The aim of this study is to determine the purpose of social media usage of farmers in Selçuklu district of Konya province. The sample volume was determined as 80 according to the stratified random sampling method, with a 95% confidence interval and with a 5% margin of error. Factor analysis was conducted to determine the farmers’ social media usage purposes. Factor analysis was conducted on 19 independent variables and 3 independent variables were identified to determine the reasons for using social media. These variables are called professional development, socialization, and communication. The relationship between professional development, socialization, and communication variables and social media platforms was determined by linear regression analysis. For platforms used for socialization purposes, it was found that Facebook was statistically significant at 1% and Instagram was 5%. According to the regression analysis, platforms used for vocational development purposes, it was found that WhatsApp was statistically significant at 1% and YouTube was 5%. In social media, training, extension, projects, and promotions should be more widely supported in order to support the professional training of enterprises. In addition, pieces of training should be provided for enterprises to use social media platforms more effectively.

The study attempted to examine the question whether rural farmers save their income. Rural farmers in Toro Local Government of Bauchi State, Nigeria were used as a case study. The factors that influence saving and investment were also determined. Out of the three districts in the LGA, two villages were purposively selected from each district and twenty farmers were randomly selected to bring the number of villages to six and total number of farmers to one hundred and twenty. This constituted the sample size; they were administered the questionnaires from where data for the study was generated. The data were analyzed using descriptive statistics and multiple regression analysis. The result indicated that contrary to traditional theory of saving where the poor are deemed incapable of saving, the rural farmers do indeed save from their little income. They need to be encouraged in this regard. The regression result showed that age, educational level, farm income, membership of cooperative societies, farming experience and access to credit were significant factors that influence saving. The result also revealed that inadequate income and too many children to carter for were major constraints to saving. To promote saving culture in the area, the capacity of the farmers to save should be enhanced by enabling them adopt birth control, providing them opportunities to work all year round and provision of simple preservation technologies.

A field survey was conducted to study the factor that determines farmers’ decisions to adapt to climate change in Deurali and Agyouli V.D.Cs of Nawalparasi District. Altogether 180 household, 90 from each V.D.C were selected randomly for the study. A logit regression model was employed in the study. However, in order to measure the magnitude of the impact of the explanatory variables on the decision of the farmer to adapt to climate change marginal effects were computed. The study uses a binary dependent variable taking the value 1 if the farmer adapted to climate change and 0 otherwise. A farmer is considered to have adapted to climate change if he/she has employed at least one of the adaptation strategies such as early and late planting, use of drought resistant crops, zero tillage operation, crop diversification, use of mulching and composting of weeds to control water loss and conserving moisture in the field. This current research considers the following as potential factors determining farmers’ decisions to adapt to climate change; economically active members, education of the household head, farm size, annual cash earnings, access to credit, training and extension. Findings reveal that these factors influence farmers’ decisions to adapt to climate change in Nawalparasi District and marginal effects computed showed that per unit increase in these variables increased the probability of practicing different adaptation strategies by 4.3%, 31.4%, 3%, 1.5%, 17%, 66% respectively. The log likelihood was computed to be -43.45. Psuedo. R2 was calculated to be 39%.

This study analysed the economics of plantain production in Northeast Nigeria. The specific objectives of the study were to; describe plantain farmers’ socio-economic characteristics in Northeast Nigeria; identify factors affecting plantain production in the study area, and also ascertain farmers’ resource use efficiency in plantain production. The study adopted a multi-stage sampling technique to collect primary data from 250 plantain farmers selected from 13 communities. In the analysis of the data, descriptive statistics and a stochastic frontier model were used. The finding of the study indicated that most (86.8%) of the respondents were male, having an average age of the respondents was 39.15 years, who are mostly educated (92.8%) and cultivate an average of 2.39 ha of land. The stochastic frontier production function maximum likelihood estimates of the parameters indicated that the production of plantain is determined by farm size, the number of suckers planted, the amount of hired labour used, and family labour. Similarly, the plantain production cost is being influenced by the cost of plantain suckers, labour, and the depreciated cost of land. Furthermore, the study revealed that the farmers were technically and allocatively efficient, although, the maximum technical efficiency was not achieved by farmers. Therefore, it was recommended that agricultural extension agents should be encouraged to reach plantain farmers with the required production technologies to promote production efficiency.

