi.none.fl_str_mv	10.24188/recia.v15.n1.2023.938
dc.identifier.eissn.none.fl_str_mv	2027-4297
dc.identifier.url.none.fl_str_mv	https://doi.org/10.24188/recia.v15.n1.2023.938
url	https://repositorio.unisucre.edu.co/handle/001/1722 https://doi.org/10.24188/recia.v15.n1.2023.938
identifier_str_mv	10.24188/recia.v15.n1.2023.938 2027-4297
dc.language.iso.spa.fl_str_mv	spa
language	spa
dc.relation.references.spa.fl_str_mv	Klurfeld DM. Research gaps in evaluating the relationship of meat and health. Meat Sci. 2015; 109:86–95. http://dx.doi.org/10.1016/j.meatsci.2015.05.022 Kamruzzaman M, Makino Y, Oshita S. Non-invasive analytical technology for the detection of contamination, adulteration, and authenticity of meat, poultry, and fish: A review. Anal Chim Acta. 2015; 853(1):19–29. http://dx.doi.org/10.1016/j.aca.2014.08.043 García G, Zambrano W, Martínez G, Zambrano J. Alteraciones del pH y temperatura en la canal a causa de factores relacionados al transporte bovino previo al sacrificio. Rev Las Agrociencias. 2021; 26(Ed Esp)95–109. https://doi.org/10.33936/la_tecnica.v0i0.2524 Ponnampalam EN, Hopkins DL, Bruce H, Li D, Baldi G, Bekhit AE din. Causes and Contributing Factors to “Dark Cutting” Meat: Current Trends and Future Directions: A Review. Compr Rev Food Sci Food Saf. 2017; 16(3):400–430. https://doi.org/10.1111/1541-4337.12258 de Sousa Ribeiro CC, Contreras-Castillo CJ, Santos-Donado PR Dos, Venturini AC. New alternatives for improving and assessing the color of dark–cutting beef – a review. Sci Agric. 2022; 79(1):1–16. https://doi.org/10.1590/1678-992X-2020-0079 Prieto N, López-Campos O, Zijlstra RT, Uttaro B, Aalhus JL. Discrimination of beef dark cutters using visible and near infrared reflectance spectroscopy. Can J Anim Sci. 2014; 94(3):445–454. https://doi.org/10.4141/cjas-2014-024 Roberts JJ, Cozzolino D. An Overview on the Application of Chemometrics in Food Science and Technology—An Approach to Quantitative Data Analysis. Food Anal Methods. 2016; 9(12):3258–3267. http://dx.doi.org/10.1007/s12161-016-0574-7 Paredi G, Raboni S, Bendixen E, de Almeida AM, Mozzarelli A. “Muscle to meat” molecular events and technological transformations: The proteomics insight. J Proteomics. 2012; 75(14):4275–4289. http://dx.doi.org/10.1016/j.jprot.2012.04.011 Barragán-Hernández WA, Mahecha-Ledesma L, Olivera-Angel M, Angulo-Arizala J. Compositional and sensory quality of beef and its determination by near infrared. Agron Mesoamerican. 2021; 32(3):1000–1018. https://doi.org/10.15517/am.v32i3.40607 Aboah J, Lees N. Consumers use of quality cues for meat purchase: Research trends and future pathways. Meat Sci. 2020; 166:108142. https://doi.org/10.1016/j.meatsci.2020.108142 Purslow PP, Warner RD, Clarke FM, Hughes JM. Variations in meat colour due to factors other than myoglobin chemistry; a synthesis of recent findings (invited review). Meat Sci 2020; 159:107941. https://doi.org/10.1016/j.meatsci.2019.107941 Prill LL, Drey LN, Olson BA, Rice EA, Gonzalez JM, Vipham JL, et al. Visual Degree of Doneness Impacts Beef Palatability for Consumers with Different Degree of Doneness Preferences. Meat Muscle Biol. 2019; 3(1):411-423. https://doi.org/10.22175/mmb2019.07.0024 Gunders D. Wasted: How America is losing up to 40 percent of its food from farm to fork to landfill. NRDC Issue Pap; 2012. https://www.nrdc.org/sites/default/files/wasted-food-IP.pdf Franco D, Mato A, Salgado FJ, López-Pedrouso M, Carrera M, Bravo S, et al. Tackling proteome changes in the longissimus thoracis bovine muscle in response to pre-slaughter stress. J Proteomics. 2015; 122:73–85. http://dx.doi.org/10.1016/j.jprot.2015.03.029 Beef Cattle Research Council. The 2010/11 National Beef Quality Audit: Canadá; 2010. https://www.beefresearch.ca/files/pdf/fact-sheets/nbqa_full_brochure_feb_2013.pdf Beef Cattle Research Council. National Beef Quality Audit, 2010/11 Beef Carcass Audit Fact Sheet: Canadá; 2011. https://www.beefresearch.ca/files/pdf/fact-sheets/1181_CCA_NBQA_Factsheet_June_15_F.pdf Mcgilchrist P, Perovic JL, Gardner GE, Pethick DW, Jose CG. The incidence of dark cutting in southern Australian beef production systems fluctuates between months. Anim Prod Sci. 2014; 54(10):1765–1769. https://doi.org/10.1071/AN14356 Riggs PK, Therrien DA, Vaughn RN, Rotenberry ML, Davis BW, Herring AD, et al. Differential Expression of MicroRNAs in Dark-Cutting Meat from Beef Carcasses. Appl. Sci. 2022; 12(7):3555. https://doi.org/10.3390/app12073555 Fuente-Garcia C, Aldai N, Sentandreu E, Oliván M, Franco D, García-Torres S, Sentandreu M. Assessment of caspase activity in post mortem muscle as a way to explain characteristics of DFD beef. J. Food Compos. Anal. 2022; 111:104599. https://doi.org/10.1016/j.jfca.2022.104599 Holdstock J, Aalhus JL, Uttaro BA, López-Campos Ó, Larsen IL, Bruce HL. The impact of ultimate pH on muscle characteristics and sensory attributes of the longissimus thoracis within the dark cutting (Canada B4) beef carcass grade. Meat Sci. 2014; 98(4):842–849. https://doi.org/10.1016/j.meatsci.2014.07.029 Leyva-García IA, Figueroa-Saavedra F, Sánchez-López