regression

Statistical models based on morphometric traits for live body weight estimation in goats

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N.A. Ouchene-Khelifi*, N. Ouchene

Veterinary sciences institute, Saad Dahleb University, Blida 1, road of Soumaa, B.P. 270, Blida 09000, Algeria

(Manuscript received 24 September 2020; accepted for publication 31 March 2021)

Abstract. The objective of this study was to develop statistical models to predict body weight from goat’s body measurements. Data on 1702 goats for circumferences of chest (CG), abdominal circumference (AC) and spiral circumference (SC), height at withers (WH), body length (BL), and body weight (BW) were analysed to study the relationship between linear body measurements and body weight. The present study revealed that in the goats from all breeds studied (Arabia, Makatia, Kabyle, M’zabite, Saanen and Alpine), the weight evolved in the same direction and at the same rate as the linear measurements chosen. The linear measurements were all significantly correlated with animal weight (p<0.001). Results indicated that Arabia goats had the highest WH (71.07 cm) and CG (17.72 cm). The highest measurements were reported in Alpine goats for AC (97.73 cm), BL (78.05 cm), SC (106.29 cm) and BW (41.60 kg). The Kabyle breed were recorded with the lowest values for the WH (64.95 cm), BL (67.58 cm) and BW (29.52 kg). The average live weight was 38.15±10.90 kg with differences according to age, sex and breed (Arabia, Makatia, Kabyle and M’Zabite). Positive and highly significant (p<0.001) correlations were observed between BW and the majority of independent variables. The highest relationship was illustrated between CG with BW (r=0.922). Linear regression analyses were performed to develop the models. The simple regression analysis found all parameters to be significant (p<0.001) (WH, BL, CG, AC and CS) and CG gave more precision on the weight when using a single measurement parameter (R2 varied between 0.950 and 0.967). Therefore, the following formula can be used to estimate the live weight of the animals using only the chest circumference (P=75*CG). The development of these equations would enable producers and researchers to predict the animal body weight and develop strategic plans for the relevant goat herds.

Evaluation of new mathematical models for estimation of single olive leaves area

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M.A. Mhanna*

General Commission for scientific agricultural research, Latakia research center, Ciano research station,

Latakia, Syria

(Manuscript received 7 March 2020; accepted for publication 24 April 2020)

Abstract. The study was conducted on “Khoderi” olive cultivar planted in Jableh Region-Latakia province, Syria in 2017 in order to evaluate some mathematical models adapted for olive single leaf area estimation. Leaf samples were taken from the middle of one-year branches. Actual areas of the leaves were measured using Adobe Photoshop CS5. Leaf dimensions (length and width) were measured accurately. Coefficients of determination were estimated for the relation between leaf dimensions and the actual area. The best coefficient of determination was between the natural logarithm of the product (leaf length × leaf width) and the natural logarithm of leaf area (R2= 0.962). Linear regression equation of the mentioned relation was fitted and evaluated. The accuracy of the new model (A=e0.9509ln LW – 0.2867) was compared to other models commonly used for olive single leaf area estimation. The comparison showed no significant differences between leaf area obtained by the new model and the actual leaf area values (p=0.01), whereas significant differences were found for the other models. The new model showed the lowest Root Mean Square Error (RMSE) and high efficiency in estimating olive leaf area of “Khoderi” cultivar in two different environments; the same results were obtained for olive cultivar “Picholine” the French. We recommend the new model for olive single leaf area estimation.

Application of path coefficient analysis in assessing the relationship between growth-related traits in indigenous Nigerian sheep (Ovis aries) of Niger State, Nigeria

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S. Egena*, D. Tsado, P. Kolo, A. Banjo, M. Adisa-Shehu-Adisa

Department of Animal Production, Federal University of Technology, P.M.B 65, Minna, Niger State, Nigeria

Abstract. Indigenous Nigerian sheep raised under extensive management were evaluated with the aim of assessing variability among body weight and body measurement traits thereby deducing components that best describe the relationship using path coefficient analysis. The parameters measured were body weight (BW), body length (BL), head length (HL), head width (HW), height at withers (HAW), chest depth (CD), chest girth (CG) and shin circumference (SC). Pair wise correlation between body weight and body measurements were positive and significant (r = 0.475 – 0.655 in males, 0.262 – 0.449 in females, and 0.336 – 0.509 in the combined population, P<0.01). Path analysis showed that shin circumference and chest depth had the greatest direct effect on body weight in male, female and the combined population (path coefficient = 0.250, 0.252 and 0.250, respectively) while the least direct effect was observed for head width (in male and female with path coefficient = 0.007 and -0.017, respectively), and height at withers in the combined population (path coefficient = -0.020). Percentage direct contribution to body weight was 6.25, 6.35 and 6.25% from shin circumference (male), chest depth (in female and the combined population respectively). The optimum linear regression models with coefficient of determination (R2) value of 0.45, 0.31 and 0.37 included forecast indices such as chest depth and shin circumference in males, body length, head length and chest depth in females and the combined population, respectively.

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