On biometrical aspects of the cephalic anatomy of Xisqueta sheep (Catalunya, Spain)

This study, based on a 48 Xisqueta skull samples, gives a statistical insight of the skull shape in this breed. Thirty eight measurements and eight indexes were recorded. The variance structure was done using a Principal Component Analysis (PCA). This was possible sequel to the application and permi...

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Detalles Bibliográficos
Autores: Parés Casanova, Pere-Miquel, Sarma, Kamal, Jordana i Vidal, Jordi
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2010
País:España
Institución:Universitat de Lleida (UdL)
Repositorio:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/47488
Acceso en línea:https://doi.org/10.4067/S0717-95022010000200001
http://hdl.handle.net/10459.1/47488
Access Level:acceso abierto
Palabra clave:Anatomy
Craneometry
Osteometry
Skull
Anatomía
Craneometría
Osteometría
Cráneo
Pallaresa (Raça ovina)
Descripción
Sumario:This study, based on a 48 Xisqueta skull samples, gives a statistical insight of the skull shape in this breed. Thirty eight measurements and eight indexes were recorded. The variance structure was done using a Principal Component Analysis (PCA). This was possible sequel to the application and permission of the covariance matrix. The mean length of the skulls was found to be 265.51± 22.24 mm, with the width and cephalic index to the magnitude of 117.2 ± 6.89 mm and 44.69 ± 4.29 mm, respectively. The viscerocranium length was 143.07± 9.74 mm thus indicating a similar portion with the neurocranium part of the skull (137.17 ± 6.25 mm). The orbit was slightly almond shaped. Variability was generally high within parameters but parameter variation was less in regard to basal surface length parameters than the others. The results from Principal Component Analysis indicated that skull variance was concentrated on the first two components. The first principal component explained 99.21 % of the generalized variance in skull parameters and gave special emphasis to viscerocranium. The second principal component may be called the neurocranial component. The first and the second principal components explained 99.77% of the observed variance. The third principal component was related with foramen magnum and orbital parameters.