E, Pérez-Linares C, Barreras-Serrano A. Impacto económico de la presencia de carne DFD en una planta de sacrificio Tipo Inspección Federal ( TIF ). Arch Med Vet. 2012; 44(1):39–42. Loudon KMW, Lean IJ, Pethick DW, Gardner GE, Grubb LJ, Evans AC, et al. On farm factors increasing dark cutting in pasture fi nished beef cattle. Meat Sci. 2018; 144:110–117. https://doi.org/10.1016/j.meatsci.2018.06.011 Rosa A, Fonseca R, Balieiro JC, Poleti MD, Domenech-Pérez K, Farnetani B, et al. Incidence of DFD meat on Brazilian beef cuts. Meat Sci. 2016; 112:132–133. https://doi.org/10.1016/j.meatsci.2015.08.074 Patiño RM, Botero LM, Bohóquez W, Therán TM. Bienestar de Bovinos durante la fase de faenado en una planta de benefi cio de la región Caribe de Colombia. ACCB. 2019; 1(31):24–35. https://revistaaccb.org/r/index.php/accb/article/view/178 Ramanathan R, Lambert LH, Nair MN, Morgan B, Feuz R, Mafi G. Economic Loss, Amount of Beef Discarded, Natural Resources Wastage, and Environmental Impact Due to Beef Discoloration. Meat Muscle Biol. 2022; 6(1):13218. https://doi.org/10.22175/mmb.13218 Ramanathan R, Hunt MC, Mancini RA, Nair MN, Denzer ML, Suman SP, et al. Recent Updates in Meat Color Research: Integrating Traditional and High-Throughput Approaches. Meat Muscle Biol. 2020; 4(2):1-24. https://doi.org/10.22175/mmb.9598 Claudia Terlouw EM, Picard B, Deiss V, Berri C, Hocquette JF, Lebret B, et al. Understanding the determination of meat quality using biochemical characteristics of the muscle: Stress at slaughter and other missing keys. Foods. 2021; 10(1):1-24. https://doi.org/10.3390/foods10010084 Fraeye I, Kratka M, Vandenburgh H, Thorrez L. Sensorial and Nutritional Aspects of Cultured Meat in Comparison to Traditional Meat: Much to Be Inferred. Front Nutr. 2020; 7(35):1-7. https://doi.org/10.3389/fnut.2020.00035 Sierra V, Olivan M. Role of Mitochondria on Muscle Cell Death and Meat Tenderization. Recent Pat Endocr Metab Immune Drug Discov. 2013; 7(2):120–129. https://dx.doi.org/10.2174/1872214811307020005 Lana A, Zolla L. Proteolysis in meat tenderization from the point of view of each single protein: A proteomic perspective. J Proteomics. 2016; 147:85–97. http://dx.doi.org/10.1016/j.jprot.2016.02.011 England EM, Matarneh SK, Oliver EM, Apaoblaza A, Scheffler TL, Shi H, et al. Excess glycogen does not resolve high ultimate pH of oxidative muscle. Meat Sci. 2016; 114:95–102. https://doi.org/10.1016/j.meatsci.2015.10.010 McKeith RO, King DA, Grayson AL, Shackelford SD, Gehring KB, Savell JW, et al. Mitochondrial abundance and efficiency contribute to lean color of dark cutting beef. Meat Sci. 2016; 116:165–173. https://doi.org/10.1016/j.meatsci.2016.01.016 England EM, Matarneh SK, Scheffler TL, Wachet C, Gerrard DE. pH inactivation of phosphofructokinase arrests postmortem glycolysis. Meat Sci. 2014; 98(4):850–857. https://doi.org/10.1016/j.meatsci.2014.07.019 Zhang M, Dunshea FR, Warner RD, Digiacomo K, Chauhan SS, Warner RD. Impacts of heat stress on meat quality and strategies for amelioration : a review. Int J Biometeorol. 2020; 64:1613–1628. https://doi.org/10.1007/s00484-020-01929-6 AMSA. Research Guidelines for Cookery, Sensory Evaluation, and Instrumental Tenderness Measurements of Meat. American Meat Science Association Educational Foundation. 2015. https://meatscience.org/docs/default-source/publications-resources/amsa-sensory-and-tenderness-evaluation-guidelines/research-guide/2015-amsa-sensory-guidelines-1-0.pdf?sfvrsn=6 Ramanathan R, Suman SP, Faustman C. Biomolecular Interactions in Postmortem Skeletal Muscles Governing Fresh Meat Color : A Review. J. Agric. Food Chem. 2020; 68(46):12779-12787. https://doi.org/10.1021/acs.jafc.9b08098 Contreras-Castillo CJ, Lomiwes D, Wu G, Frost D, Farouk MM. The effect of electrical stimulation on post mortem myofibrillar protein degradation and small heat shock protein kinetics in bull beef. Meat Sci. 2016; 113:65–72. https://doi.org/10.1016/j.meatsci.2015.11.012 Wang LL, Yu QL, Han L, Ma XL, Song R De, Zhao SN, et al. Study on the effect of reactive oxygen species-mediated oxidative stress on the activation of mitochondrial apoptosis and the tenderness of yak meat. Food Chem. 2018; 244:394–402. http://dx.doi.org/10.1016/j.foodchem.2017.10.034 Joo ST, Kim GD, Hwang YH, Ryu YC. Control of fresh meat quality through manipulation of muscle fiber characteristics. Meat Sci. 2013; 95(4):828–836. https://doi.org/10.1016/j.meatsci.2013.04.044 Mouzo D, Rodríguez-vázquez R, Lorenzo JM, Franco D, Zapata C, López-pedrouso M. Proteomic application in predicting food quality relating to animal welfare . A review. Trends Food Sci Technol. 