Zoometric measures and their utilization in prediction of live weight of local goats in southern México
Objectives of this study were: (a) to compare live weight (LW) and zoometric measures (ZM) of local goats in two locations, (b) to fit the best regression equation for goat LW prediction using ZM. LW, body length (BL), trunk length (TL), withers height (WH), hearth girth (HG), rump width (RW), rump...
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Veröffentlicht in: | SpringerPlus 2015-11, Vol.4 (1), p.695-695, Article 695 |
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Zusammenfassung: | Objectives of this study were: (a) to compare live weight (LW) and zoometric measures (ZM) of local goats in two locations, (b) to fit the best regression equation for goat LW prediction using ZM. LW, body length (BL), trunk length (TL), withers height (WH), hearth girth (HG), rump width (RW), rump length (RL), head length (HL), head width (HW), and ear length (EL) were measured in 318 Local does in Amatepec and Tejupilco, State of Mexico. Statistical methods included student’s “t” tests for comparison of means, and correlation, principal components (PC), and multiple linear regression analyses. To evaluate the goodness of fit for LW prediction models the R
2
value was used as a criterion. Differences (
P
≤ 0.05) were found between does of Amatepec and Tejupilco in LW, BL, TL, HG, RL, HL, HW, and EL. In Amatepec, LW was correlated with HG, BL, and HW (
P
≤ 0.01), whereas in Tejupilco LW was correlated with HG, BL, TL, and HW (
P
≤ 0.01). From the Amatepec measures 5 PC were extracted, and which in a multiple regression analysis explained 83.3 % of the total variance, whereas from Tejupilco 4 PC were extracted, and which in a multiple regression analysis explained 82.4 % of the total variance. The best regression model to predict doe LW in Amatepec included TL, HG, RW, and HW, whereas for Tejupilco the best model included BL, HG, HW, and EL. It is concluded that: (1) Amatepec does surpass those of Tejupilco in LW and most ZM, (2) there are reliable ZM for predicting LW of local does in both locations, HG, and HW being common measures for both populations. |
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ISSN: | 2193-1801 2193-1801 |
DOI: | 10.1186/s40064-015-1424-6 |