The purpose of this study is to compare innovative technology usage levels of dairy farms, supported and non-supported by The Instrument for Pre-accession Assistance-Rural Development (IPARD) program, by scoring their usage level of 10 innovative technologies in their dairy farms. Another purpose of the study is to determine the factors associated with the innovative technology usage levels of dairy farms. The main material of the study is dairy farms supported and not supported by the IPARD program in Konya. Full count sampling method was used when determining the dairy farms supported by IPARD Program and Neyman allocation sampling method was used when determining the dairy farm non-supported by IPARD program. Research data were collected from 50 dairy farms supported by IPARD program and 100 dairy farms non-supported by IPARD program by administering a questionnaire filled during the face-to-face interviews conducted with each individual respondent. As a result of the study, it was determined that the average gross production values and gross profits of dairy farms supported by IPARD program were 4 times higher than those non-supported by IPARD program. While innovative technology usage level of dairy farms non-supported by IPARD program were entirely low level, 90% of dairy farms supported by IPARD program were high level. From the point of view of dairy farm scale, it was determined that innovative technology usage levels were high (69.84%) in dairy farms that had 51 and more milking cows. As a result of chi-square independence test, statistically significant relationship was found between innovative technology usage level of dairy farm and 12 of 13 factors.

This study was aimed at examining gender diversified dairy farming and household level food security status and determinants of dairy cattle benefits in Haramaya district, Oromia, Ethiopia, using cross sectional data collected from randomly selected 120 sample households during year 2016 production season. Descriptive statistics and multiple linear regression models were employed for data analysis. Descriptive statistics stated that of the sample households, 71 households were found to be food secured whereas the remaining 49 household were food unsecured. Comparison of female headed and male headed dairy farming households indicated that 46.7 percent’s of female headed and 12.5 percent’s of male headed households were secured. The logistic regression result showed that female headed dairy farming participation was significantly influenced by education of household head, extension contact, cultivated land area, availability of supplementary feeds and access to market information. The impact estimation result showed that female headed have got increment in farm household’s food security status nearly by 66% than male headed households. The regression estimated coefficients indicated that dairy cattle benefits is significantly influenced by; education, access to vaccination, extension service, market information, cultivated area, milk sold on farm and fodder supplement were significant variables which affect the dairy cattle income in the study area. Therefore, policy makers should give due emphasis to the aforementioned variables to increase dairy farming benefits and improve the livelihood of rural households.

The purposes of this study were to determine the socio-economic characteristics of dairy farmers in Antalya, in Turkey, calculate the gross income, variable costs and gross margin of dairy farms, determine the probability distributions of consequences for alternative decisions to enable dairy farmers as decision makers to make a good and well-informed choice, to determine cross effects of milk prices variations on the productive strategy of dairy farms. The data were gathered via face to face interviews in Korkuteli, Dosemealtı, Elmalı, Manavgat and Serik counties of Antalya province in Turkey. The survey study was conducted with 80 farmers, who were member of Dairy Cow Breaders Union, in the 2011 production period. In this study, on the basis of previous experience, dairy farmers assigned minimum, maximum and most likely values of milk price and yield over the next period of 5 years. Then, triangular and cumulative distributions were defined by using these values. Moreover, Monte Carlo Stochastic Simulation model was developed to obtain distribution of expected gross margin per cow. The model and triangular and cumulative distributions were built in Excel with @Risk add-in software. The relationship of mean risk aversion coefficient, calculated by using negative exponential function, with both average gross margin and gross margin standard deviation values determined for each farm was examined. The results show that the relation between average gross margin and mean risk aversion coefficient was negative and significant at 5% level. But, although the relation between gross margin standard deviation and mean risk aversion coefficient was found to be negative, it was not significant at 5% level.

The present study was conducted to investigate the recent changes in dairy operations of Central Anatolia and to evaluate the milking facilities and machinery capacities of the facilities.The basic objective is to put forward the recent changes through the state supports provided to dairy facilities of the Central Anatolian Provinces. While investigating and evaluating the recent changes, milking parlors, milking machinery and livestock inventories of the facilities were taken into consideration. The relevant data were gathered from the recent records of Turkish Institute of Statistics (TUIK), Agriculture and Rural Development Support Institution (TKDK) and the Ministry of Economy.As a result, in this study while in determining the recent changes in dairy facilities of the Central Anatolian Provinces, the number of milking machinery, milking parlors and livestock inventories were taken into consideration as well as milk yields per animal and number of animals per machine. According to TUIK records for last six years; 384 milking parlors were built, 8877 milking machinery were bought, the increment in the number of livestock inventories and milk yields per animal were taken place as 62.9% and 9.5% respectively. It is thought that supports provided to dairy operations had a great effect on the recent developments. Such supports should also be provided in the future to furnish entire dairy operations with modern machinery and equipment, thus to improve yields and product qualities.

This study aims to determine and analyse farmers’ risk perceptions and risk management strategies in dairy farming. Data were obtained in 2014 (December) and 2015 (February and March) from face-to-face interviews with 96 dairy farmers in Yüregir and Saricam district of Adana province of Turkey. Factor analysis was used in data reduction to identify a small number of factors related to risk sources and risk strategies in this study. Then, multiple regression model was used to evaluate the influence of socio-economic characteristics and communication behaviour on the farmers’ risk perceptions and risk management strategies using factor loadings. The results of this study show that the most important risk source that the farmers' perceive is variability in feed prices and risk management strategy that the farmers' perceive is take precautions to prevent disease. The results of factor analysis show that the risk scale consists of 8 factors explaining 70.24% of total variance. The internal consistency coefficient Cronbach Alfa of the scale is 0.808 and KMO is 0.732. The risk management scale consists of 6 factors explaining 67.78% of total variance. The internal consistency coefficient Cronbach Alfa of the scale is 0.775 and KMO is 0.746. According to the results, perceptions were farmer-specific, a number of socio-economic variables and communication behaviour are found to be related to risk and risk management. To improve risk management strategies is useful for farmers as well and might help them to avoid many risks and reduce losses.