This study was carried out to determine the technical and economic efficiency levels of laying hen farms and factors affecting the efficiency scores. For this purpose, a personal interview was carried out. Technical and economic data of 39 laying hen farms consisting their inputs and outputs over the period 2013-2015 was formed the material of this study. Efficiency levels were estimated by using Data Envelopment Analysis (DEA).Mean technical efficiency score of the enterprises were determined as 98.6%. Also 48.7% of the enterprises were determined fully technical efficient. On the other hand, mean economic efficiency of the enterprises was determined as 88.8%, while only 17.9% of the enterprises were fully economic efficient. In order to determine the factors affecting efficiency scores, Tobit regression analysis was performed. According to the analysis results, chick mortality rate, hen mortality rate and feed conversion ratio had negative effects on technical efficiency scores, while education level of the farmer and capacity utilization ratio had positive effects. Egg cost, chick mortality rate, feed conversion rate and production length had negative effect while egg yield had positive effect on economic efficiency. As a result, enterprises would increase their technical and economic efficiency scores by decreasing the mortality rate, feed conversion rate, production length. Furthermore, increasing capacity utilization ratio, education level of the owner and egg yield/ hen would help to increase efficiency levels of the farms.

This study aimed to determine the heterogeneity that exists in water buffalo husbandry systems in Marmara Region, Turkey. A questionnaire containing a total of 60 indicators was submitted to 52 farmers. A Principal Component Analysis was performed to reduce original variables into a simplified and latent structure, which was characterized by six orthogonal components: milk productivity, economic efficiency, roughage management, dual-purpose farming, concentrate supply, and fodder production. An ANOVA model was applied to the six components to investigate the effects of the province, investment levels, grazing type, milk production, and profitability. Differences in milk productivity, roughage management, concentrate supply, and fodder management were significant according to the province and grazing type, which indicated a difference in intensification levels among the cities. Economic efficiency and dual-purpose farming differed significantly for milk production levels as well as milk productivity, and economic efficiency differed for profitability levels. We found a tendency regarding the impact of roughage management on profitability. The results conclude that profitability was associated with improving the milking traits of buffaloes and roughage management of the farms.

In the present study, the effect of consumers' perception levels (product, price, and benefit perception), consciousness levels (health, environment, and animal welfare), and sociodemographic characteristics on the purchase decision of organic chicken meat were examined. Logistic regression analysis was used to determine the relationship between the purchase decision of organic chicken meat and the perception level, consciousness level, sociodemographic characteristics. As a result of the analyses made, it has been determined that organic chicken meat naturalness perception, value-quality perception, health control awareness, awareness of animal life quality, and income level havestatistically significant effects on the probability of purchasing organic chicken meat.In conclusion, to raise consumer awareness the issues that need to be emphasized are that organic meat is natural, reliable, healthy and suitable for animal welfare.

Biosecurity (BS) is a multidimensional preventive medicine approach that has health, technical, and financial aspects. The purpose of this study was to determine the differences of the BS scores belonging to the livestock enterprises depending on the geographical region and breeding types and to predict the socioeconomic factors having an impact over the BS level. The study was conducted with 517 breeders who live in 7 different regions of Turkey. The results have revealed that the enterprises performing "beef cattle fattening and dairy cattle breeding together" have higher BS scores than the enterprises in the other breeding category (P < 0.01). The differences between the technical and financial scores according to geographical regions were statistically significant (P < 0.01). The regions categorized as "west" have the highest score and "south" have the lowest score. It was determined that as the "educational level of the breeder" and "enterprise scale" increased, the BS score significantly went up. The regression model was found significant as a whole (P < 0.01) and the independent variables explained the variation in the technical and financial BS scores to be 14.6% and 12.7%, respectively. Dissemination of education/training practices and increasing enterprise scales will positively affect the level of BS in the sector.