Mario F Cerón-Muñoz

Test-day milk yield as a selection criterion for dairy buffaloes (Bubalus bubalis Artiodactyla, Bovidae)

Due to the great demand for buffalo milk by-products the interest in technical-scientific information about this species is increasing. Our objective was to propose selection criteria for milk yield in buffaloes based on total milk yield, 305-day milk yield (M305), and test-day milk yield. A total of 3,888 lactations from 1,630 Murrah (Bubalus bubalis) cows recorded between 1987 and 2001, from 10 herds in the State of Sao Paulo, Brazil, were analyzed. Covariance components were obtained using the restricted maximum likelihood method applied to a bivariate animal model. Additive genetic and permanent environmental effects were considered as random, and contemporary group and lactation order as fixed effects. The heritability estimates were 0.22 for total milk yield and 0.19 for M305. For test-day yields, the heritability estimates ranged from 0.12 to 0.30, with the highest values being observed up to the third test month, followed by a decline until the end of lactation. The present results show that test-day milk yield, mainly during the first six months of lactation, could be adopted as a selection criterion to increase total milk yield.

Direct genetic, maternal genetic, and heterozygosity effects on weaning weight in a Colombian multibreed beef cattle population.

The (co)variance components of BW at weaning (WW) were estimated for a Colombian multibreed beef cattle population. A single-trait animal model was used. The model included the fixed effect of contemporary group (sex, season, and year), and covariates including age of calf at weaning, age of cow, individual and maternal heterozygosity proportions, and breed percentage. Direct genetic, maternal genetic, permanent environmental, and residual effects were included as random effects. Direct, maternal, and total heritabilities were 0.23 +/- 0.047, 0.15 +/- 0.041, and 0.19, respectively. The genetic correlation between direct and maternal effects was -0.42 +/- 0.131, indicating that there may be antagonism among genes for growth and genes for maternal ability, which in turn suggests that improving WW by direct and maternal EPD may be difficult. A greater value for the direct heterosis effect compared with the maternal heterosis effect was found. Furthermore, the greater the proportion of Angus, Romosinuano, and Blanco Orejinegro breeds, the less the WW.

Genetic principal components for reproductive and productive traits in dual-purpose buffaloes in Colombia.

A multitrait model (MC) and 5 reduced-rank models with principal component structure (components PC, PC, PC, PC, and PC) were compared. The objectives were to determine the most appropriate model for estimating genetic parameters and to evaluate the genetic progress of dual-purpose buffaloes in Colombia using that model. The traits evaluated were weaning weight (WW), yearling weight (W12), weight at 18 mo of age (W18), weight at 2 yr of age (W24), age at first calving (AFC), and milk yield at 270 d of first lactation (MY270). Genealogy and productive information from 34,326 buffaloes born in Colombia between 1997 and 2014 were used. Colombian Association of Buffalo Breeders (ACB) provided the data. Direct additive genetic and residual random effects were included for all the traits. In addition, the maternal additive genetic effect and permanent environmental random effect were included for WW, while a maternal additive genetic effect was included for W12. The fixed effects were contemporary group (farm, year, and calving season: January to April, May to August, or September to December; for all traits) and sex (for WW, W12, W18, and W24). Additionally, parity was included as a fixed effect for WW and W12. Age at weighing was used as a covariate for WW, W12, W18, and W24. Genetic progress of all traits was analyzed using a generalized smooth model (GAM). According to the Akaike information criteria (AIC), the best model was the one with reduced rank and first 3 principal components (PC). This model maintained 100% of the original variance. Genetic parameters estimated with this model were similar to those estimated by MC, but with smaller standard errors. Heritability for weight-related traits ranged between 0.23 and 0.44. Heritabilities for AFC and MY270 were 0.14 and 0.24, respectively. The genetic correlations obtained between all weights (WW, W12, W18, and W24) were positive and high. Correlations between all weights with AFC were negative and moderate. Correlations between all weights with MY270 were positive and moderate, and between MY270 with AFC were negative and low.

