Phenotypic characterization for milk traits in crossbred cattle population from the state of Norte de Santander

Authors

DOI:

https://doi.org/10.5965/223811712242023645

Keywords:

multiple correspondence analysis, dual purpose, animal production, milk yield, standardized residues

Abstract

Crossbred cattle are used in dual-purpose systems to obtain meat and milk, becoming one of Colombia's systems with the greatest presence. However, studies characterizing productive variables in crossbred individuals are scarce, making it pertinent to conduct analyses evaluating their potential. The objective of this study was to phenotypically characterize a population of crossbred cattle from the state of Norte de Santander (Colombia) in terms of milk traits. Up to a maximum of 4 controls per female was obtained, and information on milk yield (MY), fat percentage (FP), protein percentage (PP), and somatic cell count (SCC) of first parity crossbred females was evaluated. The information was filtered and analyzed with the R program. The mean, standard deviation, and general variation coefficient were calculated for each trait and the means and deviations by non-genetic categorical factors. For the numeric factors, graphs of trends related to the response variables were made. Multiple correspondence analysis was performed, and the standardized residual values were estimated to recognize associations between levels of non-genetic factors and each trait. Mean values for controls were: 3.06±1.40 kg/day (MY), 3.21±0.40% (PP), 3.32±0.77% (FP), and 357±256x103 cells/ml (SCC). The non-genetic factors that showed the most significance were the pasture type, the control season, and the region. Thus, MY from 1.00 to 2.00 kg is associated with the levels of region 1 (R1) and summer 1 (S1), MY from 2.10 to 3.99 kg with region 2 (R2), group 1 (G1) and winter 1 (W1), MY from 4.00 to 8.30 kg with R1, group 3 (G3) and W1, PP from 2.45 to 2.99% there was association with G1, PP from 3.00 to 3.40% with group 2 (G2), PP from 3.41 to 6.04% with G3, FP of 1.94 to 3.00% is associated with R1, G3, S1, and S2, FP of 3.01 to 4.00% with R2, G1 and W1, FP from 4 to 4.82 % with region 3 (R3), G2, and S1, SCC from 8.00 to 100x103 cells/ml is associated with R1, R3, and S1, SCC of 101 to 499x103 cells/ml with R2, G1, and W1. Finally, SCC of 500 to 888x103 cells/ml is associated with R2 and W1. A variation of medium to high magnitude of the traits evaluated within the population was evidenced, revealing that no standards that allow unifying the management of animals within herds, which can affect the efficiency of dual-purpose systems.

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Author Biographies

Luisa Fernanda Naranjo Guerrero, Universidad Nacional de Colombia

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Nancy Rodríguez Colorado, Universidad Francisco de Paula Santander

.

Luis Gabriel González Herrera, Universidad Nacional de Colombia

.

References

ACOSTA-ACOSTA Y et al. 2020. La composición de la leche, su variación según raza y la lactancia. Ciencia y Tenología 24: 93-98.

AINSWORTH JAW et al. 2012. Pasture shade and farm management effects on cow productivity in the tropics. Agriculture. Ecosystems and Environment 155: 105-110.

ÁLVAREZ JEG. 2015. Comparación de los indicadores productivos porcentaje de grasa, porcentaje de proteína, recuento de células somáticas, nitrógeno ureico en leche y producción en litros de leche bovina de fincas pertenecientes a las microcuencas del norte y oriente de Antioquia. Disertación (Pregrado en Administración de Empresas Agropecuarias) Antioquia: Corporación Universitaria La Sallista. 46p.

BAÉZ R et al. 2015. Factores asociados a la calidad físico-química de la leche en sistemas bovinos de doble propósito, en ranchos del Mezcalapa. En: VII Reunión Científica Tecnológica, Forestal y Agropecuaria Tabasco 2015. IV Simposio Internacional en Producción Agroalimentaria Tropical. p.295-300.

BREEN JE et al. 2009. Quarter and cow risk factors associated with a somatic cell count greater than 199,000 cells per milliliter in United Kingdom dairy cows. Journal of Dairy Science 92: 3106-3115.

CASTILLO-BADILLA G et al. 2019. Factors that affect the production in first lactation of dairy cattle of Costa Rica. Agronomy Mesoamerican 30: 209-227.

CHEROBIN VC et al. 2019. Condición corporal y su relación con producción láctea, reproducción y perfil metabólico en vacas lecheras del trópico boliviano. Revista de Investigaciones Veterinarias Del Peru 30: 107-118.

COZMA A et al. 2013. Influence of calf presence during milking on yield, composition, fatty acid profile and lipolytic system of milk in Prim’Holstein and Salers cow breeds. Dairy Science and Technology 93: 99-113.

DE VRIES A & MARCONDES MI. 2020. Review: Overview of factors affecting productive lifespan of dairy cows. Animal 14: S155-S164.

DURÁN-ROJAS E et al. 2020. Clasificación de empresas ganaderas doble propósito por calidad y canales de comercialización de la leche en el Caribe colombiano. Revista UDCA Actualidad & Divulgación Científica 23: e1358.