2020; 99:520–530. https://doi.org/10.1016/j.tifs.2020.03.029 Loredo-Osti J, Sánchez-López E, Barreras-Serrano A, Figueroa-Saavedra F, Pérez-Linares C, Ruiz-Albarrán M, et al. An evaluation of environmental, intrinsic and pre- and post-slaughter risk factors associated to dark-cutting beef in a Federal Inspected Type slaughter plant. Meat Sci. 2019; 150:85–92. https://doi.org/10.1016/j.meatsci.2018.12.007 Silva LHP, Assis DEF, Estrada MM, Assis GJF, Zamudio GDR, Carneiro GB, et al. Carcass and meat quality traits of Nellore young bulls and steers throughout fattening. Livest Sci. 2019; 229:28–36. https://doi.org/10.1016/j.livsci.2019.09.012 Mahmood S, Basarab JA, Dixon WT, Bruce HL. Relationship between phenotype, carcass characteristics and the incidence of dark cutting in heifers. Meat Sci. 2016; 121:261–271. https://doi.org/10.1016/j.meatsci.2016.06.020 King DA, Shackelford SD, Kuehn LA, Kemp CM, Rodriguez AB, Thallman RM, et al. Contribution of genetic influences to animal-to-animal variation in myoglobin content and beef lean color stability. J Anim Sci. 2010; 88(3):1160–1167. https://doi.org/10.2527/jas.2009-2544. Kawecki K, Stangierski J, Niedźwiedź J, Grześ B. The impact of environmental factors on the occurrence of DFD-type of beef in commercial abattoirs. Emirates J Food Agric. 2020; 32(7):533–542. https://doi.org/10.9755/ejfa.2020.v32.i7.2125 Marenčić D, Ivanković A, Kozačinski L, Popović M. The effect of sex and age at slaughter on the physicochemical properties of baby-beef meat. Vet Arh. 2018; 88(1):101–110. https://doi.org/10.24099/vet.arhiv.160720 Jacinto-valderrama RA, Sicca G, Sampaio L, Lucia M, Lima P, Noely J. Immunocastration on performance and meat quality of Bos indicus (Nellore) cattle under different nutritional systems. Sci. agric. 2021; 78(2):e20190136. http://dx.doi.org/10.1590/1678-992X-2019-0136 Gardner GE, Hopkins DL, Greenwood PL, Cake MA, Boyce MD, Pethick DW. Sheep genotype, age and muscle type affect the expression of metabolic enzyme markers. Aust J Exp Agric. 2007; 47(10):1180–1189. https://doi.org/10.1071/EA07093 Greenwood PL, Harden S, Hopkins DL. Myofibre characteristics of ovine longissimus and semitendinosus muscles are influenced by sire breed, gender, rearing type, age and carcass weight. Aust J Exp Agric. 2007; 47(10):1137–1146. https://doi.org/10.1071/EA06324 Pérez Linares, Serrano, F. Figueroa Saavedra AB. Management Factores de manejo asociados a carne DFD en bovinos en climadesertico. Arch Zootec 2008; 57(220):545–547. Steel C, Lees AM, Tarr G, Warner R, Dunshea F, Cowley F, et al. The impact of weather on the incidence of dark cutting in Australian feedlot cattle. Int J Biometeorol. 2022; 66(2):263–274. https://doi.org/10.1007/s00484-021-02180-3 Munilla ME, Vittone JS, Lado M, Romera SA, Teira GA. Efecto de las prácticas durante el manejo pre-faena sobre el rendimiento de la carne de bovinos. Rev Vet. 2021; 32(1):48. http://dx.doi.org/10.30972/vet.3215633 Diro M, Mekete B, Gebremedhin EZ. Effect of pre-slaughter beef cattle handling on welfare and beef quality in Ambo and Guder markets and abattoirs, Oromia Regional State, Ethiopia. Ethiop J Sci Technol. 2021; 14(2):89–104. https://doi.org/10.4314/ejst.v14i2.1 Osti JL, Serrano AB, Saavedra FF, Linares CP, Ruiz-Albarrán M. Evaluación de los componentes del manejo antes, durante y después de la matanza y su asociación con la presencia de carne DFD en bovinos del noreste de México. Rev. Mex. Cienc. Pecu. 2021; 12(3):773-788. https://doi.org/10.22319/rmcp.v12i3.4866 Herrán L, Romero M, Herrán L. Interacción humano-animal y prácticas de manejo bovino en subastas colombianas. Rev Investig Vet del Peru. 2017; 28(3):571–585. https://doi.org/10.15381/rivep.v28i3.13360 Lawrie RA, Ledward DA. Lawrie’s meat science. 7th ed. Cambridge: CRC Press; 2006 Cordoba, C. Correa, G. Barahona, R. Tarazona A. Comportamiento de machos cebú en corrales presacrificio y su relación con el pH de la carne. Arch. Zootec. 66(256):579-586. Pérez-linares C, Barrera A, Sánchez E, Bárbara S, Figueroa-Saavedra F. Efecto del cambio en el manejo antemortem sobre la presencia de carne DFD en ganado bovino. Rev MVZ Cordoba. 2015; 20(3):4688-4697. https://doi.org/10.21897/rmvz.39 Arik E, Karaca S. The effect of some pre-slaughter factors on meat quality of bulls slaughtered in a commercial abattoir in Turkey. Indian J Anim Res. 2017; 51(3):557–63. Cobo GC, Romero HM. Importancia de la interacción hombre-animal durante el presacrificio bovino: Revisión. Biosalud. 2012; 11(2):79–91. Carrasco-García AA, Pardío-Sedas VT, León-Banda GG, Ahuja-Aguirre C, Paredes-Ramos P, Hernández-Cruz BC, et al. Effect of stress during slaughter on carcass characteristics and meat quality in tropical beef cattle. Asian-Australasian J Anim Sci. 2020; 33(10):1656–1665. https://doi.org/10.5713/ajas.19.0804 Clinquart A, Ellies-Oury MP, Hocquette JF, Guillier L, Santé-Lhoutellier V, Prache S. Review: On-farm and processing factors affecting bovine carcass and meat quality. Animal. 