Master's Thesis from the year 2013 in the subject Agrarian Studies, Wollega University (School of graduate studies), language: English, abstract: This study analyzed factors affecting modern agricultural technology adoption by farmers and the impact of technology adoption decision on the welfare of households in the study area. The data used for the study were obtained from 145 randomly selected sample households in the study area. Binary logit model was employed to analyze the determinants of farmers’ decisions to adopt modern technologies. Moreover, the average effect of adoption on household incomes and expenditure were estimated by using propensity score matching method. The result of the logistic regression showed that household heads’ education level, farm size, credit accessibility, perception of farmers about cost of the inputs and off-farm income positively and significantly affected the farm households’ adoption decision; while family size affected their decision negatively and significantly. The result of the propensity score matching estimation showed that the average income and consumption expenditure of adopters are greater than that of non-adopters. Based on these findings it is recommended that the zonal and the woreda leaders extension agents farm and education experts, policy makers and other development oriented organizations have to plan in such a way that the farm households in the study area will obtain sufficient education, credit accessibilities and also have to train farmers to make them understand the benefits obtained from adopting the new technologies. These bodies have also to arrange policy issues that improve farm labour participation of household members and also to arrange the ways in which farmers obtain means of income outside farming activities.

This paper reviews different studies on technology adoption in sub-Saharan Africa to understand the determinants of low adoption of improved technologies, with a special focus on Malawi. This will in turn help explain why there is a gap between awareness and adoption of agriculture technologies. As evidenced from the results of the FGDs conducted in Malawi in 2018, despite the visible benefits of the new technologies, farmers often do not adopt or take a long time to adopt them. This creates a gap between awareness of agriculture technologies and their adoption. The existing literature from sub-Saharan Saharan Africa, demonstrates that adoption, as a decision-making process, is affected by farmers’ access to information, their financial and human capital, incentives and external programs, plus farmers’ attitude to risk.

"Agricultural technologies are considered as efficient instruments to support rural and economic development. In general, socio-economic factors are considered as the main determinants that delay or encourage the adoption of improved technologies. Other predictors such as health factors have rarely been included in studies as determinants of (non)adoption (Ersado et al 2004). As a result, this study attempts to determine whether or not health factors (farmers' health status and accessibility to healthcare services) negatively and significantly influence the adoption of improved agricultural technologies. A Tobit model and a bivariate probit model were designed to evaluate the hypothesis that health factors significantly and negatively impact the adoption of improved maize seeds and inorganic fertilizers in Malawi (Southern Africa). The study uses data from the 2010-2011 Malawi Third Integrated Household Survey (Malawi 2010-2011 IHS3). Overall, findings from this analysis support the hypothesis that longer distances to places were farmers can buy medication negatively and significantly impact the adoption of improved technologies; especially in the case of inorganic fertilizers. The results, however, do not indicate that chronic sickness significantly impact adoption behavior; although the impact is negative. Additionally, the results suggest that socio-economic factors that significantly influence the adoption of hybrid maize seeds and inorganic fertilizers include: education, plot ownership, hired labor, and the price of chemical fertilizers. These results, in part, support policies designed to improve healthcare systems and strengthen collaborative work between the health and agricultural sectors. " --

Since agriculture is one of the key parameters in assessing the gross domestic product (GDP) of any country, it has become crucial to transition from traditional agricultural practices to smart agriculture. New agricultural technologies provide numerous opportunities to maximize crop yield by recognizing and analyzing diseases and other natural variables that may affect it. Therefore, it is necessary to understand how computer-assisted technologies can best be utilized and adopted in the conversion to smart agriculture. Modern Techniques for Agricultural Disease Management and Crop Yield Prediction is an essential publication that widens the spectrum of computational methods that can aid in agriculture disease management, weed detection, and crop yield prediction. Featuring coverage on a wide range of topics such as soil and crop sensors, swarm robotics, and weed detection, this book is ideally designed for environmentalists, farmers, botanists, agricultural engineers, computer engineers, scientists, researchers, practitioners, and students seeking current research on technology and techniques for agricultural diseases and predictive trends.

Agriculture has been an enduring human tradition key to survival and civilization. However, after the advent of industrialization and agricultural growth, the industry has been met with several challenges including pollution, land use, and food insecurity. With the agricultural industry contributing to pollution and emissions, many have found it imperative to investigate the causes and seek out solutions. The Research Anthology on Strategies for Achieving Agricultural Sustainability discusses the issues that the agricultural industry currently faces and the technological opportunities that can be explored to help protect and predict crop growth and achieve more resilient agricultural processes. It analyzes the impact of agricultural pollution and food insecurity on a global scale, but also proposes solutions to promote agricultural sustainability. Covering topics such as bio-farming, smart farming, and population growth, this book is an indispensable resource for government officials, agricultural scientists, farmers, students and professors of higher education, activist groups, researchers, and academicians.