trabalho completo - 52ª Reunião Anual da Sociedade Brasileira de
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trabalho completo - 52ª Reunião Anual da Sociedade Brasileira de
52a Reunião Anual da Sociedade Brasileira de Zootecnia Zootecnia: Otimizando Recursos e Potencialidades Belo Horizonte – MG, 19 a 23 de Julho de 2015 Análise de componentes principais dos fatores envolvidos na taxa de prenhez em matrizes de corte submetidas a IATF1 Maria Dulcinéia da Costa2, Robertha Veloso Rebello3, José Reinaldo Mendes Ruas2, Julieta Maria Alencar Chamone2, Antônia de Maria Filha Ribeiro2, Anielle Cristina Alves Meneses 3, Wemerson Fábio Gomes Ribas4 1 Parte de da dissertação Mestrado do segundo autor Programa de Pós-Graduação em Zootecnia – UNIMONTES – Janaúba, Brasil, Bolsista FAPEMIG e:mail:[email protected] Mestranda Programa Pós-graduação em Zootecnia - UNIMONTES, BRA. Bolsista do CAPES. 4 Curso de Zootecnia - UNIMONTES, BRA. Bolsista do FAPEMIG / PIBIC. 2 3 Resumo: Foi objetivo com o trabalho avaliar a importância relativa das características que afetam a taxa de prenhez em vacas submetidas a IATF no Norte de Minas Gerais utilizando análise de componentes principais. Vários são os efeitos que pode afetar a taxa de prenhez e faz-se necessário conhecer a importância e contribuição de cada uma destas variáveis. A técnica de componentes principais é utilizada para descrever os fatores responsáveis por diferenças entre indivíduos, de acordo com um conjunto de respostas correlacionadas observadas numa população. Foram analisadas 8683 informações na estação de monta de dezembro de 2012 a maio de 2013. Foram avaliados os efeitos da categoria reprodutiva, escore corporal, touro, raça touro, horário da inseminação, estímulos ovulatórios, dia da aplicação de prostaglandina, utilização do CIDR, inseminador, estruturas de ovário e dose de ECG sobre a presença ou ausência de prenhez em animais submetidos à inseminação artificial em tempo fixo (IATF). A taxa média de prenhez foi de 52,79%. Verificou-se que cinco componentes principais responderam por 65,01 % da variância total. Os autores concluíram que dose de ECG, uso do CIDR, estímulos ovulatórios, raça do touro e inseminador são responsáveis pela maior variação na taxa de prenhez em vacas submetidas a IATF e as variáveis categorias reprodutivas, escore corporal, estrutura do ovário, dia da aplicação da protaglandina, horário da IATF contribuem muito pouco para a variabilidade da taxa de prenhez. Palavras–chave: biotecnologias reprodutivas, gado de corte, índice reprodutivo, reprodução Principal component analysis for factors involved in the pregnancy rate in beef cows subjected to IATF Abstract: The objective of this study was to evaluate the relative importance of characteristics affecting the pregnancy rate in cows submitted to TAI in the North of Minas Gerais using principal component analysis. There are many effects that can affect the pregnancy rate and it is necessary to know the importance and contribution of each of these variables. The technique of principal components is used to describe the factors responsible for the differences between individuals, according to a set of correlated responses observed in a population. We analyzed 8683 data in the breeding station from December 2012 to May 2013. The effects of reproductive category, body score, sire, sire breed, the insemination time, ovulatory stimulus, on the application of prostaglandin, using CIDR, inseminator, ovarian structures and ECG dose on the presence or absence of pregnancy in animals subjected to fixed time artificial insemination (TAI). The average pregnancy rate was 52.79%. It was found that five principal components accounted for 65.01% of the total variance. The authors concluded that ECG dose, CIDR use, ovulatory stimulus, bull race and inseminator are responsible for the variation in pregnancy rate in cows submitted to IATF and the variables reproductive categories, body score, ovarian structure, application of day the prostaglandin, the IATF time contribute very little to the variability of pregnancy rate. Keywords:, beef cattle, reproduction, reproductive rate, reproductive biotechnologies Introduction The pregnancy rate is one of the largest impact variables in assessing the reproductive performance and contributes considerably to bioeconomic efficiency. There are several factors that influence pregnancy rate in animals as efficiency in estrus detection, insemination time, semen handling, inseminator skill. It is necessary to know the importance and contribution of each of these variables that influence the pregnancy rate (BARUSELLI, 2012, MENEGHETTI et al, 2009). When evaluating many variables it is possible that some of these parameters are redundant (JOLLIFFE, 1973). The technique of principal components is used to describe the factors responsible for the differences between individuals, according to a set of correlated responses observed in a population. The method consists in the transformation of the original variables into new variables, the principal components. The principal components are orthogonal, so that the information represented by them are uncorrelated. Thus, this work ________________________________________________________________________________________________________________________________________________ Página - 1 - de 3 52a Reunião Anual da Sociedade Brasileira de Zootecnia Zootecnia: Otimizando Recursos e Potencialidades Belo Horizonte – MG, 19 a 23 de Julho de 2015 aimed to verify the relative importance of the factors that influence pregnancy rate in cows submitted to IATF using the technique of principal components. Material e Methods We analyzed information from the 8683 livestock file assigned for the provision of veterinary services company of 32 farms in 18 municipalities in the north of Minas Gerais in the breeding station from