2022; 16:100426. https://doi.org/10.1016/j.animal.2021.100426 Kim YHB, Ma D, Setyabrata D, Farouk MM, Lonergan SM, Huff-Lonergan E, et al. Understanding postmortem biochemical processes and post-harvest aging factors to develop novel smart-aging strategies. Meat Sci. 2018; 144:74–90. https://doi.org/10.1016/j.meatsci.2018.04.031 McGilchrist P, Alston CL, Gardner GE, Thomson KL, Pethick DW. Beef carcasses with larger eye muscle areas, lower ossification scores and improved nutrition have a lower incidence of dark cutting. Meat Sci. 2012; 92(4):474–480. https://doi.org/10.1016/j.meatsci.2012.05.014 Young OA, West J, Hart AL, Van Otterdijk FFH. A method for early determination of meat ultimate pH. Meat Sci. 2004; 66(2):493–498. https://doi.org/10.1016/S0309-1740(03)00140-2 Kademi HI, Ulusoy BH, Hecer C. Applications of miniaturized and portable near infrared spectroscopy (NIRS) for inspection and control of meat and meat products. Food Rev Int. 2019; 35(3):201–220. https://doi.org/10.1080/87559129.2018.1514624 Mancini RA, Hunt MC. Current research in meat color. Meat Sci. 2005; 71(1):100-121. https://doi.org/10.1016/j.meatsci.2005.03.003 Li S, Zamaratskaia G, Roos S, Båth K, Meijer J, Borch E, et al. Inter-relationships between the metrics of instrumental meat color and microbial growth during aerobic storage of beef at 4°C. Acta Agric Scand A Anim Sci. 2015; 65(2):97–106. Hodgen J. Comparison of nix color sensor and nix color sensor pro to standard meat science research colorimeters. Meat Sci. 2016; 112:159. https://doi.org/10.1016/j.meatsci.2015.08.129 Holman BWB, Collins D, Kilgannon AK, Hopkins DL. The e ff ect of technical replicate (repeats) on Nix Pro Color Sensor TM measurement precision for meat : A case-study on aged beef colour stability. Meat Sci. 2018; 135:42–45. https://doi.org/10.1016/j.meatsci.2017.09.001 Holman BWB, Hopkins DL. A comparison of the Nix Colour Sensor ProTM and HunterLab MiniScanTM colorimetric instruments when assessing aged beef colour stability over 72 h display. Meat Sci. 2019; 147:162–165. https://doi.org/10.1016/j.meatsci.2018.09.009 Prieto N, Pawluczyk O, Dugan MER, Aalhus JL. A Review of the Principles and Applications of Near-Infrared Spectroscopy to Characterize Meat, Fat, and Meat Products. Appl Spectrosc. 2017; 71(7):1403–1426. https://doi.org/10.1177/0003702817709299 Farmer LJ, Farrell DT. Review: Beef-eating quality: A European journey. Animal. 2018; 12(11):2424–2433. https://doi.org/10.1017/S1751731118001672 Ma J, Sun D, Pu H, Cheng J, Wei Q. Advanced Techniques for Hyperspectral Imaging in the Food Industry: Principles and Recent Applications. Annu Rev Food Sci Technol. 2019; 10:197–220. https://doi.org/10.1146/annurev-food-032818-121155 Tomasevic I, Tomovic V, Milovanovic B, Lorenzo J, Đorđević V, Karabasil N, et al. Comparison of a computer vision system vs. traditional colorimeter for color evaluation of meat products with various physical properties. Meat Sci. 2019; 148:5–12. https://doi.org/10.1016/j.meatsci.2018.09.015
dc.relation.bitstream.none.fl_str_mv	https://revistas.unisucre.edu.co/index.php/recia/article/download/938/1070 https://revistas.unisucre.edu.co/index.php/recia/article/download/938/1071 https://revistas.unisucre.edu.co/index.php/recia/article/download/938/1072
dc.relation.citationedition.spa.fl_str_mv	Núm. 1 , Año 2023 : RECIA 15(1):ENERO-JUNIO 2023
dc.relation.citationendpage.none.fl_str_mv	e938
dc.relation.citationissue.spa.fl_str_mv	1
dc.relation.citationstartpage.none.fl_str_mv	e938
dc.relation.citationvolume.spa.fl_str_mv	15
dc.relation.ispartofjournal.spa.fl_str_mv	Revista Colombiana de Ciencia Animal - RECIA
dc.rights.uri.spa.fl_str_mv	https://creativecommons.org/licenses/by/4.0
dc.rights.accessrights.spa.fl_str_mv	info:eu-repo/semantics/openAccess
dc.rights.creativecommons.spa.fl_str_mv	Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
dc.rights.coar.spa.fl_str_mv	http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv	https://creativecommons.org/licenses/by/4.0 Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0. http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv	openAccess
dc.format.mimetype.spa.fl_str_mv	application/pdf application/epub+zip audio/mpeg
dc.publisher.spa.fl_str_mv	Universidad de Sucre
dc.source.spa.fl_str_mv	https://revistas.unisucre.edu.co/index.php/recia/article/view/938
institution	Universidad de Sucre
bitstream.url.fl_str_mv	https://repositorio.unisucre.edu.co/bitstreams/91246bc3-1c26-49b8-882c-4cca2a58607d/download
bitstream.checksum.fl_str_mv	9a636d2c44708cec4820d2ce2cb46dad
bitstream.checksumAlgorithm.fl_str_mv	MD5
repository.name.fl_str_mv	Repositorio Institucional Universidad de Sucre
repository.mail.fl_str_mv	bdigital@metabiblioteca.com
_version_	1814111924660469760
spelling	Hernández-Hernández, Leonardo55afddddd19ce3e952ca550d9afec815300Barragán-Hernández, Wilson Andrés008cdae734bb9019d77697f5d34339bdAngulo-Arizala, Joaquín1ddbe67aeb003c660a4f492562eb8349Mahecha-Ledesma, Lilianacf076a0f9f6e738d80f22448bcc5fbdd2023-06-29 05:46:572023-07-06T09:30:41Z2023-06-29 05:46:572023-07-06T09:30:41Z2023-06-29https://repositorio.unisucre.edu.co/handle/001/172210.24188/recia.v15.n1.2023.9382027-4297https://doi.org/10.24188/recia.v15.n1.2023.938Objetivo. Revisar las causas, consecuencias y métodos de determinación de la carne DFD con el fin de contribuir al conocimiento de esta anomalía para encontrar alternativas que contrarresten su presencia. Desarrollo. La carne DFD se presenta cuando las reservas de glucógeno muscular no son suficientes para que el pH descienda a su punto óptimo 24 h después del beneficio. Se estudian diversos factores ambientales e inherentes al animal que