Lactose and milk urea nitrogen: fluctuations during lactation in Holstein cows

The objective of this study was to evaluate lactose and milk urea nitrogen (MUN) in milk from Holstein cows and their relationship with days in milk (DIM), milk yield, milk fat, milk protein, and somatic cell count (SCC). A total of 1,034 records corresponding to morning and afternoon milkings of 148 Holstein cows were used. Records were taken from 16 herds located in the Northern and Eastern dairy regions of Antioquia (Colombia). The curves were fitted using a generalized additive mixed model with smoothed estimates to find the best smoothing intensity factors involved in MUN and lactose concentration. Regarding MUN, the contemporary group effect was highly significant, but the parity effect was not significant. The DIM, lactose and milk fat smoothed covariates were highly significant, while milk yield and fat and SCC showed no statistical difference. Regarding lactose content, the contemporary group effect was highly significant, while the parity effect was not significant. Days in milk, MUN, milk fat, milk protein, and afternoon-milking SCC smoothed covariates were highly significant, while milk yield and morning-milking SCC were not significant. Lactose and milk urea nitrogen concentrations are affected by various factors throughout lactation, mainly by days in milk.

Correction: Genetic Evaluation of Dual-Purpose Buffaloes (Bubalus bubalis) in Colombia Using Principal Component Analysis

There is an error in Fig 1 Please see the corrected Fig 1 here. open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Genetic diversity and population structure of the Guinea pig (Cavia porcellus, Rodentia, Caviidae) in Colombia

The aim was to establish the genetic diversity and population structure of three guinea pig lines, from seven production zones located in Nariño, southwest Colombia. A total of 384 individuals were genotyped with six microsatellite markers. The measurement of intrapopulation diversity revealed allelic richness ranging from 3.0 to 6.56, and observed heterozygosity (Ho) from 0.33 to 0.60, with a deficit in heterozygous individuals. Although statistically significant (p < 0.05), genetic differentiation between population pairs was found to be low. Genetic distance, as well as clustering of guinea-pig lines and populations, coincided with the historical and geographical distribution of the populations. Likewise, high genetic identity between improved and native lines was established. An analysis of group probabilistic assignment revealed that each line should not be considered as a genetically homogeneous group. The findings corroborate the absorption of native genetic material into the improved line introduced into Colombia from Peru. It is necessary to establish conservation programs for native-line individuals in Nariño, and control genealogical and production records in order to reduce the inbreeding values in the populations.

Influence of attitudes and behavior of milkers on the hygienic and sanitary quality of milk

Recognizing how human behaviors affect the milk process can be useful to understand variations in hygienic and sanitary parameters in bulk tank milk. Furthermore, this knowledge could be used to design management programs that guarantee milk quality, favoring the optimization of such processes. Forty-six milkers from the same number of dairy farms in Antioquia province (Colombia) were interviewed to establish the main factors associated to milk quality. Technical knowledge, motivations, and behavior of the personnel and its effect on hygienic and sanitary quality of milk were evaluated. Quality was assessed in terms of colony-forming units (CFU) and somatic cell count (SCC) in bulk tank milk. Two factors from a multivariate mixed data analysis were evaluated. One of those factors explained 9.51% of the total variability, related with in-farm availability and use of tools and the relationships between milker and manager. The other factor, associated with work environment and recognition, explained 6.97% of the total variability. The variables that best explained CFU levels were Knowledge of the udder condition at milking, and Milking type (parlor or pasture). The SCC was associated to knowledge of animal handling, schooling of milkers, milking site, and the groups derived from the cluster analysis by farm. In conclusion, milker attitudes and behaviors can affect CFU and SCC in bulk tank milk.

Ability of non-linear mixed models to predict growth in laying hens

In this study, the Von Bertalanffy, Richards, Gompertz, Brody, and Logistics non-linear mixed regression models were compared for their ability to estimate the growth curve in commercial laying hens. Data were obtained from 100 Lohmann LSL layers. The animals were identified and then weighed weekly from day 20 after hatch until they were 553 days of age. All the nonlinear models used were transformed into mixed models by the inclusion of random parameters. Accuracy of the models was determined by the Akaike and Bayesian information criteria (AIC and BIC, respectively), and the correlation values. According to AIC, BIC, and correlation values, the best fit for modeling the growth curve of the birds was obtained with Gompertz, followed by Richards, and then by Von Bertalanffy models. The Brody and Logistic models did not fit the data. The Gompertz nonlinear mixed model showed the best goodness of fit for the data set, and is considered the model of choice to describe and predict the growth curve of Lohmann LSL commercial layers at the production system of University of Antioquia.

