The ISSR markers were found to be promising for assessing the genetic diversity in buffalo populations. Potential genetic parameters such as PIC, R(p), R(p), H and I were effectively used in this study.
The objective of this study was to determine the fitness of Quadratic, Cubic, Gompertz and Logistic functions to the growth curves of Konya Merino lambs obtained by using monthly records of live weight from birth to 480 days of age. The models were evaluated according to determination coefficient (R 2 ), mean square prediction errors (MSPE) and Durbin Watson (DW) statistics. The R 2 values of the models ranged from 0.96 to 0.99 for females and from 0.96 to 0.99 for males. The Cubic model gave the best R 2 value of 0.99 in females, while the Logistic model gave the lowest R 2 value of 0.96 in females. The results indicated that the Quadratic and Gompertz models showed the best fit to growth of Konya Merino ewe lambs by having higher R 2 values, lower MSPE and non autocorrelation. By using these models live weights at later ages could be predicted from early partial live weight data. Further studies should be carried out on growth curve characteristics at later ages including adult age.________________________________________________________________________________ Increase in live weight or dimension against age has been described as growth. Changes in live weight or dimension for a period of time are explained by the growth curves. Animal breeders are interested in the genotypic and phenotypic relationships during all phases of growth. Knowledge of genotypic and phenotypic relationships among live weights, degree of maturity and growth rate during all phases of growth is necessary to formulate breeding programmes to improve lifetime efficiency (Smith et al., 1976). Growth curves are also used for investigating optimum feeding programmes, determining optimum slaughtering age and the effects of selection on curve parameters and on live weight at a certain age (Blasco & Gomes, 1993).The shape of growth curves has been reported to vary according to the species of animal, the environment and the trait (Efe, 1990;Akbaş et al., 1999;Topal et al., 2004). Moore (1985) studied the growth curves of domesticated mammals. He reported that linear and cubic models fitted the data of cattle, pigs, sheep, goats, rabbits, mice and rats sufficiently, and supplied a standard growth curve for these mammals. Akbaş et al. (1999) studied live weight changes of Kıvırcık and Dağlıç male lambs from birth to 420 days using growth curve models. They reported that the simple linear model gave the best fit for Dağlıç and the quadratic model for Kıvırcık lambs. Also, nonlinear Brody, Negative exponentials, Gompertz, Logistic and Bertalanffy models fitted the body weight data of Kıvırcık and Dağlıç male lambs well (models' R 2 values were above 0.98). Esenbuğa et al. (2000) reported that R 2 values for the Brody model in Morkaraman, Awassi and Tushin lambs were 0.99, 0.99 and 0.98, respectively and the fitness of this model was found to be sufficient. The Gompertz function was found to be appropriate for describing the growth curve of Suffolk sheep (Lewis et al., 2002). Growth from birth to 360 days of age in ewe lambs of the Morkaraman and Awas...
Keskin, I., Dag, B. and Sariyel, V. 2009. Fitness of four different mathematical models to the lactation curve of Brown Swiss cows in Konya Province of Turkey. Can. J. Anim. Sci. 89: 195Á199. The aim of this study was to investigate the fitness of Incomplete Gamma (WD), Exponential (WIL), Mixed Log (MIL) and Polynomial Regression (AS) models to the lactation curve of Brown Swiss Cows. Data were collected from 143 Brown Swiss cows raised on the Altinova State Farm in Konya Province, Turkey. Milk yield was recorded monthly, and milk records were started at the third week of lactation (mean 0 16.9 day, SD00.7). Total milk yields estimated by the four models were very close to real total milk yield. The models were found to be adequate for estimation of milk yield. The MIL model underestimated the peak yield significantly. The differences between peak yields of the models and real peak yields were not significant and ranged from 27.70 to 29.01 L. All models forecasted peak time earlier than real peak time. The differences for the persistency values of the four models were significant. The AS model's persistency value was nearly equal to the real persistency value (77.56 vs. 77.59%). R 2 values of the models changed from 86.05 to 97.95%. The AS model gave the best R 2 and the least MSPE values. Consequently, the AS model showed the best fit to the lactation data of Brown Swiss cows and allowed a suitable definition of the lactation curve.Key words: Brown Swiss, cows, lactation curve, milk yield, mathematical model Keskin, I., Dag, B. et Sariyel, V. 2009. Ajustement de quatre mode`les mathe´matiques a`la courbe de lactation des Suisses brunes dans la province turque de Konya. Can. J. Anim. Sci. 89: 195Á199. L'e´tude devait e´tablir dans quelle mesure les mode`les Gamma incomplet (WD), Exponentiel (WIL), Log mixte (MIL) et Re´gression polynomiale (AS) refle`tent la courbe de lactation des vaches Suisses brunes. Les donne´es ont e´te´recueillies sur 143 vaches e´leve´es dans la ferme d'É tat d'Altinova, dans la province de Konya, en Turquie. Le rendement laitier a e´te´enregistre´mensuellement a`partir de la troisie`me semaine de lactation (moyenne 016,9 jours, É .-T. 00,7). Le rendement laitier total estime´par les quatre mode`les se rapproche beaucoup du rendement re´el. Les mode`les conviennent a`l'estimation du rendement laitier. Ne´anmoins, le mode`le MIL sous-estime sensiblement le rendement maximal. L'e´cart entre le rendement maximal indique´par le mode`le et le rendement maximal re´el n'est pas significatif et varie de 27,70 a`29,01 l. Tous les mode`les anticipent le moment oul e rendement maximal sera atteint, comparativement a`la re´alite´. La persistance varie sensiblement d'un mode`le a`l'autre. Celle du mode`le AS e´quivaut presque a`la persistance re´elle (77,56 c. 77,59 %). La valeur R 2 des mode`les varie de 86,05 % a`97,95 %. Le mode`le AS donne la meilleure valeur R 2 et la plus faible erreur de pre´diction au carre´. On en de´duit que ce mode`le est celui qui refle`te le mieux les donne´es de lactati...
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