Introduction.
This article is aimed at clarifying some basic concepts that concern everything related to animal genetic improvement, within which it is important to safeguard the study of its minimum stages and the facilitating tools for its implementation and propagation. These considerations are important because they increase the possibilities of improving the quality of livestock, and therefore the production of meat.
Origins of animal genetic improvement.
There is no agreement on which were the first domesticated animals. According to the literature, they belong to the families Canidae (dogs), Bovidae (bovines) and Caprinae (goats). Some 6,000 to 10,000 years ago, based on their experience, primitive man began a continuous process of selection from a productive and behavioral point of view, choosing for reproduction those copies that seemed most appropriate. All this leads us to reflect that the trends that modern man must follow are those of his predecessors, only with the difference that nowadays we have the help of animal genetic improvement technology, as mentioned above, animal selection was carried out choosing the best adapted animals, with the best weight, in short a series of parameters that only the choice of animal genetics gives, that is why the importance of the technologies currently used in animal genetic improvement is about.
This procedure was the most indicated according to the knowledge of the ancient era, since the primitive cattlemen used the only available tool of improvement of their animals: the phenotypic selection, or of the most beneficial features. Some breeders maintain this way of facing Genetic improvement until today. In principle, it is not an error, but on the contrary: it is what modern geneticists call mass selection (CONAMEG, 2007).
What we observe as external characteristics in livestock are usually the guides to choose the best specimens both in ancient times and in the present, a situation that makes us think that despite all the technological development as far as genetics is concerned, we still maintain in the present methods preserved since antiquity.
Conceptualization of animal genetic improvement.
Currently, it can be considered as animal genetic improvement as the set of all the fundamental biological and mathematical tools to increase the frequency of those genes related to characteristics that we consider favorable in a population of animals in their different classifications, all this with the intention of improving the breed of an animal category for purposes that can range from domestic needs to that of increasing the production of meat and milk in cattle.
The experiences of different countries have allowed to conclude that the steps of an animal genetic improvement plan are generally similar in any species, regardless of the place where it is developed and the production system (Buxadé, 1995).
Technical bases of the best unbiased linear prediction method (BLUP Methodology)
This method gives us the possibility of being able to predict breeding values with a minimum variation of these values. Among the assumed assumptions, it is worth mentioning the need to consider a correct genetic and statistical model, added to the knowledge of the genetic parameters of the population. When all kinship relationships between animals are included, the method allows the effects of drift and selection to be considered, provided that the latter is contained in the data. In addition, it is necessary that the selection has been based on a linear function invariant to the translation (Gianola, Fernando and Im, 1988 and 1989).
In practice, due to ignorance of the true genetic parameters, the BLUP prediction is carried out in two steps: first, the components of the variance are estimated, generally by means of the REML model (maximum restricted likelihood, acronym in English), and then they use the estimations for the prediction of the genetic values of the future descendants, which will be used in the generation of a ranking of reproducers.
The REML estimators, in addition to being sufficient, allow obtaining unbiased estimates in the presence of some forms of selection (Gianola and Fernando, 1989).
This methodology has been shown to be the most accurate in the presence of values without normal distribution, as is generally the case in field conditions (Robinson, 1991). In the application of the model, the design of a good experimental design is determinant, since REML estimates can be biased, for example when the base population does not constitute a random sample (Van der Werfy De Boer, 1990) or when the totality is lacking of information related to the selection process (Gianola and Fernando, 1989). Several authors have compared the use of BLUP versus traditional methods. Works carried out in pigs, using field and simulated data, highlight the advantages of BLUP compared to the use of selection indexes. BLUP is particularly advantageous in low heritability traits, which are expressed in a single sex, or when animals of different ages are compared in different environments. However, in the long term and in relation to the use of selection indexes, the use of BLUP as a selection method tends to increase inbreeding and reduce additive genetic variance (Wray, 1989). For a correct implementation of the BLUP it is necessary to mathematically model the genetic and environmental variation, so that it adjusts optimally to reality. It is necessary to adequately examine all the effects that affect the mean and variance of the different characters (Henderson, 1975).
Conclusion
In conclusion, the adequate implementation of an animal genetic improvement program should consider the use of quantitative and molecular genetic tools to maximize the expected impact. In the same way, genetic progress as a consequence of this plan will only be possible through an adequate reproductive management of the herd and / or the application of reproductive biotechnologies that allow the transfer of genetic progress to a greater number of producers and in a shorter time.
A breeding program aims to increase the frequency of certain genes (actually, gene alleles). The increase in the frequency of these alleles over time is called "gene progression" and their rate of increase will depend on factors such as the efficiency of the selection criteria, the crossing model used and the generational interval of the species with which work In general, a breeding program could begin to generate results from the first generation. In cattle, a female can be enrolled at 18 months, and gestate for 9 months, so the intergenerational period could be estimated in at least 30 months, given that the reproductive efficiency in heifers reaches between 70 and 80% in cattle of meat.
Experiences in the application of genetic management in cattle in the municipality Catatumbo Zulia State.
As I expressed it in my presentation in steemit, I am originally from Encontrados Municipio Catatumbo, Zulia state, Venezuela, in this beautiful region of the South of the Lake the cattle activity flourishes behind the academic knowledge of the Agricultural Production Engineers and Administrators in Agricultural Production, which we graduated from the Experimental University South del Lago, university that has been responsible for preparing professionals who like me want to contribute our knowledge in the area of agricultural production, especially in the genetic improvement of cattle, unfortunately the landowners or owners of large herds or haciendas do not see the need for knowledge in the genetic area to improve meat production, which is why by raising awareness of engineers in agricultural production as far as animal production is concerned we encourage study and new technologies in what we genetic breeding animal refers.
Glossary of fundamental terms in animal genetics
Genotype: Set of genes of an organism.
Phenotype: Observable external manifestation of a genotype.
Genetic value: Proportion in which the manifestation of a productive (phenotypic) character may be attributable to the genotype of the animal.
Additive variance: Variance produced by the existence of differences in mean phenotypic effects between alleles of the same gene.
Support bibliography for the realization of the article:
Jaime Piñeira V. Marine Biologist, Ph.D. José Luis Riveros F. Veterinarian, Ph.D. Ricardo Felmer D. Biochemist, Ph.D. Scientific journal Livestock and Prairies. Inia inland. (2009). Chile.