The majority of farm households in Turkey and especially the Eastern Anatolia are still based on low-input semi subsistence agriculture and livestock production. Despite a slow decline in recent years, agriculture and livestock production remains a major employer in Turkey and it is a significant contributor to the country’s gross domestic product, GDP. Whist Turkey is one of the EU candidate countries, is self sufficient in food production and Turkish agriculture is poorly structured inefficient, with farming in the Eastern Anatolia being mainly subsistence farming. Yet, these traditional rural structures combined with poor access to low level of education and low level of off-farm unemployment problem makes the situation more complicated and unsustainable. The best way to promote sustainability, better and higher production of Eastern Anatolian and rural Turkey is to invest in the local people, villages through improved, continuing and effective agricultural and livestock programs in particular. Investment in human capital especially in the rural areas leads to more employment opportunities through entrepreneurship and innovation in organic agriculture and livestock production. A holistic approach to developing and improving supply chains could unlock the potential for sophisticated, state-of-the-art organic agriculture and livestock producers and businesses in the region to become EU and global players. Eastern Anatolian livestock producers and the farmers have the ambitions to take part in future progress because the region is naturally organic not by design but default. It is for sure that present potential of the region has not been fully determined and utilized. EU has greatly benefited from previous enlargements economically, politically and socially. When European Union (EU) and Turkish Government relations considered and accession of Turkey to EU would be the logical consequence of the previous accessions. The screening on chapter 11 (Agriculture and rural development) is one of the important criteria and Turkey is working on to meet these benchmarks.

Trees in upland, semiarid agroecological zones typically require water efficiency due to low rainfall, cold and dry temperatures as in Niğde Province, Central Anatolia, Türkiye. This study quantitatively assessed farmer perception of ecosystem services and production advantage of trees in a semiarid zone. Forty-nine farmers in Niğde Province were surveyed. The survey evaluated two major factors: ecosystem services and production advantage using eleven indicators. The responses were grouped by age, gender, education, district class (rural and urban) and farm settlement (rural and urban) and were analysed by test of association (χ2) at P≤0.05. Most farmers had knowledge of trees in their environment and mainly supported the perspective that trees were important mainly for cultural and provisioning ecosystem services. However, they held the opinion that having trees on their farmer was a production disadvantage in a semiarid agroecological zone. Although there were no gender differences in their perspectives, there were significant difference by age, education, district class and farm settlement. Farmers in this semiarid agroecological zone seemed more interested in trees with evident ecosystem services and production advantage such as improved crop yield, water efficiency, weed and pest management, ease of harvesting as well as reduced overall production cost. By implication, trees with multiple benefits are required if further planting by farmers is to be encouraged for agroecosystem improvement. In addition, tree choice will be based on farmer perception of the benefits of trees for ecosystem services and production advantage and further research to identify and promote trees that benefits the widest range of agroecosystems.

In the current paper, it was aimed to detect the SSR markers that can be used in the prevention of confusion that may occur in breeding or nurseries, and directly genetically separating Uzun and Kırmızı pistachio cultivars from other commercial cultivars. A total of genotypes of 16 Pistacia vera species, one P. atlantica, one P. eurycarpa and two P. terebinthus species were obtained from the farmer's orchard in Nizip district of Gaziantep province for genetic characterization. Genetic diversity and clustering analyzes were performed with UPGMA (Unweighted Pair Group Method with Arithmetic Average) and STRUCTURE 2.3.4 programs using the scored SSR loci. Genetic relationship and population structure of genotypes were defined using common and distinct polymorphic PCR fragments. Cultivar-specific markers to be used in identifying and distinguishing the genetic structure of Uzun and Kırmızı cultivars were carried out in the current research. CUPOhBa2127 marker has the highest allele number (Na=10). In addition, 11 out of 25 SSR markers were explained as cultivar-specific SSRs that can distinguish Uzun and Kırmızı cultivars. These markers can be used directly by breeders and geneticists without any preliminary screnning of the markers. A quite serious providence will be achieved in the cost and time that will occur with the preliminary analysis, and thus, the confusion that may occur in large scale orchard establishments or nurseries will be reduced to pretty low levels with DNA analysis.