ABSTRACT This study was conducted to compare predictive performances of different data-mining algorithms for determining factors influencing the average daily milk yield at dairy cattle enterprises of Ardahan province, located in the Eastern Anatolia region of Turkey. The algorithms employed in the present study were Classification and Regression Tree (CART), Chi-Square Automatic Interaction Detector (CHAID), Exhaustive Chi-Square Automatic Interaction Detector (Exhaustive CHAID), Multivariate Adaptive Regression Splines (MARS), and Multilayer Perceptron (MLP). The MARS algorithm outperformed the other algorithms in the study. Visual results of CART revealed that the culture-breed cows with a lactation length greater than 237.500 days had the highest milk yield (10.64 kg/day). Culture-breed cows calving earlier than the 4th month gave the highest yield of approximately 10 kg/day in the regression tree of CHAID. The Exhaustive CHAID results were almost the same as the structure of the CHAID. The use of MARS may provide an opportunity to detect factors affecting milk production (breed, feed supply, type of milking, mastitis control, cow year group, and lactation length) and their interactions. Moreover, the MARS algorithm may be useful in making an accurate decision about increasing milk yield per cow.

ABSTRACT The aim of this investigation was to determine risk factors affecting production of beekeeping farms in Igdir province of Turkey and to develop strategies in coping with these risks. Research was based on data collected through a questionnaire applied to 85 beekeeping farms registered to Igdir Beekeepers’ Union according to exact counting method. Factor analysis was applied to collected data to identify risk factors and risk management strategies. Factor analysis was conducted under principle component extraction method and VARIMAX rotation. A stepwise regression analysis was used to reveal the relationship between each of four strategy factors and eight risk factors. As risks in procuring labor occur, farmers are more likely to adopt modern agricultural techniques and risk management strategies, such as registering to a cooperative, product insurance, contract farming, and cooperating with public bodies. Unfavorable security conditions and lack of proper bookkeeping in farms are more likely to lead to adoption of careful production and investment planning. As enterprise conditions get better or external conditions get worse, protecting the investment through disease-prevention and better marketing through getting more market information becomes important. Thus, thirteen applicable strategies are determined in the study. As a result, the approach developed in this research could be suggested for beekeepers in selecting necessary strategies against possible risk factors defined here for sustainable honey production and more income.

ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF) in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth) and testicular (testicular length, scrotal length, and scrotal circumference) measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1) and with interaction (MARS_2) terms. The superiority order in the predictive accuracy of the algorithms was found as CART > CHAID ≈ Exhaustive CHAID > MARS_2 > MARS_1 > RBF > MLP. Moreover, all tested algorithms provided a strong predictive accuracy for estimating body weight. However, MARS is the only algorithm that generated a prediction equation for body weight. Therefore, it is hoped that the available results might present a valuable contribution in terms of predicting body weight and describing the relationship between the body weight and body and testicular measurements in revealing breed standards and the conservation of indigenous gene sources for Mengali sheep breeding. Therefore, it will be possible to perform more profitable and productive sheep production. Use of data mining algorithms is useful for revealing the relationship between body weight and testicular traits in describing breed standards of Mengali sheep.