Characterization of the sheep farming system in the brazilian Semiarid from the multivariate perspective.

Abstract: This study aimed to characterize the purebred Morada Nova sheep and crossbred farming systems in Ceará State, Brazil, through multivariate analysis. The study was carried out in the Morada Nova municipality in Ceará. Thirteen representative Morada Nova pure sheep Breeders (MNB) and 48 crossbreds? breeders of Morada Nova with other breeds (CMN) were interviewed. Was used a questionnaire-based including 12 variables: Breeder Age (BA); Herd Size (HS); Breeding System (BS); feed Supplementation (SUPLE); season feed supplementation (winter or summer); Age at Sexual maturity of Ram (ASR); Ram Discard Age (RDA); Age at Sexual maturity of the Ewe (ASE); Ewe Discard Age (EDA); Commercialization (COM); family participation (FAMP); Main Breeder Activity (MBA). Descriptive statistics and variance analysis were performed, followed by Tukey's test for the comparison of the farming systems of the two studied groups. Variables that characterize the farming systems were subjected to factorial analysis, cluster and discriminant analysis. Based on the factorial analysis, the variables SUPLE, SEASON, ASR, EDA, BA, HS and MBA most significantly contributed to the characterization of farming systems in both studied groups. There was obtained a high level of error classification of breeders to their origin group, due to the handling homogeneity between the studied groups. Multivariate analyses are useful for characterizing the farming system, but the results found can be influenced by the nature or characteristics of the data evaluated.

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Bibliographic Details
Main Authors: ARANDAS, J. K. G., ALVES, A. G. C., FACO, O., BELCHIOR, E. B., SHIOTSUKI, L., RIBEIRO, M. N.
Other Authors: JANAINA KELLI GOMES ARANDAS, University Federal Rural de Pernambuco (UFRPE) - Recife, PE, Brazil; ÂNGELO GIUSEPPE CHAVES ALVES, University Federal Rural de Pernambuco (UFRPE) - Recife, PE, Brazil; OLIVARDO FACO, CNPC; ERNANDES BARBOZA BELCHIOR, CNPASA; LUCIANA SHIOTSUKI, CNPASA; MARIA NORMA RIBEIRO, Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq, Brazil.
Format: Artigo de periódico biblioteca
Language:Ingles
English
Published: 2020-07-06
Subjects:Breeding Practices, Local Breed, Livestock System, Livestock breeds, Análise multivariada, Raça local, Raça Morada Nova, Semiárido, Região Nordeste, Brasil, Ovino, Método Estatístico, Cruzamento, Small ruminants, Sheep breeds, Multivariate analysis, Analysis of variance, Crossing,
Online Access:http://www.alice.cnptia.embrapa.br/alice/handle/doc/1123625
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Summary:Abstract: This study aimed to characterize the purebred Morada Nova sheep and crossbred farming systems in Ceará State, Brazil, through multivariate analysis. The study was carried out in the Morada Nova municipality in Ceará. Thirteen representative Morada Nova pure sheep Breeders (MNB) and 48 crossbreds? breeders of Morada Nova with other breeds (CMN) were interviewed. Was used a questionnaire-based including 12 variables: Breeder Age (BA); Herd Size (HS); Breeding System (BS); feed Supplementation (SUPLE); season feed supplementation (winter or summer); Age at Sexual maturity of Ram (ASR); Ram Discard Age (RDA); Age at Sexual maturity of the Ewe (ASE); Ewe Discard Age (EDA); Commercialization (COM); family participation (FAMP); Main Breeder Activity (MBA). Descriptive statistics and variance analysis were performed, followed by Tukey's test for the comparison of the farming systems of the two studied groups. Variables that characterize the farming systems were subjected to factorial analysis, cluster and discriminant analysis. Based on the factorial analysis, the variables SUPLE, SEASON, ASR, EDA, BA, HS and MBA most significantly contributed to the characterization of farming systems in both studied groups. There was obtained a high level of error classification of breeders to their origin group, due to the handling homogeneity between the studied groups. Multivariate analyses are useful for characterizing the farming system, but the results found can be influenced by the nature or characteristics of the data evaluated.