Identification of risk factors affecting production of beekeeping farms and development of risk management strategies: A new approach

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

Determination of factors affecting dairy cattle: a case study of Ardahan province using data mining algorithms

WOS: 000501503600001This 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

IDENTIFICATION OF POTATO PURCHASING BEHAVIORS AND PREFERENCES OF CONSUMERS BY MEANS OF ROBUST FACTOR ANALYSIS

WOS: 000407960800027The present questionnaire study was conducted to establish potato purchasing preferences of 385 consumers selected randomly from Igdir, Turkey. All the items ranging from 1 to 11 on the basis of an ordinal 11 point scale data on fresh potato and its products were collected from the consumers. Robust Unweighted Least Squares (RULS) extraction method was used based on promin rotation method for obtaining better solutions in the ordinal data set. Polychoric correlation matrix was used instead of Pearson correlation matrix in the violation of the basic assumption on normal distribution of the ordinal items due to the fact that it is evidence that null hypothesis of multivariate asymmetric kurtosis was rejected (P= 0.000). Four new factors were extracted from all the items on both fresh potato and its products through 'Factor 'software program, which gives more comprehensive and understandable outputs. The rotated factor loadings for potato products were clustered into four factors: content (Factor 1), value of nutrient and calorie (Factor 2), additives and price (Factor 3) and situation of package and health (Factor 4), respectively. The rotated factor loadings for fresh potato preferences of the consumers were also assigned to four factors: source (Factor 1), price and color (Factor 2), tubers structure (Factor 3) and tubers properties (Factor 4), respectively. The current results revealed that an application of EFA factor analysis on the basis of ULS extraction method, promin rotation method and polychoric correlations as a dispersion matrix was more effective when compared with the traditional EFA applications for the ordinal data. Besides, potato producers, sellers and entrepreneurs who desire to develop new marketing strategies might be recommended to take into account four factors that can affect purchasing preferences of the consumers on fresh potato and its product

Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan

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

Comparison of the Predictive Capabilities of Several Data Mining Algorithms and Multiple Linear Regression in the Prediction of Body Weight by Means of Body Measurements in the Indigenous Beetal Goat of Pakistan

WOS: 000398881500036The main goal of this study was to establish the algorithm with the best predictive capability among classification and regression trees (CART), chi-square automatic interaction detector (CHAID), radial basis function (RBF) networks and multilayer perceptrons with one (MLP1) and two (MLP2) hidden layers in body weight (BW) prediction from selected body measurements in the indigenous Beetal goat of Pakistan Moreover, the results obtained with the data mining algorithms were compared with multiple linear regression (MR). A total of 205 BW records including one categorical (sex) and six contmuous (head girth above eyes, neck length, diagonal body length, belly sprung, shank circumference and rump height) predictors were utilized The Pearson correlation coefficient between the actual and predicted BW (r) and root-mean-square error (RMSE) were used as goodness-of-fit criteria, among others A 10-fold-cross validation was applied to tram and test CART, CHAID and ANN and to estimate MR coefficients. The most significant BW predictors were sex, rump height, shank circumference and head girth The r value ranged from 0.82 (MLPI) to 0 86 (RBF and MR) The lowest RMSE (3.94 kg) was found for RBF and the highest one (4.49 kg) for MLPI In general, the applied algorithms quite accurately predicted BW of Beetal goats, which may be helpful in making decisions upon standards, favourable drug doses and required feed amount for animals. The ascertainment of the body measurements associated with BW using data mining algorithms can be considered as an indirect selection criterion for future goat breeding studies.Polish Ministry of Science and Higher EducationMinistry of Science and Higher Education, Poland [517-01-028-3962/17]The publication of this article was partially supported by the Polish Ministry of Science and Higher Education grant No. 517-01-028-3962/17

Effect of Carrot (Daucus carota) Leaf Powder on External and Internal Egg Characteristics of Hy-Line White Laying Hens

WOS: 000398881500018This current work was conducted to determine the effect of dried carrot (Dawns carota) leaf powder at different amounts on some external and internal egg characteristics of Hy-line white laying hens as a commercial type through two-way ANOVA, to estimate the Pearson correlation between pairs of egg external and internal characteristics and to predict each of egg internal charactenstics from egg external charactenstics, treatment and week through CHAID analysis A total number of eighty, 56 weeks old Hy-Line White laying hens (commercial type) of nearly similar initial body weight (1360.6 +/- 14.25 g) were assigned into 5 experimental groups (control group and 4 treatment groups) each including 16 and maintained individually in cages of 35 x 40 x 45 cm The strongest correlations were found for egg weight-egg width (r=0 910, P<0.01), haugh unit-albumen index (r=0 876, P<0 01), egg weight-egg height (r=0 799, P<0.01), and egg shape index-egg height (r=0 693, P<0.01). ANOVA results revealed that treatment factor influenced only egg height among all the egg characteristics (P<0.05). The effect of treatment by week interaction on all the characteristics was non-significant. The significant differences in other egg characteristics between weeks were recorded except for egg shape index and egg height (P<0.05). Very strongly Pearson coefficient of 0.876 was estimated in egg shape index between predicted and actual values (P<0.01) m the CHAID analysis in comparison with other egg mtemal characteristics. The Nodes numbered 3, 4, 5, 8, 9 and 12 with the egg shape index of 72-76 m the CHAID analysis illustrated suitable eggs for egg cartons and shipment in poultry industry As a result, it was determined m the study that CHAID analysis may be used to better prove relationship mechanism between egg quality characteristics which are of great importance for higher price and more income of fertile and table eggs

Influence of wine tasting on the color of teeth amongst professional wine tasters of gironde, France: a pilot study

The appearance of the smile and in particular the color of the teeth is of great cosmetic importance for many people. Because of the coloring substances that make up wine, wine tasters are subject by their profession to a high risk of having discolored teeth. The main objective of this study was therefore to observe the association between the color of the maxillary central incisors and the profession of wine tasters. To do this, we conducted a cross-sectional study in the Gironde region (France) by comparing the color of the buccal face of the maxillary central incisors of professional wine tasters and controls. The teeth color was measured using a spectrophotometer and the delta E (difference between two colors) was noted by comparison with a common reference. On a population of 61 people (31 wine tasters and 30 controls), our results showed no significant difference in the color of the teeth studied. However, a trend towards the impact of age on tooth color was observed. Within the limits of this study, it does not appear that the color of the buccal face of the maxillary incisors is significantly related to professional wine tasting