pueden estar interrelacionados y que serían los responsables de estrés y consecuente aparición de carne DFD. Así mismo, se revisan los diferentes métodos con los cuales se puede determinar esta condición. Consideraciones finales. El manejo de los animales pre- y pos-beneficio es determinante en la aparición de carnes DFD. Conocer los factores que influyen sobre su presencia y los métodos disponibles para su determinación puede contribuir con la disminución de esta anomalía y mejorar la calidad de las canales.Objective. Review the cause, consequences, and assessment methods in DFD beef to contribute to the knowledge of this meat anomaly and analyze alternatives to face. Development. The DFD beef shows up when the stock of muscular glycogen is not enough to decline muscular pH 24 h to the optimal point after being slaughtered. Several factors related to beef DFD including animal and environmental, are studied; likewise, asses’ methods are revised. Final considerations. Handling before and after slaughter are a keystone to DFD presence. Therefore, knowing the relationship among factors related to DFD and the assessment methods could diminish the DFD presence in the beef value chain.application/pdfapplication/epub+zipaudio/mpegspaUniversidad de SucreLeonardo Hernández-Hernández, Wilson Andrés Barragán-Hernández, Joaquín Angulo-Arizala, Liliana Mahecha-Ledesma - 2023https://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessEsta obra está bajo una licencia internacional Creative Commons Atribución 4.0.http://purl.org/coar/access_right/c_abf2https://revistas.unisucre.edu.co/index.php/recia/article/view/938Beef qualityCarcassOrganoleptic propertiesColorimetrySlaughterConsumersCalidad de la carneCanal animalPropiedades organolépticascolorimetríaSacrificioConsumidoresCarne oscura, firme y seca (DFD). Causas, implicaciones y métodos de determinaciónDark-cutting meat. Causes, implications, and methods of determinationArtículo de revistainfo:eu-repo/semantics/articleJournal articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_dcae04bchttp://purl.org/coar/resource_type/c_2df8fbb1Texthttp://purl.org/redcol/resource_type/ARTREVhttp://purl.org/coar/version/c_970fb48d4fbd8a85Klurfeld DM. Research gaps in evaluating the relationship of meat and health. Meat Sci. 2015; 109:86–95. http://dx.doi.org/10.1016/j.meatsci.2015.05.022Kamruzzaman M, Makino Y, Oshita S. Non-invasive analytical technology for the detection of contamination, adulteration, and authenticity of meat, poultry, and fish: A review. Anal Chim Acta. 2015; 853(1):19–29. http://dx.doi.org/10.1016/j.aca.2014.08.043García G, Zambrano W, Martínez G, Zambrano J. Alteraciones del pH y temperatura en la canal a causa de factores relacionados al transporte bovino previo al sacrificio. Rev Las Agrociencias. 2021; 26(Ed Esp)95–109. https://doi.org/10.33936/la_tecnica.v0i0.2524Ponnampalam EN, Hopkins DL, Bruce H, Li D, Baldi G, Bekhit AE din. Causes and Contributing Factors to “Dark Cutting” Meat: Current Trends and Future Directions: A Review. Compr Rev Food Sci Food Saf. 2017; 16(3):400–430. https://doi.org/10.1111/1541-4337.12258de Sousa Ribeiro CC, Contreras-Castillo CJ, Santos-Donado PR Dos, Venturini AC. New alternatives for improving and assessing the color of dark–cutting beef – a review. Sci Agric. 2022; 79(1):1–16. https://doi.org/10.1590/1678-992X-2020-0079Prieto N, López-Campos O, Zijlstra RT, Uttaro B, Aalhus JL. Discrimination of beef dark cutters using visible and near infrared reflectance spectroscopy. Can J Anim Sci. 2014; 94(3):445–454. https://doi.org/10.4141/cjas-2014-024Roberts JJ, Cozzolino D. An Overview on the Application of Chemometrics in Food Science and Technology—An Approach to Quantitative Data Analysis. Food Anal Methods. 2016; 9(12):3258–3267. http://dx.doi.org/10.1007/s12161-016-0574-7Paredi G, Raboni S, Bendixen E, de Almeida AM, Mozzarelli A. “Muscle to meat” molecular events and technological transformations: The proteomics insight. J Proteomics. 2012; 75(14):4275–4289. http://dx.doi.org/10.1016/j.jprot.2012.04.011Barragán-Hernández WA, Mahecha-Ledesma L, Olivera-Angel M, Angulo-Arizala J. Compositional and sensory quality of beef and its determination by near infrared. Agron Mesoamerican. 2021; 32(3):1000–1018. https://doi.org/10.15517/am.v32i3.40607Aboah J, Lees N. Consumers use of quality cues for meat purchase: Research trends and future pathways. Meat Sci. 2020; 166:108142. https://doi.org/10.1016/j.meatsci.2020.108142Purslow PP, Warner RD, Clarke FM, Hughes JM. Variations in meat colour due to factors other than myoglobin chemistry; a synthesis of recent findings (invited review). Meat Sci 2020; 159:107941. https://doi.org/10.1016/j.meatsci.2019.107941Prill LL, Drey LN, Olson BA, Rice EA, Gonzalez JM, Vipham JL, et al. Visual Degree of Doneness Impacts Beef Palatability for Consumers with Different Degree of Doneness Preferences. Meat Muscle Biol. 2019; 3(1):411-423. https://doi.org/10.22175/mmb2019.07.0024Gunders D. Wasted: How America is losing up to 40 percent of its food from farm to fork to landfill. NRDC Issue Pap; 2012. https://www.nrdc.org/sites/default/files/wasted-food-IP.pdfFranco D, Mato A, Salgado FJ, López-Pedrouso M, Carrera M, Bravo S, et al. Tackling proteome changes in the longissimus thoracis bovine muscle in response to pre-slaughter stress. J Proteomics. 