This research was conducted to determine the effects of different seaweed doses on yield and nutritional values of hydroponic wheatgrass (Triticum aestivum L.) juice in the climatization chamber of Karabuk University, Eskipazar Vocational School, Department of Crop and Animal Production between the dates of 15.01.2015 and 15.06.2015. In the research, four different seaweed doses (Control; 0, D1; 150, D2; 300, D3; 450 and D4; 600 ppm) and control were applied to irrigation water and their effects on the content of biomass rate, biomass and grass yield, grass juice yield and pH, plant height and root length, biomass and grass dry matter rate, grass juice energy and macronutrient values (protein, carbohydrate, fat, dietary fiber and ash) were analysed. According to the results, while the highest biomass and grass yield, plant height values were obtained from D1, D2, D3 and D4 treatments, the highest grass juice yield and root length were obtained from D3 treatment. The highest pH, grass dry matter content was obtained from control treatment. Seaweed dose treatments were not had influence on grass juice energy values. However, the rise in the grass juice yield was caused a rise in the total energy values in the unit area. D3 treatments can be recommendable to achieve the highest grass juice yield.

Collected blue-green algae (cyanobacteria) from freshwater sites throughout Tokat province and its outlying areas were isolated in laboratory environment and their morphological systematics were determined and also their species identifications were studied by molecular methods. Seven different species of blue-green algae collected from seven different sites were isolated by purifying in cultures in laboratory environment. DNA extractions were made from isolated cells and extracted DNAs were amplified by using PCR. Cyanobacteria specific primers were used to amplify 16S rRNA and phycocyanine gene regions using PCR. Phylogenetic identification of species were conducted by evaluation of obtained sequence analysis data by using computer software. According to species identification by sequence analysis, it was seen that molecular data supports morphological systematics.

Although the intensification of agricultural production is the reason for feeding of increasing human population the demand for organic or ecological products is increasing in parallel with the social consciousness in recent years. Hair goat breeding is made in a large part of Turkey that is suitable or may become suitable for organic production system with a few arrangements. In this study, Hair goat breeding was evaluated together with the Regulation on the Principles and Implementation of Organic Agriculture. The study is important in terms of ensuring sustainability of hair goats under the threat of crossbreeding by assessing it within organic production.

Discretization is a data pre-processing task transforming continuous variables into discrete ones in order to apply some data mining algorithms such as association rules extraction and classification trees. In this study we empirically compared the performances of equal width intervals (EWI), equal frequency intervals (EFI) and K-means clustering (KMC) methods to discretize 14 continuous variables in a chicken egg quality traits dataset. We revealed that these unsupervised discretization methods can decrease the training error rates and increase the test accuracies of the classification tree models. By comparing the training errors and test accuracies of the model applied with C5.0 classification tree algorithm we also found that EWI, EFI and KMC methods produced the more or less similar results. Among the rules used for estimating the number of intervals, the Rice rule gave the best result with EWI but not with EFI. It was also found that Freedman-Diaconis rule with EFI and Doane rule with EFI and EWI slightly performed better than the other rules.

The aim of this study was to investigate the relationship between the amount of cow milk production and its price in Turkey in the period between 1985-2015.The Koyck model that is one of the distributed lag models was used to analyse of these data. The production of cow milk was considered as dependent variable and the price series consisting of cow milk prices and lagged price series are considered as explanatory variable in the model. According to the results of Koyck model, it was determined that the production of cow milk was affected by the prices of maximum one year retrospectively and the time required to dramatically affect to production of cow milk of the change taken place in prices of cow milk was 2.9 years. Furthermore, the increase of 1 TL in price of cow milk decreases the production of cow milk by 183372.4 tonnes. On the other hand, the increase of 1 TL in prices in the previous period decreases the production of cow milk by 137345.9 tonnes. Based on these data, it can be said that the price of cow milk composed in the free market conditions is rather efficient in determination to production amount. In conclusion, economic measures such as making of production planning, constituting of efficient marketing opportunities, price policies and giving a place to stable production can be taken against to fluctutations in the price increases.

