Background The study was focused on the adoption and intensity of adoption of artificial insemination (AI) Technology in Saesie-tsaedaemba District of Tigray Region, Ethiopia. AI is one of the most important and valuable dairy technology that has been used for genetic improvement for several years in the study area. However, there was little empirical information about major factors affecting adoption decision and intensity of AI in the study area. The purpose of this study was to evaluate the status of AI technology adoption and its intensity and to identify major factors influencing the adoption and intensity of use of AI technology. Methods A multistage sampling technique was applied to select study sites and sample households. A structured interview was used to collect data from a total of 204 sample farmers. Besides, key informants interview was used to triangulate, validate, and enrich the findings of the household interview. Results Results of the tobit model regression revealed that households’ level of literacy, milk yield, income, training, access to extension service, mobile ownership, supplementation of concentrated feed and hybrid cattle ownership were found to have a positive and statistically significant relationship with adoption and intensity of AI technology, whereas distance to farmer training centre (FTC) office had shown a negative relationship. Conclusions Adoption of context-based AI technology plays a paramount importance in achieving farm household's food security. The extension system should give more emphasis to the capacity building which is pivotal for introducing, adoption, and scaling out of best practices of dairy technologies. Besides the effort of the government, the participation of the private sector in AI technology is important to achieve wider adoption of AI technology.

The use of row planter in Ethiopia for sesame production is almost at the infant stage, and most seeds were typically sown through manual broadcasting as the tariff of imported agricultural machinery (row planter) is high. This shows that poor and small-scale farmers are unable to purchase row planter/sesame seed driller machine/ as its cost is expensive and their land is small. Hence, this study has assessed farmers' willingness to pay to rent sesame seed driller machine service by conducting a survey of 124 farmers in Kafta-humera district, western Tigray, Ethiopia. A survey questionnaire related to CVM was designed and face-to-face interviews were made to collect the data. The descriptive result showed that 85.48% of the farmers were willing to rent the Sesame seed driller machine with a mean of ETB 911.37 per hectare. The Probit regression results confirm that the educational level, access to extension service, the income of the household, and access to credit were the factors that affecting the farmers’ level of willingness to pay positively. However, the cultivable land size was negatively influencing willingness to rent sesame seed driller machine by the farmers. Regarding the perception of farmers, majority of the respondents were perceived positively particularly with the statements of “sesame seed driller machine decreases weed occurrence and makes easy to control weed, increases sesame grain yield and it makes farmers financially profitable". However, they perceived negatively on that it drills a higher seed rate and missed plant to some extent. The study, therefore, recommends encouraging well educated and better off people to engage in sesame farming, overhauling agricultural extension services. Moreover, it is suggested that investors, cooperatives or private companies should introduce sesame seed driller machine not only for themselves but also to rent service at a fair price.