The main definition for meat quality should include factors that affect consumer appreciation of the product. Physical laboratory analyses are necessary to identify factors that affect meat quality and specific equipment is used for this purpose, which is expensive and destructive, and the analyses are usually time consuming. An alternative method to performing several beef analyses is near-infrared reflectance spectroscopy (NIRS), which permits to reduce costs and to obtain faster, simpler, and nondestructive measurements. The objective of this study was to evaluate the feasibility of NIRS to predict shear force [Warner-Bratzler shear force (WBSF)], marbling, and color (*a = redness; b* = yellowness; and L* = lightness) in meat samples of uncastrated male Nelore cattle, that were approximately 2-yr-old. Samples of longissimus thoracis (n = 644) were collected and spectra were obtained prior to meat quality analysis. Multivariate calibration was performed by partial least squares regression. Several preprocessing techniques were evaluated alone and in combination: raw data, reduction of spectral range, multiplicative scatter correction, and 1st derivative. Accuracies of the calibration models were evaluated using the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), coefficient of determination in the calibration (R2C), and prediction (R2P) groups. Among the different preprocessing techniques, the reduction of spectral range provided the best prediction accuracy for all traits. The NIRS showed a better performance to predict WBSF (RMSEP = 1.42 kg, R2P = 0.40) and b* color (RMSEP = 1.21, R2P = 0.44), while its ability to accurately predict L* (RMSEP = 1.98, R2P = 0.16) and a* (RMSEP = 1.42, R2P = 0.17) was limited. NIRS was unsuitable to predict subjective meat quality traits such as marbling in Nelore cattle.

Traditional selection programs for dairy cattle, based on quantitative principles, have worked well and allowed strong selection processes in the world over many decades. The objectives of this work were to estimate linkage disequilibrium (LD) levels at varying SNPs densities, to evaluate the effective population size of Holstein cattle, to characterize runs of homozygosity (ROH) distribution through Holstein cattle from Nariño and, to estimate and compare inbreeding coefficient (F) based on genomic markers information, runs of homozygosity (FROH), genomic relationship matrix (FGRM), and excess of homozygous (FSNP). After quality control, the dataset used was composed of 606 Holstein animals and 22200 SNP markers. PLINK program was used to identify LD, Ne, ROH segment and FROH and FSNP, FGRM was calculated with BLUPF90 family of programs. The average of r2 in all chromosomes was 0.011, the highest r2 was found in BTA3 (0.0323), and the lowest in BTA12 (0.0039). 533 ROH segments were identified in 319 animals; findings obtained in this study suggest that on average 0,28% of Holstein genome is autozygous. Total length of ROH was composed mostly of small segments (ROH1-4Mb and ROH4-8Mb). These segments accounted for approximately 96%, while larger ROH (ROH>8Mb) were 3.37% of all ROH detected. Inbreeding averages FROH, FSNP and FGRM methodologies were 0.28%, 3.11% and 3.36% respectively. The Pearson’s correlation among these different F values was: 0.49 (FROH-FSNP), 0.25 (FROH-FGRM), 0.22 (FSNP-FGRM). The distribution of ROH shared regions identified on 19 autosome chromosomes, cover a relevant number of genes inside these ROH. Our result evidenced lowest LD extension levels compared with other Holstein populations; inbreeding results suggest that FGRM and FSNP may be useful estimators of individual autozygosity in Holstein from Colombia. Genes related with production and reproduction were found, but the most important are the two that may be related to adaptation to Colombian high tropics. This work is a pioneer and be the starting point for programs of genetic improvement and genomic population studies in the country and mainly in high tropic areas where the dairy breeds have an important production.