December 2012 to May 2013. The effects of parity cow, body condition score, bull breed bull time of insemination, reproductive categories ovulatory stimulus, on the application of prostaglandin re-use the CIDR inseminator, ovarian structures and dose of ECG on the presence or absence of pregnancy in animals submitted to artificial insemination at fixed time (TAI). Reproductive categories of matrices were nulliparous (heifers), primiparous (one calving), multiparous (more than one calving) and single cows (without suckling calves). The body score was based on the subjective analysis of the nutritional status of animals by means of visual assessment of veterinarians who were beginning the protocol depending on the muscle coverage and fat mass, on a scale from 1.0 to 5.0 (1 = very Thin, 5 = very fat) according Houghton et al. (1990), adapted to intervals of 0.25. The structures assessed by ovarian ultrasound were classified according to the size of the follicle P: 4 to 5 mm, L: 5 to 8 mm, G +, 8 mm in diameter and up CL: Presence of corpus luteum in the ovary. The time of insemination was in the morning and in the afternoon. The reuse of CIDR possible to use 1, 2, and 3 to 4 times. Ovulatory stimuli were calf removal (shang) application of equine chorionic gonadotropin and the implementation of both at once 3 (RB + ECG). We used the Chi-square test at 5% significance (P <0.05) by the PROC FREQ procedure and for the principal component analysis, the PRINCOMP the Statistical Analysis System (SAS, 2000). Results and Discussion The average pregnancy rate was 52.79%. Significant differences in calving order, body condition score, time insemination, bull, bull breed, CIDR reuse, ovulatory stimulus, ovarian structures, ECG dosage, day of applying lutalize and inseminators. The principal component analysis explains the structure of variance and covariance of the original variables, building a smaller set of linear combinations (principal components) that preserve most of the information provided by the variables in question. There are five principal components accounted for 65.01% of the total variance (Table 1). Table 1. Principal components (PC), eigenvalues (λ), percentage of the total variance explained by the principal components (VPC) and accumulated variance (AV). Principal components λ VPC AV CP1 1.98398165 0.1804 0.1804 CP2 1.77301318 0.1612 0.3415 CP3 1.26521954 0.1150 0.4566 CP4 1.08478187 0.0986 0.5552 CP5 1.04383288 0.0949 0.6501 CP6 0.95420195 0.0867 0.7368 CP7 0.78322490 0.0712 0.8080 CP8 0.65832382 0.0598 0.8679 CP9 0.62031451 0.0564 0.9243 CP10 0.50634099 0.0460 0.9703 CP11 0.32676470 0.0297 1.0000 Considering the five principal components (Table 2) accounted for 65% of the variation in pregnancy rate in cows submitted to TAI, the original variables dose of ECG, CIDR use, ovulatory stimulus, bull breed and inseminator make this change as the variables reproductive categories, body score, ovarian structure, day of application of prostaglandin, the IATF time does not make it up. Table 2. Estimate Eigenvectors obtained from the correlation matrix between the variables in cows submitted to TAI in the North of Minas Gerais. Original variables CP1 CP2 CP3 CP4 Reproductive categories -.313057 0.388817 -.239453 0.106842 Body Score 0.386179 -.084929 -.385421 -.167425 Ovarian structure 0.411697 -.419349 0.029733 0.184015 pregnancy rate CP5 -.037137 -.174550 0.038281 ________________________________________________________________________________________________________________________________________________ Página - 2 - de 3 52a Reunião Anual da Sociedade Brasileira de Zootecnia Zootecnia: Otimizando Recursos e Potencialidades Belo Horizonte – MG, 19 a 23 de Julho de 2015 Application prostaglandin day Ovulatory stimulus ECG Dose CIDR use TAI Sire Sire breed inseminator -.211244 0.315827 0.488729 -.132067 0.194303 0.366405 0.068682 0.077300 0.358207 0.244824 0.373650 -.511237 0.251694 0.044626 0.094929 0.046614 0.351367 0.556392 0.151928 0.278133 -.407646 0.045090 0.105292 -.283660 0.340691 -.058072 -.048923 0.087094 0.047435 0.458399 -.718553 0.261861 0.062938 -.137290 -.132016 -.143340 -.359055 0.350730 0.507111 0.629929 Conclusions The variables dose of ECG, Ovarian structure, CIDR use, ovulatory stimulus, bull breed and inseminator are responsible for the variation in pregnancy rate in cows submitted to IATF; The variables reproductive categories, body score, ovarian structure, application day of prostaglandin, the TAI contribute very little to the variability of pregnancy rate. Acknowledgements The authors thank to FAPEMIG for financial support. References BARUSELLI, P. S.; SALES, J. N. S.; SALA, R. V. et al. History, evolution and perspectives of timed artificial insemination programs in Brazil. Animal Reproduction, v. 9, n. 3, p. 139-152, 2012. JOLLIFFE, I.T. Discarding variables in a principal component analysis. II: Real data. Appl. Stat., v.22, p.21-31, 1973. MENEGHETTI, M.; SÁ FILHO, O. J.; PERES, R. et al. Fixed-time artificial insemination with estradiol and progesterone for Bos indicus cows I: Basis for development of protocols. Theriogenology, v. 72, n. 2, p. 179–189, 2009. VASCONCELOS, J. L. M.; VILELA, E. R.; SÁ FILHO, O. G. Remoção temporária de bezerros em dois momentos do protocolo de sincronização da ovulação GnRH-PGF2α-BE em vacas Nelore pós-parto Remoção temporária de bezerros em dois momentos do protocolo de sincronização da ovulação GnRH-PGF2α-BE em vacas Nelore pósparto. Arquivo Brasileiro de Medicina Veterinária e Zootecnia, v. 61, p. 95-103, 2009. SAS Statistical analysis system SAS/STAT users guide release 9.1. ed. Cary, NC, SAS Institute Inc. 2002–2008. ________________________________________________________________________________________________________________________________________________ Página - 3 - de 3
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