FRANZOI M et al. 2019. Variation of detailed protein composition of cow milk predicted from a large database of mid-infrared spectra. Animals 9: 1-14.

JUÁREZ-BARRIENTOS JM et al. 2015. Tipificación de sistemas de doble propósito para producción de leche en el distrito de desarrollo rural 008, Veracruz, México. Revista Cientifica de La Facultad de Ciencias Veterinarias de La Universidad Del Zulia 25: 317-323.

JURADO-GÁMEZ H et al. 2019. Evaluación de la calidad composicional, microbiológica y sanitaria de la leche cruda en el segundo tercio de lactancia en vacas lecheras. Revista de La Facultad de Medicina Veterinaria y de Zootecnia 66: 53-66.

MADRID A et al. 2020. Modelación de la curva de producción, grasa y proteína en ganado Holstein y Jersey del Norte y Oriente de Antioquia. Revista Universidad Católica de Oriente 31: 70-84.

MARINI PR & DI MASSO RJ. 2019. Edad al primer parto e indicadores de eficiencia en vacas lecheras con diferente potencialidad productividad en sistemas a pastoreo. La Granja: Revista de Ciencias de La Vida 29: 84-96.

MENDOZA-SÁNCHEZ G et al. 2009. Factores ambientales que afectan el recuento de células somáticas en leche de búfalos (Bubalus bubalis). Revista de Medicina Veterinaria 18: 11-20.

NARANJO-GUERRERO LF et al. 2022. Caracterización bromatológica de pastos en seis municipios del Departamento de Norte de Santander; Colombia. Scientia Et Technica 27: 245-252.

NAVARRO R et al. 2021. A multivariate statistical analysis of milk yield and quality in intensive dairy procution systems in Paraná state, Brazil. Tropical and Subtropical Agroecosystems 24: 1-11.

NÚÑEZ-TORRES OP & ALMEIDA-SECAIRA RI. 2022. Quantitative genetics: principles of farming in livestock production. Journal of the Selva Andina Animal Science 9: 23–36.

PERSSON WALLER K et al. 2020. Udder health of early-lactation primiparous dairy cows based on somatic cell count categories. Journal of Dairy Science 103: 9430-9445.

R CORE TEAM. 2021. A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. https://www.r-project.org

RODRÍGUEZ VC et al. 2015. Calidad de leches crudas en sistemas doble propósito en Córdoba (Colombia), en condiciones de máxima y mínima precipitación. Ciencia Y Agricultura 12: 51.

SÁNCHEZ-CASTRO et al. 2019. Stability of genetic predictions for stayability using random regression models that include end points beyond 6 yr of age. Transl. Anim. Sci., 3: 1678-1682.

SALAMANCA C & BENTEZ M. 2012. Producción de leche de vacas mestizas del Sistema Doble Propósito en el municipio de Arauca. Revista Electrónica de Veterinaria 13: 1-15.

SOSSA C & BARAHONA R. 2015. Comportamiento productivo de novillos pastoreando en tropico de altura con y sin suplementación energética. Revista de la facultad de Medicina Veterianaria y Zootecnia 62: 67-80.

TERÁN J. 2014. Manejo semiestabulado de ganado de leche en la asociación campo verde de Turucucho. Disertación (Pregrado en ingeniería agropecuaria) Quito: Universidad politécnica Salesiana. 139p.

VALLEJO C et al. 2018. Calidad físico-química e higiénico sanitaria de la leche en sistemas de producción doble propósito,Manabí-Ecuador. Revista de Investigación Talentos 5: 35-44.

VARGAS SOBRADO D et al. 2017. Valores de la relación grasa/proteína y nitrógeno ureico en leche de vacas lecheras de la zona norte de Alajuela y Heredia, Costa Rica. Revista Ciencias Veterinarias 34: 67.

VÉLEZ-ECHEVERRI L & GONZÁLEZ-HERRERA LG. 2018 Prevalencia de mastitis en vacas Lucerna y sus cruces. Livestock Research for Rural Development 30.

VITE C et al. 2015. Factores genéticos y no genéticos que afectan los indices productivos y reproductivos de vacas doble propósito en la huasteca veracruzana. Zootecnia Tropical 33: 337-349.

WERNER E. 2014. Relación de la producción de leche y calidad sobre el recuento de células somáticas en rebaños del sur de Chile. Disertación (pregrado en ingeniería agronómica) Chile: Universidad Austral de Chile. 33p.

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Published

2023-12-29

How to Cite

GUERRERO, Luisa Fernanda Naranjo; COLORADO, Nancy Rodríguez; HERRERA, Luis Gabriel González. Phenotypic characterization for milk traits in crossbred cattle population from the state of Norte de Santander. Revista de Ciências Agroveterinárias, Lages, v. 22, n. 4, p. 645–655, 2023. DOI: 10.5965/223811712242023645. Disponível em: https://revistas.udesc.br/index.php/agroveterinaria/article/view/23578. Acesso em: 22 dec. 2024.

Issue

Section

Research Article - Science of Animals and Derived Products