Evolutionary mechanisms have shaped the genomic architecture of Colombian Creole cattle breeds. The mating and selection processes have impacted several traits, promoting differences within and between populations. Studies of population structure and selection signatures in Colombian Creole breeds are scarce, and need more attention to better understand genetic differentiation, gene flow, and genetic distance. This study aimed to analyze the population structure and identify selection imprints in the Criollo Caqueteño (CAQ) population. It used 127 CAQ animals genotyped with Chip HD 777,000 SNPs. The population structure analyses used discriminant principal component analysis (DAPC), integrated haplotype scoring (iHS), and index-fixing (Fst) methodologies to detect selection signals. We can highlight SNP regions on the genes TMPRSS15, PGAM2, and EGFR, identified by the Fst method. Additionally, the iHS regions for cluster 1 identified candidate genes on BTA 3 (CMPK1 and FOXD2), BTA 11 (RCAN1), and BTA 22 (ARPP21). In group 2, we can highlight the genes on BTA 4 (SLC13A4, BRAF), BTA 9 (ULBP), BTA 14 (CSMD3) and BTA 19 (KRTAP9-2). These candidate genes have been associated with fertility traits, precocity, growth, and environmental and disease resistance, indicating a genetic potential in CAQ animals. All this promotes a better understanding of the diversity and genetic structure in the CAQ population. Based on that, our study can significantly assist the sustainable development and conservation of the breed in the Colombian Amazon.

Los estudios de genealogías nacen del interés por aclarar el dilema "de dónde venimos y adónde vamos”. Ante esta situación se comienza por consolidar los registros de padres, madres y abuelos (paternos y maternos) iniciando así un árbol genealógico. La falta de la consolidación del registro genealógico en los sistemas de producción se convierte en un impedimento para el análisis de pedigrí y la realización de evaluaciones genéticas. El objetivo de este estudio fue evaluar la genealogía de los animales involucrados en los apareamientos para la generación de embriones implantados, mediante la técnica de transferencia de embriones en el proyecto GESTAR. La base de datos contó con 741 registros de animales y una profundidad de 5 generaciones. Se utilizaron softwares, Pedigree Viewer versión 6.5 y CFC: Tool For Monitoring Genetic Diversity versión 1.0, para realizar análisis genealógicos, renumerar los registros de los individuos y evaluar la profundidad del pedigree. Resultados y conclusión: De los 741 registros de animales que comprenden 5 generaciones, se identificaron 551 progenies, 181 registros de padres y 282 de madres. Los registros clasificaron a 184 individuos fundadores y 557 no fundadores, 6 individuos con identificación de padre y 551 con padre y madre conocido, 74 grupos de hermanos completos con un tamaño promedio por familia de 3.72 animales, un máximo 20 y mínimo de 2, y 42 de identificados como consanguíneos. La genealogía evaluada presenta una alta conectabilidad entre los individuos y posee una adecuada profundidad para ser usada en programas de mejoramiento genético o de transferencia de embriones, aumentando así la confiabilidad de los valores genéticos y otros parámetros de interés

La Universidad está en permanentes procesos de autoevaluación con la pretensión de obtener insumos para el mejoramiento del currículo y es por ello que surge el interés de sistematizar la experiencia que se deriva de la implementación de la estrategia de los semilleros de investigación. De allí que la presente investigación plantea como objetivo de investigación la generación de un modelo psicopedagógico que sea útil para la implementación de semilleros de investigación en instituciones de educación superior virtual mediante el cual se integre La Universidad con los territorios. El instrumento de medición fue basado en un cuestionario en escala Likert en tres momentos diferentes dentro del desarrollo de los semilleros transversales de investigación en el año 2020. El análisis estadístico determinó el nivel de asociación de las variables clasificadas en los tres factores diferenciados: competencias digitales, habilidades blandas y habilidades para la investigación. Dentro de los resultados más relevantes se encontró que la autorregulación del pensamiento fue correlacionada significativamente demostrando que en los semillerista que participaron en los dos periodos de estudio se mejoraron en gran medida las habilidades para, la comunicación, organización de su tiempo, generación de preguntas y finalmente para defender sus ideas. Los estudiantes presentaron un nivel alto de correlación entre las dos primeras aplicaciones del instrumento con relación a el trabajo en equipo, la socialización, el autoaprendizaje, la capacidad de adaptación, la integridad y el respeto por sí mismo, en este sentido, se presenta un incremento del nivel de correlación hasta valores medio y alto, de las habilidades para la investigación con respecto a la capacidad de adaptación de los semilleristas.