Evaluation of development traits of beef buffalo in Brazil using multivariate analysis

The buffalo population in Brazil increased about 12.9% between 1998 and 2003, to 2.8 million head, evidencing the importance of this species for the country. The objective this work was evaluation of animal growth using multivariate analysis. The data were from 2,944 water buffalo from 10 herds rais...

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Main Authors: N. Flournoy, J.A. DeFreitas, A.M. Jorge, P.B. Ferraz Filho, C.H.M. Malhado, A.A. Ramos, J.C. DeSouza, W.R. Lamberson
Format: Article
Language:English
Published: Taylor & Francis Group 2010-02-01
Series:Italian Journal of Animal Science
Subjects:
Online Access:http://www.aspajournal.it/index.php/ijas/article/view/982
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author N. Flournoy
J.A. DeFreitas
A.M. Jorge
P.B. Ferraz Filho
C.H.M. Malhado
A.A. Ramos
J.C. DeSouza
W.R. Lamberson
author_facet N. Flournoy
J.A. DeFreitas
A.M. Jorge
P.B. Ferraz Filho
C.H.M. Malhado
A.A. Ramos
J.C. DeSouza
W.R. Lamberson
author_sort N. Flournoy
collection DOAJ
description The buffalo population in Brazil increased about 12.9% between 1998 and 2003, to 2.8 million head, evidencing the importance of this species for the country. The objective this work was evaluation of animal growth using multivariate analysis. The data were from 2,944 water buffalo from 10 herds raised in pasture conditions in Brazil. Principal components and genetic distances were estimated using proc PRINCOMP and proc CANDISC in SAS (SAS Inst. Inc. Cary, NC, USA). Variables analyzed were birth weight (BW), age at weaning (AW), weaning weight (WT), weight adjusted to 205 d (W205), total gain between BW and WT (TG), daily gain between BW and WT (DG), weight adjusted to 365 d (W365), total gain between WT and W365 (TG3), daily gain between WT and W365 (TGD3), weight adjusted to 550 d (W550) and weight adjusted to 730 d (W730). Means and standard deviations for each variable were 39.4 ± 3.2 kg, 225.6 ± 38.8 d, 209.4 ± 39.4 kg, 195.4 ± 30.2 kg, 157.4 ± 32.0 kg, 0.77 ± 0.16 kg/d, 282.0 ± 43.5 kg, 73.9 ± 33.9 kg, 0.53 ± 0.21 kg/d, 406.8 ± 67.9 kg, and 468.2 ± 70.6 kg, respectively. The eigenvalues to four first principal components were 5.29, 2.54, 1.66, 1.01, and justify 48%, 23%, 15% and 9%, respectively, with a total cumulative 95%. We created an index using the first principal component which is Y= 0.0552 BW + 0.0438 AW + 0.3142 WT + 0.3549 W205 + 0.3426 TG + 0.3426 DG + 0.4070 W365- 0.1531 TG3 - 0.2059 TGD3 - 0.3833 W550 - 0.3966 W730. This index accounted for 48% the variation in the correlation matrix. This principal component emphasizes early growth of the animal. Estimates the pair-wise squared distances between herds, D2(i|j)= (xi-xj)’ cov-1(xi-xj), using with basis the average of weight of animals, showed the largest distance between herds eight (Murrah: DF) and seven (Murrah: Amazon) and the closest distance between herds one (Mediterranean - RS) and five (Jafarabadi - SP).
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spelling doaj.art-fcf7accc233843678a4d84411661a4522022-12-21T23:58:25ZengTaylor & Francis GroupItalian Journal of Animal Science1594-40771828-051X2010-02-0162s32132410.4081/ijas.2007.s2.321Evaluation of development traits of beef buffalo in Brazil using multivariate analysisN. FlournoyJ.A. DeFreitasA.M. JorgeP.B. Ferraz FilhoC.H.M. MalhadoA.A. RamosJ.C. DeSouzaW.R. LambersonThe buffalo population in Brazil increased about 12.9% between 1998 and 2003, to 2.8 million head, evidencing the importance of this species for the country. The objective this work was evaluation of animal growth using multivariate analysis. The data were from 2,944 water buffalo from 10 herds raised in pasture conditions in Brazil. Principal components and genetic distances were estimated using proc PRINCOMP and proc CANDISC in SAS (SAS Inst. Inc. Cary, NC, USA). Variables analyzed were birth weight (BW), age at weaning (AW), weaning weight (WT), weight adjusted to 205 d (W205), total gain between BW and WT (TG), daily gain between BW and WT (DG), weight adjusted to 365 d (W365), total gain between WT and W365 (TG3), daily gain between WT and W365 (TGD3), weight adjusted to 550 d (W550) and weight adjusted to 730 d (W730). Means and standard deviations for each variable were 39.4 ± 3.2 kg, 225.6 ± 38.8 d, 209.4 ± 39.4 kg, 195.4 ± 30.2 kg, 157.4 ± 32.0 kg, 0.77 ± 0.16 kg/d, 282.0 ± 43.5 kg, 73.9 ± 33.9 kg, 0.53 ± 0.21 kg/d, 406.8 ± 67.9 kg, and 468.2 ± 70.6 kg, respectively. The eigenvalues to four first principal components were 5.29, 2.54, 1.66, 1.01, and justify 48%, 23%, 15% and 9%, respectively, with a total cumulative 95%. We created an index using the first principal component which is Y= 0.0552 BW + 0.0438 AW + 0.3142 WT + 0.3549 W205 + 0.3426 TG + 0.3426 DG + 0.4070 W365- 0.1531 TG3 - 0.2059 TGD3 - 0.3833 W550 - 0.3966 W730. This index accounted for 48% the variation in the correlation matrix. This principal component emphasizes early growth of the animal. Estimates the pair-wise squared distances between herds, D2(i|j)= (xi-xj)’ cov-1(xi-xj), using with basis the average of weight of animals, showed the largest distance between herds eight (Murrah: DF) and seven (Murrah: Amazon) and the closest distance between herds one (Mediterranean - RS) and five (Jafarabadi - SP).http://www.aspajournal.it/index.php/ijas/article/view/982Gain, Murrah, Weight
spellingShingle N. Flournoy
J.A. DeFreitas
A.M. Jorge
P.B. Ferraz Filho
C.H.M. Malhado
A.A. Ramos
J.C. DeSouza
W.R. Lamberson
Evaluation of development traits of beef buffalo in Brazil using multivariate analysis
Italian Journal of Animal Science
Gain, Murrah, Weight
title Evaluation of development traits of beef buffalo in Brazil using multivariate analysis
title_full Evaluation of development traits of beef buffalo in Brazil using multivariate analysis
title_fullStr Evaluation of development traits of beef buffalo in Brazil using multivariate analysis
title_full_unstemmed Evaluation of development traits of beef buffalo in Brazil using multivariate analysis
title_short Evaluation of development traits of beef buffalo in Brazil using multivariate analysis
title_sort evaluation of development traits of beef buffalo in brazil using multivariate analysis
topic Gain, Murrah, Weight
url http://www.aspajournal.it/index.php/ijas/article/view/982
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