2015; 122:73–85. http://dx.doi.org/10.1016/j.jprot.2015.03.029Beef Cattle Research Council. The 2010/11 National Beef Quality Audit: Canadá; 2010. https://www.beefresearch.ca/files/pdf/fact-sheets/nbqa_full_brochure_feb_2013.pdfBeef Cattle Research Council. National Beef Quality Audit, 2010/11 Beef Carcass Audit Fact Sheet: Canadá; 2011. https://www.beefresearch.ca/files/pdf/fact-sheets/1181_CCA_NBQA_Factsheet_June_15_F.pdfMcgilchrist P, Perovic JL, Gardner GE, Pethick DW, Jose CG. The incidence of dark cutting in southern Australian beef production systems fluctuates between months. Anim Prod Sci. 2014; 54(10):1765–1769. https://doi.org/10.1071/AN14356Riggs PK, Therrien DA, Vaughn RN, Rotenberry ML, Davis BW, Herring AD, et al. Differential Expression of MicroRNAs in Dark-Cutting Meat from Beef Carcasses. Appl. Sci. 2022; 12(7):3555. https://doi.org/10.3390/app12073555Fuente-Garcia C, Aldai N, Sentandreu E, Oliván M, Franco D, García-Torres S, Sentandreu M. Assessment of caspase activity in post mortem muscle as a way to explain characteristics of DFD beef. J. Food Compos. Anal. 2022; 111:104599. https://doi.org/10.1016/j.jfca.2022.104599Holdstock J, Aalhus JL, Uttaro BA, López-Campos Ó, Larsen IL, Bruce HL. The impact of ultimate pH on muscle characteristics and sensory attributes of the longissimus thoracis within the dark cutting (Canada B4) beef carcass grade. Meat Sci. 2014; 98(4):842–849. https://doi.org/10.1016/j.meatsci.2014.07.029Leyva-García IA, Figueroa-Saavedra F, Sánchez-López E, Pérez-Linares C, Barreras-Serrano A. Impacto económico de la presencia de carne DFD en una planta de sacrificio Tipo Inspección Federal ( TIF ). Arch Med Vet. 2012; 44(1):39–42.Loudon KMW, Lean IJ, Pethick DW, Gardner GE, Grubb LJ, Evans AC, et al. On farm factors increasing dark cutting in pasture fi nished beef cattle. Meat Sci. 2018; 144:110–117. https://doi.org/10.1016/j.meatsci.2018.06.011Rosa A, Fonseca R, Balieiro JC, Poleti MD, Domenech-Pérez K, Farnetani B, et al. Incidence of DFD meat on Brazilian beef cuts. Meat Sci. 2016; 112:132–133. https://doi.org/10.1016/j.meatsci.2015.08.074Patiño RM, Botero LM, Bohóquez W, Therán TM. Bienestar de Bovinos durante la fase de faenado en una planta de benefi cio de la región Caribe de Colombia. ACCB. 2019; 1(31):24–35. https://revistaaccb.org/r/index.php/accb/article/view/178Ramanathan R, Lambert LH, Nair MN, Morgan B, Feuz R, Mafi G. Economic Loss, Amount of Beef Discarded, Natural Resources Wastage, and Environmental Impact Due to Beef Discoloration. Meat Muscle Biol. 2022; 6(1):13218. https://doi.org/10.22175/mmb.13218Ramanathan R, Hunt MC, Mancini RA, Nair MN, Denzer ML, Suman SP, et al. Recent Updates in Meat Color Research: Integrating Traditional and High-Throughput Approaches. Meat Muscle Biol. 2020; 4(2):1-24. https://doi.org/10.22175/mmb.9598Claudia Terlouw EM, Picard B, Deiss V, Berri C, Hocquette JF, Lebret B, et al. Understanding the determination of meat quality using biochemical characteristics of the muscle: Stress at slaughter and other missing keys. Foods. 2021; 10(1):1-24. https://doi.org/10.3390/foods10010084Fraeye I, Kratka M, Vandenburgh H, Thorrez L. Sensorial and Nutritional Aspects of Cultured Meat in Comparison to Traditional Meat: Much to Be Inferred. Front Nutr. 2020; 7(35):1-7. https://doi.org/10.3389/fnut.2020.00035Sierra V, Olivan M. Role of Mitochondria on Muscle Cell Death and Meat Tenderization. Recent Pat Endocr Metab Immune Drug Discov. 2013; 7(2):120–129. https://dx.doi.org/10.2174/1872214811307020005Lana A, Zolla L. Proteolysis in meat tenderization from the point of view of each single protein: A proteomic perspective. J Proteomics. 2016; 147:85–97. http://dx.doi.org/10.1016/j.jprot.2016.02.011England EM, Matarneh SK, Oliver EM, Apaoblaza A, Scheffler TL, Shi H, et al. Excess glycogen does not resolve high ultimate pH of oxidative muscle. Meat Sci. 2016; 114:95–102. https://doi.org/10.1016/j.meatsci.2015.10.010McKeith RO, King DA, Grayson AL, Shackelford SD, Gehring KB, Savell JW, et al. Mitochondrial abundance and efficiency contribute to lean color of dark cutting beef. Meat Sci. 2016; 116:165–173. https://doi.org/10.1016/j.meatsci.2016.01.016England EM, Matarneh SK, Scheffler TL, Wachet C, Gerrard DE. pH inactivation of phosphofructokinase arrests postmortem glycolysis. Meat Sci. 2014; 98(4):850–857. https://doi.org/10.1016/j.meatsci.2014.07.019Zhang M, Dunshea FR, Warner RD, Digiacomo K, Chauhan SS, Warner RD. Impacts of heat stress on meat quality and strategies for amelioration : a review. Int J Biometeorol. 2020; 64:1613–1628. https://doi.org/10.1007/s00484-020-01929-6AMSA. Research Guidelines for Cookery, Sensory Evaluation, and Instrumental Tenderness Measurements of Meat. American Meat Science Association Educational Foundation. 