Yazar "Mikail, N." seçeneğine göre listele

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    A Bayesian approach for describing the growth of Chukar partridges
    (European Poultry Science, 2019) İqbal, F.; Eyduran, E.; Mikail, N.; Sarıyel, V.; Huma, Z.E.; Aygün, A.; Keskin, İ.
    In this article, a Bayesian approach was employed for estimating the body growth of Chukar partridge (Alectoris chukar). Nonlinear growth models commonly used to estimate the growth curve of birds were fitted to weight-age data and estimates of model parameters and their credible intervals were obtained via a formal Bayesian framework. More specifically, the Gompertz, Brody, Logistic and von Bertalanffy growth models were fitted to weekly body weight data of 108 female and 72 male partridge chicks from hatch to 20 weeks of age. Deviance Information Criteria (DIC) and the coefficient of determination (R2) were employed as the goodness of fit for comparing the fitted models. The DIC and R2 values of the models ranged from 172.9 to 204.2 and 0.9765 to 0.9913, respectively. The von Bertalanffy model was found to provide the best fit in terms of lower DIC and higher R2 values, followed by the Gompertz model for both male and female partridge data. The Bayesian approach was found to be adequate for fitting complex nonlinear functions to weight-age data of Chukar partridges.
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    FUZZY LOGIC APPLICATIONS IN HORTICULTURE AND A SAMPLE DESIGN FOR JUICE VOLUME PREDICTION IN POMEGRANATE (PUNICA GRANATUM L.)
    (Corvinus Univ Budapest, 2019) Pakyurek, M.; Aydin, Y.; Mikail, N.
    Fuzzy expert systems search for a solution based on the expertise of people who are experts in a particular field. This could be described as a kind of advisory system edited on computer. The use of natural language on the basis of fuzzy logic and easier understanding of system logs provide this technique to resolve many daily and current problems. In this study, a sample expert system to estimate juice volume in pomegranate was designed, using the fuzzy logic method, which closest to the logic of the human mindset Recording of data was performed on the private farm of the province of Siirt, Turkey. The Fuzzy Logic Interface of MATLAB Program was used in the designing phase of the system. The evaluation of the model was carried out according to coefficient of determination and coefficient of correlation. The model revealed R-2 = 80% coefficient of determination, and r = 0.89 coefficient of correlation. With more informative parameters, the error rate can be decreased. Fuzzy logic seems one of the useful tools with prediction purposes in horticulture.
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    MOST PROBABLE PRODUCING ABILITY AS A WITHIN-HERD MANAGEMENT AND CULLING TOOL
    (Pakistan Agricultural Scientists Forum, 2019) Mikail, N.; Cue, R.; Bakir, G.
    The objectives of this study were to examine the effects of management and environmental effects on milk yield (factors such as herd, year of calving, parity and age at calving), total and 305-dayand to examine the magnitude of the variability amongst cows. Data were obtained from three state farms. Data set consisted of records from 1004 Holstein-Friesian and 6690Brown Swiss cows. The average total milk yield, days in milk and 305 day milk yield were 5760 kg, 316 days and 5420 kg, respectively. Repeatability of total milk yield, 305 day milk yield and most probable producing ability of each cow were calculated. Repeatability of total and 305 day milk yield was estimated to be 0.31. The results of this study suggest positive trends for lactation milk yield and the significant repeatability shows that it is possible to rank cows, on a within-herd basis, on the basis of their Most Probable Producing Ability, and hence use this as a phenotypic selection and culling criteria for herd management.