The aim of this study is to determine the factors that affect the development of bureaucratic knowledge and skills of farmers in rural areas. To achieve this aim, a questionnaire was administered face-to-face to 110 farmers. The survey was conducted in the central villages of Tokat Province in 2013. Exploratory factor analysis and confirmatory factor analysis were used to determine the factors that affect the development of farmers’ knowledge and skills regarding bureaucratic procedures. The exploratory factor analysis generated a structure with 4 factors and 10 variables. These factors which explained 76.063% of the total variance, and their reliability coefficients were determined as cooperation tendency (0.803), bureaucratic procedure experience (0.701), level of benefit from government support (0.900) and immediate environment communication (0.601). According to the results of the confirmatory factor analysis, the fit index values were 0.938 for GFI; 0.934 for CFI and 0.913 for NFI. The fact that the RMSEA and CMIN/DF coefficients were also consistent and significant indicates that the results fit the theory. The fact that the intended goodness-of-fit index values of these coefficients were significant also indicates that the results fit the theory. Thus, the factors that affect the bureaucratic knowledge and skills of farmers in the rural areas of Tokat Province were found to be: getting involved in agricultural organizations, the experience of performing formal procedures in public offices, attempts to benefit from agricultural support and immediate environment communication.

This study was conducted to determine the response of 19 bread wheat varieties to natural infection of leaf diseases under ecological conditions of Düzce in the Western Black Sea Region. The trial was established in accordance with randomized block with four replications and the seeds were planted on 17.11.2015. The wheat varities were observed for the associated diseases including septoria leaf spot disease (caused by Septoria tritici during milking stage), yellow rust disease (caused by Puccinia striiformis at the end of the flowering period), brown rust disease (caused by Puccinia recondita at the beginning of milking stage). The disease severity were assessed in the field conditions according to natural contamination. According to determined diseases severity, the most sensitive variety against septoria leaf spot disease was “Bereket” with 60%, while the most tolerant variety was “Aslı” with 14%. The most sensitive variety against yellow rust disease was “Tekirdağ” with 45.4%, while the most tolerant variety was “Midas” with 0.6%. The most sensitive variety against brown rust disease was “Tahirova” with 22%, while the most tolerant variety was “Midas” with 0.2%. The results indicated that promising wheat varieties for future breeding studies were: Aldane, Aslı, Konya 2002, Köprü, Masaccio and Tosunbey (against septoria leaf spot disease), Aslı, Esperia, Kate A1, Karasunya Odeska, Masaccio and Midas (against yellow rust disease), Aldane, Aslı, Bereket, Köprü, Masaccio, Midas and Tekirdağ (against brown rust disease).

Sage (Salvia spp.) is the most important and largest genus of the Lamiaceae family, and the popularity among medical plants is increasing. Sage plant is widely used in pharmaceutical, food and spice industries and as tea by many people. The fact that the plant may be marketed after being collected uncontrollably from the nature threatens its future. Therefore, it is necessary to put these species under protection and to start breeding projects as well to do genetic characterization of them. For this purpose, in the study, 11 different sage species from the Eastern Mediterranean region were collected and genetic differences among species were determined using SRAP (Sequence dependent replicated polymorphism) markers. As the result of our experiments, average polymorphism content, allele number and polymorphism information content (PIC) of the species were calculated as 90.91%, 4.2 and 0.91, respectively. The PIC values ranged from 0.04 to 0.99. While the average genetic difference among species was determined as 43.15%, the highest genetic difference, which was between Salvia aucheri spp. aucheri and Salvia aramiensis, was found to be 61.46%. The least genetic difference, on the other hand, was detected between Salvia tomentosa and Salvia hypergeia species with 22.62% similarity. Additionally, according to the observations made through the study, the SRAP markers we used were thought to be reliable for the genetic characterization of sage species. In breeding programs where interspecies dissimilarities are considered, selecting parental species with high genetic differences will increase the success.

Advancement in agricultural technologies is seen to result in the shift in production functions. The study was conducted to establish the impact of the improved rice variety on productivity in the Ejura-Sekyedumase and Atebubu-Amantin Municipalities of Ghana. The study was based on the survey of 208 rice farmers using a three-stage stratified sampling method. The study used a structured questionnaire to collect input-output data from the rice farmers. Data were analysed using the Cobb-Douglas production function. The study found that the technical change associated with the introduction of the improved rice variety was of the non-neutral type. Further, the adoption of the improved rice variety has increased rice productivity by about 46% for the adopters. The main determinants of productivity for the adopters were seed, land, fertiliser, herbicide, and education. Productivity among the non-adopters was positively influenced by seed, land, herbicide, and fertiliser. The study concluded that the improved rice variety has superior yield advantage. The study recommends for the simultaneous promotion of improved rice varieties and their recommended inputs to increase rice productivity.