2015. https://meatscience.org/docs/default-source/publications-resources/amsa-sensory-and-tenderness-evaluation-guidelines/research-guide/2015-amsa-sensory-guidelines-1-0.pdf?sfvrsn=6Ramanathan R, Suman SP, Faustman C. Biomolecular Interactions in Postmortem Skeletal Muscles Governing Fresh Meat Color : A Review. J. Agric. Food Chem. 2020; 68(46):12779-12787. https://doi.org/10.1021/acs.jafc.9b08098Contreras-Castillo CJ, Lomiwes D, Wu G, Frost D, Farouk MM. The effect of electrical stimulation on post mortem myofibrillar protein degradation and small heat shock protein kinetics in bull beef. Meat Sci. 2016; 113:65–72. https://doi.org/10.1016/j.meatsci.2015.11.012Wang LL, Yu QL, Han L, Ma XL, Song R De, Zhao SN, et al. Study on the effect of reactive oxygen species-mediated oxidative stress on the activation of mitochondrial apoptosis and the tenderness of yak meat. Food Chem. 2018; 244:394–402. http://dx.doi.org/10.1016/j.foodchem.2017.10.034Joo ST, Kim GD, Hwang YH, Ryu YC. Control of fresh meat quality through manipulation of muscle fiber characteristics. Meat Sci. 2013; 95(4):828–836. https://doi.org/10.1016/j.meatsci.2013.04.044Mouzo D, Rodríguez-vázquez R, Lorenzo JM, Franco D, Zapata C, López-pedrouso M. Proteomic application in predicting food quality relating to animal welfare . A review. Trends Food Sci Technol. 2020; 99:520–530. https://doi.org/10.1016/j.tifs.2020.03.029Loredo-Osti J, Sánchez-López E, Barreras-Serrano A, Figueroa-Saavedra F, Pérez-Linares C, Ruiz-Albarrán M, et al. An evaluation of environmental, intrinsic and pre- and post-slaughter risk factors associated to dark-cutting beef in a Federal Inspected Type slaughter plant. Meat Sci. 2019; 150:85–92. https://doi.org/10.1016/j.meatsci.2018.12.007Silva LHP, Assis DEF, Estrada MM, Assis GJF, Zamudio GDR, Carneiro GB, et al. Carcass and meat quality traits of Nellore young bulls and steers throughout fattening. Livest Sci. 2019; 229:28–36. https://doi.org/10.1016/j.livsci.2019.09.012Mahmood S, Basarab JA, Dixon WT, Bruce HL. Relationship between phenotype, carcass characteristics and the incidence of dark cutting in heifers. Meat Sci. 2016; 121:261–271. https://doi.org/10.1016/j.meatsci.2016.06.020King DA, Shackelford SD, Kuehn LA, Kemp CM, Rodriguez AB, Thallman RM, et al. Contribution of genetic influences to animal-to-animal variation in myoglobin content and beef lean color stability. J Anim Sci. 2010; 88(3):1160–1167. https://doi.org/10.2527/jas.2009-2544.Kawecki K, Stangierski J, Niedźwiedź J, Grześ B. The impact of environmental factors on the occurrence of DFD-type of beef in commercial abattoirs. Emirates J Food Agric. 2020; 32(7):533–542. https://doi.org/10.9755/ejfa.2020.v32.i7.2125Marenčić D, Ivanković A, Kozačinski L, Popović M. The effect of sex and age at slaughter on the physicochemical properties of baby-beef meat. Vet Arh. 2018; 88(1):101–110. https://doi.org/10.24099/vet.arhiv.160720Jacinto-valderrama RA, Sicca G, Sampaio L, Lucia M, Lima P, Noely J. Immunocastration on performance and meat quality of Bos indicus (Nellore) cattle under different nutritional systems. Sci. agric. 2021; 78(2):e20190136. http://dx.doi.org/10.1590/1678-992X-2019-0136Gardner GE, Hopkins DL, Greenwood PL, Cake MA, Boyce MD, Pethick DW. Sheep genotype, age and muscle type affect the expression of metabolic enzyme markers. Aust J Exp Agric. 2007; 47(10):1180–1189. https://doi.org/10.1071/EA07093Greenwood PL, Harden S, Hopkins DL. Myofibre characteristics of ovine longissimus and semitendinosus muscles are influenced by sire breed, gender, rearing type, age and carcass weight. Aust J Exp Agric. 2007; 47(10):1137–1146. https://doi.org/10.1071/EA06324Pérez Linares, Serrano, F. Figueroa Saavedra AB. Management Factores de manejo asociados a carne DFD en bovinos en climadesertico. Arch Zootec 2008; 57(220):545–547.Steel C, Lees AM, Tarr G, Warner R, Dunshea F, Cowley F, et al. The impact of weather on the incidence of dark cutting in Australian feedlot cattle. Int J Biometeorol. 2022; 66(2):263–274. https://doi.org/10.1007/s00484-021-02180-3Munilla ME, Vittone JS, Lado M, Romera SA, Teira GA. Efecto de las prácticas durante el manejo pre-faena sobre el rendimiento de la carne de bovinos. Rev Vet. 2021; 32(1):48. http://dx.doi.org/10.30972/vet.3215633Diro M, Mekete B, Gebremedhin EZ. Effect of pre-slaughter beef cattle handling on welfare and beef quality in Ambo and Guder markets and abattoirs, Oromia Regional State, Ethiopia. Ethiop J Sci Technol. 2021; 14(2):89–104. https://doi.org/10.4314/ejst.v14i2.1Osti JL, Serrano AB, Saavedra FF, Linares CP, Ruiz-Albarrán M. Evaluación de los componentes del manejo antes, durante y después de la matanza y su asociación con la presencia de carne DFD en bovinos del noreste de México. Rev. Mex. Cienc. Pecu. 2021; 12(3):773-788. https://doi.org/10.22319/rmcp.v12i3.4866Herrán L, Romero M, Herrán L. Interacción humano-animal y prácticas de manejo bovino en subastas colombianas. Rev Investig Vet del Peru. 2017; 28(3):571–585. https://doi.org/10.15381/rivep.v28i3.13360Lawrie RA, Ledward DA. Lawrie’s meat science. 