Semiparametric Modeling of Daily Ammonia Levels in Naturally Ventilated Caged-Egg Facilities.

Ammonia concentration (AMC) in poultry facilities varies depending on different environmental conditions and management; however, this is a relatively unexplored subject in Colombia (South America). The objective of this study was to model daily AMC variations in a naturally ventilated caged-egg facility using generalized additive models. Four sensor nodes were used to record AMC, temperature, relative humidity and wind speed on a daily basis, with 10 minute intervals for 12 weeks. The following variables were included in the model: Heat index, Wind, Hour, Location, Height of the sensor to the ground level, and Period of manure accumulation. All effects included in the model were highly significant (p<0.001). The AMC was higher during the night and early morning when the wind was not blowing (0.0 m/s) and the heat index was extreme. The average and maximum AMC were 5.94±3.83 and 31.70 ppm, respectively. Temperatures above 25°C and humidity greater than 80% increased AMC levels. In naturally ventilated caged-egg facilities the daily variations observed in AMC primarily depend on cyclic variations of the environmental conditions and are also affected by litter handling (i.e., removal of the bedding material).

Modelación del crecimiento de pollitas Lohmann LSL con redes neuronales y modelos de regresión no lineal

espanolObjetivo. Modelar la curva del crecimiento de aves de la linea Lohmann LSL utilizando modelos no lineales (MNL), no lineales mixtos (MNLM) y redes neuronales artificiales (RNA). Materiales y metodos. Periodicamente se pesaron 33 aves en promedio, desde el dia 21 al 196 de vida para un total de 558 registros individuales de peso. En el ajuste de la curva de crecimiento se utilizaron los modelos: no lineal de Von Bertalanffy (MNL), no lineal Mixto de Von Bertalanffy (MNLM) y redes neuronales artificiales (RNA). Los modelos se compararon con coeficiente de correlacion y medidas de presicion cuadrado medio del error (CME), desviacion media absoluta (MAD) y porcentaje de la media absoluta del error (MAPE). Resultados. Los valores de correlacion entre los datos reales y estimados, fueron 0.999, 0.990 y 0.986 para MNLM, RNA y MNL respectivamente. El modelo mas preciso con base en los criterios MAPE, MAD y CME fue el MNLM, seguido por la RNA. La grafica de prediccion generada la RNA es similar a la del MNLM. La RNA presento un desempeno superior al MLN. Conclusiones. El mejor modelo para la prediccion de curvas de crecimiento de aves comerciales de la linea Lohmman LSL hasta los 196 dias de edad, con multiples mediciones por animal en el tiempo, fue el MNLM. La RNA presento un desempeno superior al MNL. EnglishObjective. Modeling the pullet growth curve of the Lohmann LSL line, by using nonlinear model (MNL), nonlinear mixed model (MNLM) and artificial neural networks (ANN). Materials and methods. An average of 33 birds, were weighed from day 21 to 196 of life for 558 individual weight records. To adjust the growth curve the following models were used: nonlinear Von Bertalanffy (MNL), nonlinear mixed Von Bertalanffy (MNLM) and artificial neural networks (RNA). The models were compared with a correlation coefficient and precision measurements: mean square error (MSE), Mean Absolute Deviation (MAD) and the mean absolute percentage error (MAPE). Results. Correlation values, between actual and estimated data, were 0.999, 0.990 and 0.986 for MNLM, RNA and MNL respectively. The most accurate model based on the MAPE, MAD and CME criteria was MNLM followed by RNA. The prediction graph for RNA was similar to MNLM. The RNA performance was higher than MLN. Conclusions. The best model for the prediction of growth curves of commercial Lohmman LSL birds to 196 days of age, was the MNLM, with multiple measurements per animal at the time. RNA performance was higher MLN.