7th ed. Cambridge: CRC Press; 2006Cordoba, C. Correa, G. Barahona, R. Tarazona A. Comportamiento de machos cebú en corrales presacrificio y su relación con el pH de la carne. Arch. Zootec. 66(256):579-586.Pérez-linares C, Barrera A, Sánchez E, Bárbara S, Figueroa-Saavedra F. Efecto del cambio en el manejo antemortem sobre la presencia de carne DFD en ganado bovino. Rev MVZ Cordoba. 2015; 20(3):4688-4697. https://doi.org/10.21897/rmvz.39Arik E, Karaca S. The effect of some pre-slaughter factors on meat quality of bulls slaughtered in a commercial abattoir in Turkey. Indian J Anim Res. 2017; 51(3):557–63.Cobo GC, Romero HM. Importancia de la interacción hombre-animal durante el presacrificio bovino: Revisión. Biosalud. 2012; 11(2):79–91.Carrasco-García AA, Pardío-Sedas VT, León-Banda GG, Ahuja-Aguirre C, Paredes-Ramos P, Hernández-Cruz BC, et al. Effect of stress during slaughter on carcass characteristics and meat quality in tropical beef cattle. Asian-Australasian J Anim Sci. 2020; 33(10):1656–1665. https://doi.org/10.5713/ajas.19.0804Clinquart A, Ellies-Oury MP, Hocquette JF, Guillier L, Santé-Lhoutellier V, Prache S. Review: On-farm and processing factors affecting bovine carcass and meat quality. Animal. 2022; 16:100426. https://doi.org/10.1016/j.animal.2021.100426Kim YHB, Ma D, Setyabrata D, Farouk MM, Lonergan SM, Huff-Lonergan E, et al. Understanding postmortem biochemical processes and post-harvest aging factors to develop novel smart-aging strategies. Meat Sci. 2018; 144:74–90. https://doi.org/10.1016/j.meatsci.2018.04.031McGilchrist P, Alston CL, Gardner GE, Thomson KL, Pethick DW. Beef carcasses with larger eye muscle areas, lower ossification scores and improved nutrition have a lower incidence of dark cutting. Meat Sci. 2012; 92(4):474–480. https://doi.org/10.1016/j.meatsci.2012.05.014Young OA, West J, Hart AL, Van Otterdijk FFH. A method for early determination of meat ultimate pH. Meat Sci. 2004; 66(2):493–498. https://doi.org/10.1016/S0309-1740(03)00140-2Kademi HI, Ulusoy BH, Hecer C. Applications of miniaturized and portable near infrared spectroscopy (NIRS) for inspection and control of meat and meat products. Food Rev Int. 2019; 35(3):201–220. https://doi.org/10.1080/87559129.2018.1514624Mancini RA, Hunt MC. Current research in meat color. Meat Sci. 2005; 71(1):100-121. https://doi.org/10.1016/j.meatsci.2005.03.003Li S, Zamaratskaia G, Roos S, Båth K, Meijer J, Borch E, et al. Inter-relationships between the metrics of instrumental meat color and microbial growth during aerobic storage of beef at 4°C. Acta Agric Scand A Anim Sci. 2015; 65(2):97–106.Hodgen J. Comparison of nix color sensor and nix color sensor pro to standard meat science research colorimeters. Meat Sci. 2016; 112:159. https://doi.org/10.1016/j.meatsci.2015.08.129Holman BWB, Collins D, Kilgannon AK, Hopkins DL. The e ff ect of technical replicate (repeats) on Nix Pro Color Sensor TM measurement precision for meat : A case-study on aged beef colour stability. Meat Sci. 2018; 135:42–45. https://doi.org/10.1016/j.meatsci.2017.09.001Holman BWB, Hopkins DL. A comparison of the Nix Colour Sensor ProTM and HunterLab MiniScanTM colorimetric instruments when assessing aged beef colour stability over 72 h display. Meat Sci. 2019; 147:162–165. https://doi.org/10.1016/j.meatsci.2018.09.009Prieto N, Pawluczyk O, Dugan MER, Aalhus JL. A Review of the Principles and Applications of Near-Infrared Spectroscopy to Characterize Meat, Fat, and Meat Products. Appl Spectrosc. 2017; 71(7):1403–1426. https://doi.org/10.1177/0003702817709299Farmer LJ, Farrell DT. Review: Beef-eating quality: A European journey. Animal. 2018; 12(11):2424–2433. https://doi.org/10.1017/S1751731118001672Ma J, Sun D, Pu H, Cheng J, Wei Q. Advanced Techniques for Hyperspectral Imaging in the Food Industry: Principles and Recent Applications. Annu Rev Food Sci Technol. 2019; 10:197–220. https://doi.org/10.1146/annurev-food-032818-121155Tomasevic I, Tomovic V, Milovanovic B, Lorenzo J, Đorđević V, Karabasil N, et al. Comparison of a computer vision system vs. traditional colorimeter for color evaluation of meat products with various physical properties. Meat Sci. 2019; 148:5–12. https://doi.org/10.1016/j.meatsci.2018.09.015https://revistas.unisucre.edu.co/index.php/recia/article/download/938/1070https://revistas.unisucre.edu.co/index.php/recia/article/download/938/1071https://revistas.unisucre.edu.co/index.php/recia/article/download/938/1072Núm. 1 , Año 2023 : RECIA 15(1):ENERO-JUNIO 2023e9381e93815Revista Colombiana de Ciencia Animal - RECIAPublicationOREORE.xmltext/xml2757https://repositorio.unisucre.edu.co/bitstreams/91246bc3-1c26-49b8-882c-4cca2a58607d/download9a636d2c44708cec4820d2ce2cb46dadMD51001/1722oai:repositorio.unisucre.edu.co:001/17222024-04-17 16:30:52.042https://creativecommons.org/licenses/by/4.0Leonardo Hernández-Hernández, Wilson Andrés Barragán-Hernández, Joaquín Angulo-Arizala, Liliana Mahecha-Ledesma - 2023metadata.onlyhttps://repositorio.unisucre.edu.coRepositorio Institucional Universidad de Sucrebdigital@metabiblioteca.com

Carne oscura, firme y seca (DFD). Causas, implicaciones y métodos de determinación

Publicaciones similares